An Application of Lean Thinking to the Furniture Engineering Process

Chao Wang

Thesis submitted to the Faculty of Virginia Polytechnic

Institute and State University in partial fulfillment of
the requirements for the degree of

MASTER OF SCIENCE
in
Forest Products

Approved by:

Henry Quesada-Pineda
Urs Buehlmann
D. Earl Kline

March 21, 2011

Blacksburg, Virginia

Key words: Lean engineering, Furniture engineering process, Value Stream Mapping, Engineering lead
time
 An Application of Lean Thinking to the Furniture Engineering Process

Chao Wang
(Abstract)

Efficient engineering processes are critically important for furniture manufacturers. Engineering impacts the production
cost, design quality, product lead time, and customer satisfaction. This research presents a systematic approach to
analyze a furniture engineering process through a case study. The research was conducted through a case study in a
furniture plant located in China, producing American style furniture products. The first stage was to investigate the
company’s current engineering process, identify non value-added activities, and analyze the engineering performance
based on selected Key Performance Indicators (KPIs) such as lead time, document error rate, and engineering
throughput. A survey questionnaire was sent out to the engineering group to determine the current engineering
efficiency.

Results show that ―product complexity‖ and ―engineer competency‖ are the two most influential factors that impact
engineering lead time and quality. In the second stage, value stream mapping was used to analyze an upholstery
furniture engineering process. The approach encompasses an analysis of the current state of the engineering process
and the proposal of a lean future state value stream map (VSM).

Results from the current state VSM show, that the value-added ratio of the current engineering process is only 26%.
Several engineering steps present deficiency such as the processes of creating drawings, compile mass production
documents, check and sign-off engineering documents, create CNC programs, and generate packaging files. Based on
current state VSM analysis, the researcher focused on transforming these processes to eliminate waste and to propose
the best practices for the future state VSM.

From this research, it shows that current processes include a large amount of non-value adding activities such as
waiting, extra processing, rework, excess motion, transportation, underutilized people, and inefficient information.
These non-value adding activities are interfering with engineers’ ability to prepare engineering documents for
downstream jobs and affecting the overall manufacturing process. The VSM is effective to provide the visual control
over the engineering process for implementing lean transformations.

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 Acknowledgements

I would like to thank the following people for their support throughout this research project:

My most sincere appreciation to Dr. Henry Quesada-Pineda for giving me this opportunity to conduct the research.
He has provided me with encouragement, support and guidance over the past two years. Thank you very much.

My great appreciation to Dr. Urs Buehlmann and Dr. D. Earl Kline for their support and instruction as my
committee.

My thanks to Omar Espinoza and Qinghua Liu for their assistance throughout this research project.

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 Preface

This thesis consists of five sections. Chapter one starts with introduction, motivation, justification of this research.
Chapter two reviews the literature on lean thinking, engineering processes, and the lean implementations of the wood
furniture industry. Chapter three discusses the general methods for the research including questionnaire design, travel
plan, data collection, data analysis, results, and conclusion. Chapter four discusses the results obtained from the survey
questionnaire applied in the engineering group of the case study company. Chapter five conducts a value stream
mapping (VSM) lean transformation to streamline an upholstery engineering process.

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 Table of Contents
List of Figures………………………….………………………………………………………………………………..vii
List of Tables…………………………………………………………………………………………………………...viii

CHAPTER 1 INTRODUCTION ....................................................................................................................................... 1

1.1 INTRODUCTION .................................................................................................................................................................. 1
1.2 MOTIVATION...................................................................................................................................................................... 1
1.3 JUSTIFICATION ................................................................................................................................................................... 2
1.4 PROBLEM STATEMENT ....................................................................................................................................................... 3
1.5 GOAL AND OBJECTIVES ...................................................................................................................................................... 4
1.6 EXPECTED OUTPUT............................................................................................................................................................. 4
CHAPTER 2 LITERATURE REVIEW ............................................................................................................................ 5
2.1 FURNITURE INDUSTRY ....................................................................................................................................................... 5
2.2 ENGINEERING DESIGN ........................................................................................................................................................ 6
2.2.1 The role of engineering in a product life-cycle ......................................................................................................... 6
2.2.2 Process engineering .................................................................................................................................................. 7
2.2.3 Engineering performance indicators ......................................................................................................................... 7
2.2.4 Lean engineering ....................................................................................................................................................... 8
2.2.5 Concurrent engineering .......................................................................................................................................... 11
2.3 LEAN THINKING ............................................................................................................................................................... 11
2.4 LEAN TOOLS AND APPLICATIONS...................................................................................................................................... 13
2.5 SUMMARY OF LITERATURE REVIEW ................................................................................................................................. 17
CHAPTER 3 METHODOLOGY .................................................................................................................................... 18
3.1 INTRODUCTION ................................................................................................................................................................ 18
3.2 QUESTIONNAIRE DESIGN .................................................................................................................................................. 19
3.2.1 Company selection .................................................................................................................................................. 19
3.2.2 Design questionnaire sections and relevant questions ............................................................................................ 19
3.2.3 Phone Interview....................................................................................................................................................... 20
3.3 ON-SITE STUDY PLAN ....................................................................................................................................................... 20
3.4 QUESTIONNAIRE APPLICATION ......................................................................................................................................... 22
3.4.1 Questionnaire application ....................................................................................................................................... 22
3.5 VSM DATA COLLECTION AND INTERVIEW........................................................................................................................ 22
3.5.1 Determine customer demand ................................................................................................................................... 22
3.5.2 Identify supplier and customer boundary requirements .......................................................................................... 23
3.5.3 Process Metrics ....................................................................................................................................................... 24
3.5.4 Waste and error Investigation ................................................................................................................................. 24
3.6 DATA ANALYSIS ............................................................................................................................................................... 24
3.6.1 Questionnaire analysis ............................................................................................................................................ 25
3.6.2 Current State Value Stream Mapping ..................................................................................................................... 25
3.6.3 Future State Value Stream Mapping ....................................................................................................................... 26
3.7 SUMMARY OF METHODOLOGY ......................................................................................................................................... 26
CHAPTER 4 MEASURING ENGINEERING PROCESS EFFICIENCY ..................................................................... 27
4.1 ABSTRACT ....................................................................................................................................................................... 27
4.2 INTRODUCTION ................................................................................................................................................................ 27
4.3 THEORETICAL BACKGROUND........................................................................................................................................... 28

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 4.4 METHODS......................................................................................................................................................................... 28
4.5 RESULTS AND DISCUSSION............................................................................................................................................... 29
4.5.1 Engineering experience and awareness of lean concepts and problem-solving methods ....................................... 29
4.5.2 Engineering process metrics ................................................................................................................................... 31
4.5.3 Factors affecting engineering lead time .................................................................................................................. 32
4.5.4 Factors affecting job completion and accuracy ...................................................................................................... 35
4.6 ENGINEERING CHANGE .................................................................................................................................................... 36
4.6.1 Error rates ............................................................................................................................................................... 36
4.6.2 Engineering Change ................................................................................................................................................ 38
4.7 CONCLUSIONS .................................................................................................................................................................. 38
CHAPTER 5 USING VALUE STREAM MAPPING TO ANALYZE AN UPHOLSTERY ENGINEERING PROCESS
.......................................................................................................................................................................................... 40
5.1 ABSTRACT ....................................................................................................................................................................... 40
5.2 INTRODUCTION ................................................................................................................................................................ 40
5.3 LITERATURE REVIEW ....................................................................................................................................................... 41
5.3.1 Lean engineering ..................................................................................................................................................... 41
5.3.2 Value Stream Mapping (VSM) in wood products industry ...................................................................................... 43
5.4 METHODS......................................................................................................................................................................... 43
5.5 RESULTS .......................................................................................................................................................................... 44
5.5.1 General Engineering Function ................................................................................................................................ 44
5.5.2 Product family and customer demand analysis ....................................................................................................... 46
5.5.3 Process analysis ...................................................................................................................................................... 48
5.5.4 Process metrics and unit ......................................................................................................................................... 51
5.5.5 Process cycle time and Lead Time .......................................................................................................................... 52
5.5.6 Value Stream Mapping – Current State .................................................................................................................. 53
5.5.7 Current State Analysis ............................................................................................................................................. 57
5.5.8 Root Causes Analysis: ............................................................................................................................................. 59
5.5.9 Future State Analysis: ............................................................................................................................................. 60
5.6 CONCLUSIONS: ................................................................................................................................................................. 65
REFERENCE: ................................................................................................................................................................. 67
APPENDIX A QUESTIONNAIRE .................................................................................................................................. 71
APPENDIX B PERMISSION TO USE FIGURE 2.1 ...................................................................................................... 76

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 LIST OF FIGURES

FIGURE 1.1 PRODUCT COST VERSUS TIME .............................................................................................................. 2

FIGURE 2.1 IMPORT MARKET SHARE OF NON-UPHOLSTERED WOOD HOUSEHOLD FURNITURE............. 5
FIGURE 2.2 COST INCURRED TO FIX MISTAKES IN PRODUCT LIFE CYCLE AND THE CORRESPONDING
LEVEL OF CONTROL...................................................................................................................................................... 8
FIGURE 2.3 THE FIVE LEAN PRINCIPLES ................................................................................................................ 13
FIGURE 3.1 METHODOLOGY USED TO DEVELOP SURVEY, COLLECT, AND ANALYZE DATA .................. 18
FIGURE 3.2 VALUE STREAM MAPPING METHOD ................................................................................................. 26
FIGURE 4.1 ENGINEERING EXPERIENCE OF UPHOLSTERY GROUP ................................................................. 30
FIGURE 4.2 ENGINEERING EXPERIENCE OF SOLID WOOD GROUP .................................................................. 30
FIGURE 4.3 KNOWLEDGE OF LEAN CONCEPTS AND PROBLEM-SOLVING METHODS ................................ 31
FIGURE 4.4 IDENTIFIED ENGINEERING PERFORMANCE METRICS .................................................................. 32
FIGURE 4.5 ENGINEERING LEAD TIME VERSUS PRODUCTION LEAD TIME IN TWO ENGINEERING
GROUPS .......................................................................................................................................................................... 33
FIGURE 4.6 PERFORMANCE DIFFERENCE USING SOLIDWORKS AS THE PRIMARY ENGINEERING
DESIGN TOOL ................................................................................................................................................................ 33
FIGURE 4.7 AVERAGE LEAD TIME DISTRIBUTION OF EACH PRODUCT ......................................................... 34
FIGURE 4.8 AVERAGE ENGINEERING LEAD TIME FOR EACH PRODUCT ....................................................... 35
FIGURE 4.9 AVERAGE CUSTOMER NUMBER ......................................................................................................... 35
FIGURE 4.10 RESPONDENT DISTRIBUTION ON ENGINEERING THROUGHPUT ............................................. 36
FIGURE 4.11 THE AVERAGE NUMBER OF PREPRODUCTION AND MASS PRODUCTION DOCUMENTS. .. 36
FIGURE 4.12 RESPONDENT DISTRIBUTION OF ENGINEERING ERROR RATE IN SOLID WOOD
ENGINEERING GROUP ................................................................................................................................................. 37
FIGURE 4.13 RESPONDENT DISTRIBUTION OF ENGINEERING ERROR RATE IN UPHOLSTERY
ENGINEERING GROUP ................................................................................................................................................. 37
FIGURE 4.14 RESPONSE RATE ON ECO PERCENTAGE ......................................................................................... 38
FIGURE 4.15 TIME SPENT ON ECO ............................................................................................................................ 38
FIGURE 5.1 A TYPICAL FURNITURE ENGINEERING PROCESS BY USING FUNCTIONAL FLOW CHART .. 45
FIGURE 5.2 CUSTOMER DEMAND OF UPHOLSTERY PRODUCTS ...................................................................... 47
FIGURE 5.3 ENGINEERING DESIGN CONTEXT DIAGRAM................................................................................... 48
FIGURE 5.4 GROUP SMALL EVENTS INTO INDIVIDUAL ACTIVITY.................................................................. 54
FIGURE 5.5 CURRENT STATE VALUE STREAM MAPPING (VSM) ...................................................................... 56
FIGURE 5.6 TAKT TIME VERSUS PROCESS CYCLE TIME .................................................................................... 57
FIGURE 5.7 ROOT CAUSES OF TWO MAJOR PROBLEMS ..................................................................................... 59
FIGURE 5.8 FUTURE STATE VALUE STREAM MAPPING (VSM) ......................................................................... 63

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 LIST OF TABLES

TABLE 1.1 DIFFERENT TYPES OF WASTE IN AN ENGINEERING PROCESS ....................................................... 3

TABLE 2.1 SIMULATION METHODS AND OUTCOMES OF REDUCING ECO LEAD TIME ................................ 7
TABLE 2.2 ENGINEERING PERFORMANCE INDICATORS ...................................................................................... 8
TABLE 2.3 RESULTS OF LEAN SOFTWARE DEVELOPMENT PROCESS ............................................................ 10
TABLE 2.4 LITERATURE ON LEAN PRODUCT DEVELOPMENT AND ENGINEERING .................................... 10
TABLE 2.5 DEGREE OF CE IMPLEMENTATION ...................................................................................................... 11
TABLE 2.6 WASTE MODEL IN ADMINISTRATIVE AREA ..................................................................................... 12
TABLE 2.7 LEAN TOOLS AND METHODS ................................................................................................................ 15
TABLE 2.8 ADMINISTRATIVE LEAN TOOLS FOR DIFFERENT LEVELS OF USE ............................................. 15
TABLE 2.9 APPLICATIONS OF LEAN IN THE FURNITURE INDUSTRY .............................................................. 16
TABLE 2.10 SUMMARY OF LITERATURE REVIEWED .......................................................................................... 17
TABLE 3.1 PROJECT AGENDA DURING CASE STUDY .......................................................................................... 21
TABLE 3.2 ACCESSING THE CUSTOMER DEMAND .............................................................................................. 23
TABLE 3.3 DATA COLLECTION FOR CERTAIN TYPE OF UNITS......................................................................... 23
TABLE 3.4 WASTE ANALYSIS AND DATA COLLECTION METHOD .................................................................. 24
TABLE 4.1 METRICS ..................................................................................................................................................... 32
TABLE 5.1 LEAN PRACTICES IN SOFTWARE ENGINEERING .............................................................................. 42
TABLE 5.2 LITERATURE ON LEAN PRODUCT DEVELOPMENT AND ENGINEERING .................................... 43
TABLE 5.3 INDICATORS FOR PRIMARY PROCESS ................................................................................................ 47
TABLE 5.4 MAIN ENGINEERING PROCESS ............................................................................................................. 50
TABLE 5.5 ENGINEERING PROCESS ......................................................................................................................... 51
TABLE 5.6 DEFINITION OF EACH PROCESS METRIC............................................................................................ 52
TABLE 5.7 VALUE-ADDED TIME VERSUS NON-VALUE-ADDED TIME ............................................................ 53
TABLE 5.8 RESTRUCTURED PRIMARY ENGINEERING PROCESS ...................................................................... 55
TABLE 5.9 INTERRUPTIONS IN THE ENGINEERING PROCESS ........................................................................... 59
TABLE 5.10 SUMMARY OF COUNTERMEASURES AND KAIZEN IMPLEMENTATION ................................... 64
TABLE 5.11 METRICS COMPARISON – CURRENT STATE VERSUS FUTURE STATE ...................................... 65

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 CHAPTER 1 INTRODUCTION

1.1 Introduction

Presently, furniture manufacturers have been searching for effective Lean Thinking principles to reduce cost, improve
quality, and shorten time-to-market to increase their competitive advantage in the market place. Schuler and
Buehlmann (2003) indicate that lean manufacturing is an essential element for the strategic renewal of a business
model for the U.S. furniture industry. Another investigation of 145 wood products companies in the US, Cumbo, Kline,
and Bumgardner (2006) indicates that a majority (55%) of these companies had been implementing lean manufacturing
at the time of the study. The research concluded that 56% of cabinets makers, 71% of upholstered and 53% non-
upholstered furniture manufacturers indicated they were implementing lean manufacturing. Quesada-Pineda and Gazo
(2007) report that lean manufacturing practices, like pull system scheduling, are positively related to the performance
of furniture manufacturing companies.

Lean principles encompass systematic approaches for both administration (Beau Keyte and Locher, 2004) and
manufacturing level processes (Rother and Shook, 1998). Lean administration initiatives help people eliminate waste
and improve work efficiency in nonproduction areas such as accounting (Maskell and Baggaley, 2003), engineering
(Middleton, Flaxel, and Cookson, 2005; Haque, 2003; Freire and Alarcón, 2002) and service (Bowen and Youngdahl,
1998), while lean manufacturing performs a lean transformation for the production process improvement such as
automobile manufacturing (Womack, Jones, and Roos, 1990), aerospace production (Murman and Allen, 2002), or the
PC fabrication process (Ben Naylor, Naim, and Berry, 1999).

In the secondary wood products industry, research has been conducted in the use of lean tools and methods to eliminate
waste and improve production efficiency in manufacturing processes (Hunter, 2008; Motsenbocker et al., 2005; Hunter,
Bullard, and Steele, 2004). However, little attention is given in the application of lean to nonproduction areas such as
design, new product development (NPD), engineering, and product development (PD) (Baines et al., 2006). Since over
70% of production costs are determined at the product design stage (Boothroyd, Dewhurst, and Knight, 2001), lean
strategies in the product development process will give manufacturers more opportunity to achieve further
improvements and enhance performance.

Like other manufacturing industries, the role engineering plays is important within product development in the wood
furniture industry as it realizes design concepts, facilitates mass production and mass customization (Lihra, Buehlmann,
and Beauregard, 2008). However, many furniture manufacturers do not have an efficient engineering process (Huang
and Mak, 1998). As a result, problems are manifested in longer processing times of drawings which lead to production
delays, an increase in engineering errors that affect product quality, higher costs, and excessive changes of design and
waste. These problems negatively impact the engineering efficiency and affect the overall manufacturing processes in
the downstream.

Therefore, applying lean thinking to the engineering process would greatly benefit furniture manufacturers in today’s
competitive market place. This research incorporates two parts in introducing lean thinking to the furniture engineering
process. The first part is the analytical research of a furniture engineering process in a case study company. The second
part encompasses an in-depth analysis of the engineering value stream and utilizes the value stream mapping (VSM)
method to implement a lean application within the engineering department for that company.

1.2 Motivation

Engineering is an important stage in the product life-cycle because it determines the manufacturability of products and
their production costs. In Figure 1.1, as the product is designed, there is just 8% of the budget (incurred cost) spent, but
80% cost of the product (permitted cost) is determined (Anderson, 1990). Also, Boothroyd, Dewhurst, and Knight
(2001) stated that over 70% production cost is determined in the product design stage. Further, Ehrlenspiel et al. (2007)
indicated that the decision made within the product development stage has a great impact on cost through the product

1
life-cycle. Thus a lean and effective engineering process is important to the furniture manufacturers to control the
product costs in the product life-cycle.

Figure 1.1 Product cost versus time

Product quality is another internal factor for conducting this research. Morgan and Liker (2006) described the
engineering process as “raw material consists of information – customer needs, past product characteristics,
competitive product data, engineering principles, and other inputs that are transformed through the product
development process into the complete engineering of a product that will be built by manufacturing.” Research on
engineering process for optimizing product quality has been reported (Freire and Alarcón, 2002; Loch and Terwiesch,
1999; Thomas Culbreth, Miller, and O'Grady, 1996). Thus, the lean engineering process is essential to ensure the
quality of products.

Researchers have expressed the necessity to conduct research on furniture engineering. Schuler and Buehlmann (2003)
indicated that future successful furniture manufacturers have to figure out how to provide special services to their
customers in the fields of designing and engineering of their products. Lihra, Buehlmann, and Beauregard (2008) also
described engineering as an important process in the value stream to help furniture manufacturers realize mass
customization. Quesada-Pineda and Gazo (2007) indicated that product design and engineering is a key performance
measure for the wood furniture industry.

However, there is no systematic approach in the furniture industry to measure the internal engineering processes like
designing, reviewing, checking, and releasing to accommodate the production deadlines.

1.3 Justification

The primary focus of this research is to identify the function of engineering to determine product lead time, quality, and
cost in the wood furniture industry. The secondary focus of this research is to use the value stream mapping method to
analyze the current state of a furniture engineering process and to use lean principles to design future state value stream
mapping based on proposed improvements.

The furniture industry is dependent on raw materials and labor which are the major elements comprising production
costs. However, design and engineering process are critical steps in determining the production cost because
inappropriate design will lead to unnecessary waste and effort in the late manufacturing process. Furthermore, product
quality is also specified at the design stage (Thomas Culbreth, Miller, and O'Grady, 1996). Thus, furniture
manufacturers are obligated to build and explore more radical changes to the process of product design and engineering.

Currently, the furniture industry is transitioning from mass production to mass customization (Lihra, Buehlmann, and
Beauregard, 2008). The product complexity and frequency of new introductions makes it difficult for product
engineering to catch up with the production pace, which tends to cause shipment delays, inferior quality, and excessive

2
costs. An efficient engineering process will allow the furniture manufacturers to have more flexibility and control in
delivering desired products and services to the customer. As Karlsson and Ahlstrom (1996) indicated, lean product
development provides the potential to ―faster product development with fewer engineering hours, improve
manufacturability of products, higher quality products, fewer production start-up problems, and faster to market‖. Lean
engineering is one of the important functions within lean product development; it exhibits great potential to facilitate
and extend the advantages achieved in the manufacturing context.

Although engineering research has been conducted in the furniture industry (Min, Cheng, and Qiao-yun, 2010; Thomas
Culbreth, Miller, and O'Grady, 1996), it is still lacking a systematic method to streamline the engineering process.
There is no study showing the impact of engineering in the product life-cycle for furniture manufacturers. The relevant
research on analyzing two important elements in the furniture engineering system – people and process, has received
less attention.

1.4 Problem statement

As 70% of production costs are determined at product design stage (Boothroyd, Dewhurst, and Knight, 2001), lean
implementation applied to design and engineering processes should receive more attention than that applied to the
production area. It is easy to see that many furniture manufacturers do not have an efficient engineering process.
Similar to the situation of most design companies in the other manufacturing businesses, drawing or production
documents are controlled merely by the released date without having a quantified method to measure each internal
design process such as designing, reviewing, checking, and releasing (Freire and Alarcón, 2002).

Engineering coordinates and interconnects with other administrative functions within a company. As Rother and Harris
(2001) described, ramp-to-ramp value stream mapping is supposed to depict this situation where engineering
communicates with its internal suppliers and customers. To streamline this value stream, many obstacles need to be
overcome first within the process. Table 2.1 shows nine types of obstacles and its corresponding example in the
furniture engineering process:

Table 1.1 Different types of waste in an engineering process

Categories Problem (obstacles)
Overproduction Excessive orders (drawings) not in need for the downstream process
Correction  Engineering changes
 Engineering design errors
 Reprinted drawings
Material movement  Unnecessary steps to move drawings
 Multiple approval steps
Processing  Constant interruptions while creating drawings
 Various copies/formats of drawings
Inventory  Work-in-progress (WIP) drawings or orders
Waiting  Waiting of design confirmation from customers
 Waiting information from other departments
 Downtime of office automation system
Motion  Walking to copy machine
Underutilized people  Unevenly distributed workload
 Limited authority to engineers
Information flow  Inefficient office automation system for engineering request
 Inefficient communication within departments

Consequently, the above problems lead to longer drawing processing times which result in production delays, high
rates of engineering errors affecting product quality, higher production costs and excessive waste caused by the
engineering changes.

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Therefore, it is important to use visualization tools to identify waste and non-value-added steps in the product
development process. Former research of lean implementation in furniture industry was just focused on improving
production efficiency and productivity (Espinoza, 2009; Hunter, 2008; Czabke, 2007; Motsenbocker et al., 2005;
Hunter, Bullard, and Steele, 2004). Research on lean application of engineering area in the furniture industry has not
been studied.

1.5 Goal and objectives

The goal of this research is to apply lean engineering principles to the wood furniture industry in order to increase
productivity, eliminate waste, and increase internal customer satisfaction. Specifically, the objectives of this study are:

 Analyze the current engineering performance and key performance indicators through survey questionnaires in the
engineering group of the case study company.
 Evaluate current state VSM of furniture engineering processes to identify both value-added and non-value-added
engineering activities towards fulfilling customer requirements.
 Future state will be analyzed and evaluated according to process efficiency and Key Performance Indicators (KPIs)
found through survey questionnaire and on-site study analysis to provide solutions for how valid and useful the
future state would be to the industry.

1.6 Expected output

 Lean engineering model for wood furniture product development and propose best lean engineering process
solutions for potential industrial participants.
 Lean engineering tool kits for furniture manufacturers. Identify causes of engineering waste from current state
VSM and explore methods (kaizen events) to eliminate waste based on questionnaires and process data analysis to
depict future state VSM.
 Implementation plan for improving the engineering process of the case study company.

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 CHAPTER 2 LITERATURE REVIEW

2.1 Furniture industry

In the 1800s, the US furniture industry enjoyed a boom on the East Coast. After that, the furniture industry experienced
three major transitions. The first transition happened in the late 1800s, when Cincinnati replaced the East Coast area as
the leading center for furniture production (Oliver, 1966). The second transition happened between 1880 and 1910,
when Grand Rapids, Michigan, became the leading production center. However, as resources in Grand Rapids were
depleted at the same time as the Great Depression in 1930s, Michigan manufacturers lost their primary advantage and
left mass marketing to manufacturers in the southern states such as North Carolina and Virginia, which formed the third
transition. Since then, High Point, North Carolina, has developed into the furniture industry center.

The structure of the US wood household furniture industry is highly fragmented (Grushecky et al., 2006; West and
Sinclar, 1992). Furniture manufacturers resist consolidation. Upholstery manufacturers do not want work in the case
goods business. Mass producers have little association with small cabinet makers. Southern producers rely on
southeastern wood species while the northern manufacturers prefer resources close to their locations. The product
construction methods are different between the North and the South. The National Association of Furniture
Manufacturers (NAFM) represents the small and family-owned businesses, while the Southern Furniture Manufacturers
Association (SFMA) represents large family-owned companies in the South (Dugan, 2009).

In the advent of globalization, the US furniture industry is experiencing tumultuous change as major manufacturers are
losing ground because of global competition (Drayse, 2008). Southern manufacturers have been facing competitiveness
from exporters outside of the US. The imports of non-upholstered wood household furniture increased from 19% in
1992 to 64% market share in 2008 (Figure 2.1). The output of US furniture manufacturing increased slowly and
employment has fallen sharply in the midst of global competition and economic recession in recent years.

Figure 2.1 Import market share of non-upholstered wood household

furniture (1992 to 2008), adapted from (Buehlmann and Schuler, 2009)

Furniture manufacturing exhibits complexity in terms of characteristics of the industry and furniture manufacturing
process (Thomas Culbreth, Miller, and O'Grady, 1996):

In regard to complexity of the industry, the following aspects are noted:

 Manufacturers provides large product offerings which results in diverse parts population
 Pressure to frequently introduce new products and redesigns
 Competitive pressure to shorten lead time for quick delivery of products

5
 Due to the frequent new product introduction, a typical facility has to design large amount of new parts every year

In regard to the perspective of complexity in the manufacturing process, the following characteristics can be identified:
 Many furniture parts present complex geometry instead of rotational or prismatic shapes.
 The variety of wood properties contributes to the difficulties of machining characteristics and processes
 The presence of surface imperfections will affect the value of the final products
 Wood machining process has to take consideration of dimensional variation of wood
 Scrap tends to be generated from the machining processes

The above complexities in the nature of the business, manufacturing process and customization lead to intense
competition, high labor cost, and a fragmented market that is creating vulnerability in the industry owing to global
competition (Drayse, 2008). Due to the large product offerings and frequent new product introductions, manufacturers
have to carry large inventories and frequently introduce new product designs which inevitably increase the production
cost and lead time. Also, many manufacturers are reluctant to adopt new technologies which can help upgrade
fabrication efficiency and improve product quality (Scott, 2006). The complex manufacturing processes increase the
labor cost and generate scraps which impact the manufacturing competitiveness in terms of quality and cost (Vickery,
Dröge, and Markland, 1997). These underlying disadvantages in the furniture industry drives the downstream
customers such as retailers and distributors look for alternative places to make their products.

Consolidation is considered a solution for the US furniture industry (Drayse, 2008; Quesada and Gazo, 2006). However,
the furniture industry is much more fragmented than other manufacturing industries. It is hard to acquire the knowledge
of how much market share of each major player has. The competition is fierce within the industry and no one holds a
sustainable competitive advantage (Dugan, 2009).

Furthermore, by researching the literature, Vickery, Dröge, and Markland (1997) identified ten manufacturing
competitive priorities for the furniture industry which include flexibility in three areas: product (customization),
process (mix), and volume. Also included are low production costs, new product introductions, delivery speed and
dependability, quality (conformance to specification), product reliability, and design quality (design innovation). The
research reveals that manufacturing has primary responsibility for the new product process – design quality and new
product introduction. These two items are highly associated with efficient engineering methodologies such as Design
for Manufacturability (DFM) (Anderson, 1990) and innovation (Gupta and Wilemon, 1988).

2.2 Engineering design

2.2.1 The role of engineering in a product life-cycle

The importance of design and engineering process toward determining product cost can be found in some of the
literature. Anderson (1990) in his book ―Design for Manufacturability‖ mentions that “By the time a product has been
designed, only about 8% of the total product budget has been spent. But by that point, the design has determined 80%
of the cost of the product!” Boothroyd, Dewhurst, and Knight (2001) states that over 70% production costs are
determined in the product design stage. Ehrlenspiel et al. (2007) also discusses how significant the decisions made in
product development stage may have effects through the product lifecycle.

However, in traditional sequential product development processes, production engineers lack an effective
communication conduit with the product engineers. This misses the best opportunity to implement engineering rules
and principles, such as Design for Manufacturability (DFM), at an early design stage to optimize design for ease of
production and assembly process (Eppinger et al., 1994). Actually, engineering plays an important role to facilitate
DFM methodology. Not much research has been conducted on the effectiveness of DFM for addressing manufacturing
process and system issues (Boothroyd, Dewhurst, and Knight, 2001; Helander and Nagamachi, 1992; Anderson, 1990).
Although few engineering principles show the effectiveness in other industries, the furniture industry has seldom
utilized the same methodologies to facilitate design and engineering process (Huang and Mak, 1998).

6
2.2.2 Process engineering

Furniture product engineering essentially involves the coordination of different departments within the company as
well as different partners outside of the company. The information flows are quite important for effective engineering
communication within and outside of the company (Allen and Cohen, 1969). An efficient engineering process could
facilitate such an effective flow of communication (Freire and Alarcón, 2002). Indeed, furniture engineering is a
complex process and potentially hides lots of process improvement opportunities (SÜTÇÜ et al., 2005). Process
efficiency is an important metric to reflect process improvement and performance (B. Prasad, 1996). It measures how
well a process uses available resources to achieve anticipated results. Prasad (1996) also indicated there is an inverse
relationship between process efficiency and a product life cycle lead time. In Prasad’s model, he depicted (the Original
State of Process Configuration) that as the process efficiency improved the lead time was reduced. The improvement
results were impacted by different process configurations such as the lead time results from process renovation
configuration was better than lead time results from the process restructuring.

2.2.3 Engineering performance indicators

A significant driver of product development costs and lead time is engineering changes (Loch and Terwiesch, 1999).
Engineering changes (ECs) refers to making design changes to an existing product (Barzizza, Caridi, and Cigolini,
2001). It has a significant impact on new product development (NPD) process in terms of NPD success rates, and
occurrence of bottleneck activity, since engineering changes management always competes for the same resources as
new product development (Li and Moon, 2009).

Engineering changes occur after the engineering drawings are issued and before the product progresses into the
production process. However, in Figure 2.2, when late stages exist in product life cycle, the more costs occur in
production. Diprima identified and categorized three types of engineering changes: immediate, mandatory, and
convenience (Diprima, 1982). This classification was based on the degree of urgency. ―Immediate‖ means the EC
needs to be implemented now. ―Mandatory‖ means to implement an EC as soon as possible, while ―convenient‖ means
to implement EC as conveniently as possible (Diprima, 1982). Furthermore, a new taxonomy of EC was incorporated
(Barzizza, Caridi, and Cigolini, 2001). In these classifications, ECs were categorized as ―scrap‖, ―rework‖, and ―use-as-
is‖. ―Scrap‖ means serious technical faults and user safety problems exist and need to be solved immediately. ―Scrap‖
will directly affect the work in progress (WIP) inventory since this inventory cannot be applied to other products.
―Rework‖ means EC is required for improvements of pre-change WIP without affecting finished products and
components. ―Use-as-is‖ means a product has neither technical faults nor user-safety problems but a product is needed
to improve the design. ―Scrap‖ and ―rework‖ are inconsistent to ―immediate‖ in Diprima’s classification, while ―use-
as-is‖ could be coordinated with either ―mandatory‖ or ―convenience‖ in Diprima’s categories.

Loch and Terwiesch (1999) outlined strategies to reduce Engineering Change Orders lead time (in Table 2.1):

Table 2.1 Simulation methods and outcomes of reducing ECO lead time
Methods Description Outcomes
Flexible capacity Optimize utilization (the relationship Effective utilization factor goes down to 88% and helps
between capacity available and to decrease the throughput time from 25 hours to 14
capacity required) hours, a 44% reduction.
Merging tasks Combine works that were done by Total average throughput time reduces from 28 to 10
separate organizational entities before hours, a 64% reduction.
Balancing the Identify and bottleneck activity (high Total average throughput time for both testing activities
workload utilization) and shift partial jobs to reduces from 28 to 12 hours, a 57% reduction.
other activity for improvement of
overall performance
Pooling Sharing workloads among engineers Examples of pooling are not included in the article
Managing Reduce the set-up time between Holding the same batch size, utilization reduces to 82%,
batching problems activities the throughput time of one activity reduces 60%

7
ECs include changes for improving production efficiency by optimizing product architecture and fabrication process, as
well as the changes for correcting engineering errors and mistakes (Balakrishnan and Chakravarty, 1996). Freire and
Alarcón (2002) proposed two performance indicators for tracking both improvement change and the error correcting
change in the design process. The indicators are used to diagnose and evaluate the design process in the construction
industry (in Table 2.2):

Table 2.2 Engineering performance indicators

Indicators Calculation Description
Changes in design Number of changes divided by total The indicator helps to deliver the magnitude of changes
number of drawings (or documents) in projects
Errors/omissions Number of errors/total number of This indicator helps to measure the quality of drawings
drawings (documents) (or documents) in the design process

From the literature, it can be concluded that engineering changes have significant impacts on product development cost,
lead time, and quality. Certain indicators can be used to evaluate the engineering performance relevant to engineering
changes.

2.2.4 Lean engineering

Karlsson and Ahlstrom (1996) classified engineering as one of the interrelated techniques in Lean product development.
Morgan and Liker (2006) described the engineering process as “raw material consists of information – customer needs,
past product characteristics, competitive product data, engineering principles, and other inputs that are transformed
through the product development process into the complete engineering of a product that will be built by
manufacturing.”

As people paid more attention to implementing lean manufacturing and mapping manufacturing processes, they
overlooked the importance of design and engineering on costs in product life-cycle (Baines et al., 2006).

Figure 2.2 Cost incurred to fix mistakes in product life cycle and the corresponding
level of control (adapted from Prasad 1996)

Prasad (1996) depicts the trend of the cost to fix a mistake in the product life-cycle (Figure 2.2). A problem fixed at
the early stages of product life-cycle costs less than detecting and fixing it in the late stages. Also detecting and fixing
problems at early stages of the product life-cycle creates more opportunities for improvements. In Figure 2.2,
engineering is positioned at an early stage of product life cycle which indicates its important role in determining
production cost.

8
Furthermore, lean thinking principles are applied in production area which leads to the concept of ―lean manufacturing‖.
However, Womack and Jones (1996a) indicated that lean principles are also suitable for areas outside manufacturing
operations. Baines et al. (2006) saw that lean principles have more potential benefits when applied to knowledge-based
activities such as design, new product development (NPI), engineering and product development (PD) (Table 2.4).
Lean engineering research has been conducted in aerospace, automotive, software and construction industry (Middleton,
Flaxel, and Cookson, 2005; Liker, 2004; Haque, 2003; Freire and Alarcón, 2002).

Freire and Alarcón (2002) developed a lean design process for a construction project based on lean manufacturing
concepts and methods. They proposed four stages to carry out design process improvements:

• Diagnosis and evaluation

• Changes implementation
• Control
• Standardization

The research utilized seven lean tools on five potential improvement areas, which resulted in increased value-added
activities, reduced product unit errors, largely decreased waiting time, and enhanced cycle time utilization. Finally, the
overall performance of engineering products improved.

Haque (2003) conducted research of lean engineering in aerospace industry. He restated five-step lean principles
applied to a manufacturing process (Womack and Jones, 1996; Rother and Shook, 1998) and further redefined each
principle in a lean engineering manner. Then he applied three different lean applications (Kaizen on a design process,
Single piece flow in New Product Introduction (NPI), off-line development to speed time to market) at three different
levels – process hierarchy, detailed design, and project management, on three case study companies. He also mentioned
the importance of modular design as a lean tool to facilitate product engineering on easing future modification or
evolution of products and the reuse of design elements. In a case of illustrating ―off-line development of products‖,
modular design showed its effectiveness on reducing lead time by 25 to 50 percent.

Middleton, Flaxel, and Cookson (2005) presented an application of how the lean manufacturing concepts could be
transferred to lean implementation of software development. The techniques and principles utilized to streamline the
software engineering process include:

• Continuous-flow processing
• Customer defined value
• Design structure matrix (DSM) and flow
• Takt time
• Linked processes
• Standardized procedures
• Eliminate rework
• Balancing loads
• Posting results
• Data driven decisions
• Minimize inventory

By implementing the above techniques, the benefits are identified into the following six aspects (in Table 2.3):

9
Table 2.3 Results of lean software development process
ID Results
1. Lean techniques take effect in helping diagram and refine processes to reduce process steps and travel distance,
while increasing the value added ratio in the process. For instance, one process which includes 498 steps has
been substantially improved.
2. Informal estimate by senior staff shows that there has been about a 25% productivity gain by implementing
lean in the last two years.
3. By applying a survey to QA engineers, technical writers and business system analysts inside the company, 55%
respondents agreed that lean is suitable to software development.
4. Quality is improved by knowing customer needs through interviews and surveys. The rework time on fixing
defects has a 65%-80% decrease.
5. Visual indicator in the process helps people know how much progress the current output goes towards fulfilling
time-related goals. It allows viewer to see whether the number of work units completed over time is reaching a
target.
6. The products developed through lean approach got positive responses from customers at a trade show.

Reinertsen (2005) incorporated how to utilize lean manufacturing methods to deal with the inherent variability in
product development process. Five key methods were applied to streamline the product development process; they are
queue management, batch size reduction, cadence, rapid local adjustments and waste elimination.

From the literature (Table 2.4), it shows that lean principles applied in production environment are applicable to
administrative area. Also different industries demonstrated the effectiveness of implementing lean in the administrative
processes. Most industries using lean to facilitate the product development and engineering processes are concentrated
in aerospace, construction, and software. From the literature, it also shows that the methodologies of lean engineering
still are not sufficient, coherent, and sustainable. Proper tools and applications are still missing.

Table 2.4 Literature on lean product development and engineering

Author Title Outcomes
Freire and Achieving Lean Design Process: Propose a methodology to achieve a lean design process
Alarcón 2002 Improvement Methodology for the construction industry by applying seven tools for
improvement based on five areas – client, administration,
project, resources, and information.
Haque 2003 Lean Engineering in the Aerospace Propose lean principles to three different levels of
Industry engineering processes:
• Detailed design level
• Project management level
• Design strategy level
Browning On Customer Value and Improvement in Demonstrate the effectiveness of ―maximizing value‖ as a
2003 Product Development Processes preferred way to incorporate ―lean‖ in the product
development process rather than ―minimizing cost and
time‖ as a preferred way to create customer value
Reinertsen Let It Flow Propose to apply five key methods of lean manufacturing
2005 to address the high inherent variability of product
development. The methods encompasses queue
management, batch size reduction, cadence, rapid local
adjustments, and waste elimination
Middleston et Lean Software Management Case Study: Demonstrate the effective application of lean principles in
al. 2005 Timberline Inc. software engineering.

10
2.2.5 Concurrent engineering

Concurrent engineering (CE) is an effective methodology used for improving engineering quality and reducing lead
time. Sprague, Singh, and Wood (2002) define concurrent engineering as ―a systematic approach to the integrated,
concurrent design of products and their related processes, including manufacture and support.‖ One of the biggest
applications of the concurrent engineering approach is the aerospace industry where different functional teams worked
in parallel and development process results could be rapidly verified from multiple options (Rush and Roy, 2000). The
most phenomenal result of concurrent engineering, compared to the traditional sequential engineering, is the reduction
of product development lead time, appreciation of total quality (quality of process, quality of organization, and product
quality), increased productivity and decreased costs (costs of rework, scrap, and delays) (Ghodous, Vandorpe, and
Biren Prasad, 2000).

The degree of implementing concurrent engineering could be divided into four categories (Table 2.5):

Table 2.5 Degree of CE implementation (O'Grady and Young, 1991)

Categories Description
One-way (―over the wall‖)  Designs are isolated from other functions then designs send to manufacturing.
 No consideration of different product life cycle factors
Stunted two-way  if necessary, minor changes will be made after designs are complete
Two-way  Designs are evaluated discretely
Integrated  Design are evaluated constantly

In the furniture industry, key factors of determining the benefits of CE are product complexity and product life-cycle
(Thomas Culbreth, Miller, and O'Grady, 1996). Complexity could be reflected on various style differentiations, part
geometries, and materials. Because of complexity, furniture manufacturing tends to have excessive machining
operations and relatively long lead times.

Thomas Culbreth, Miller, and O'Grady (1996) illustrated an application of concurrent engineering systems in furniture
automation process. The authors utilized constraint networks to represent the constraining impacts of an automation
process to realize the flexible automation. Min, Cheng, and Qiao-yun (2010) discussed the use of CE to modeling based
on feature modeling and modular design for board-type furniture. The CE system approach allows the company to
effectively reduce lead times by improving design for manufacturability. Designers are accessible to global information
provided by the CE system which helps determine proper fixture and cutting tool for production, so the potential
manufacturing problems and costs are reduced.

2.3 Lean thinking

The Lean Thinking initially received attention in 1990 (Womack, Jones, and Roos, 1990) in the study of manufacturing
performance in automobile industry between Western countries and Japanese car makers. They found that the average
time for a Japanese manufacturer to produce a car was 20 to 30 percent lower than its Western counterparts. After an
investigation of ―Toyota Production System (TPS)‖, they introduced the concept of ―Lean Production‖.

Lean Thinking gives us a solution to eliminate muda, a Japanese word meaning ―waste‖. Muda incorporates all kinds
of human activities that absorb resources without creating value (Womack and Jones, 1996). Ohno (1988) identifies
seven types of wastes through the observation of Toyota Production System:

 Overproduction
 Correction
 Material movement
 Processing
 Inventory
 Waiting

11
 Motion

Prasad (1996) expanded the definition of waste and tapped into engineering area by adding one more candidate to the
waste pool – waste of information flow. Waste of information flow refers to ―Unnecessary transfer of information
between two or more dissimilar systems (computer systems or otherwise)‖. Some examples of this type of waste
described by Prasad include: ―conversion from one format to the other‖, ―upload and download of information‖, ―files
retrieval and storage‖, ―unnecessary notification or notes‖, ―one-to-many communications instead of posting publicly
(many-to-many)‖, ―data security‖, etc.

By adapting seven types of waste in Ohno’s model in production area, Beau Keyte and Locher (2004) developed the
model to redefine the waste in administrative area. They also included ―Underutilized people‖ as the eighth waste
(Table 2.6):

Table 2.6 Waste model in administrative area

Waste Category Office Examples
1. Overproduction  Printing paperwork out before it is really needed
 Purchasing items before they are needed
 Processing paperwork before the next person is ready for it
2. Correction  Order entry errors
 Design errors and engineering change orders
 Invoice errors
 Employee turnover
3. Material movement  Excessive email attachments
 Multiple hand-offs
 Multiple approvals
4. Extra processing  Re-entering data
 Extra copies
 Unnecessary or excessive reports
 Transactions
 Cost accounting
 Expediting
 Labor reporting
 Budget processes
 Travel expense reporting
 Month-end closing activities
5. Inventory  Filled in-boxes (electronic and paper)
 Office supplies
 Sales literature
 Batch processing transactions and reports
6. Waiting  System downtime
 System response time
 Approvals from others
 Information from customers
7. Excess motion  Walking to/from copier
 Central filing
 Fax machine
 Other offices
8. Underutilized people  Limited employee authority and responsibility for basic tasks
 Management command and control
 Inadequate business tools available

Womack and Jones (1996a) incorporate five lean principles to eliminate waste for a process:

12
 Specify
Strive for
customer
perfection
value

Identify
Pull value
stream

Create
flow

Figure 2.3 The five lean principles

In Figure 2.3, ―Specify value‖ means to specify the value that is defined by the customer, but not by the engineers or
any other people within an organization. ―Identify the value stream‖ means figuring out all the processes to deliver a
product or service to customers. ―Flow‖ means to create continuous value-creating steps flow and reduce batch sizes
for a single-task process. ―Pull‖ means pull the value from customer. Every process along the value stream should be
aligned with customer needs and adjusted accordingly to satisfy customer needs when it is needed. ―Pursue Perfection‖
means lean principles endlessly strive for perfection, avoiding unnecessary waste and errors in the processes and
implementing continuous improvements.

The goal of Lean Thinking is to use least resources and time to deliver desired customer value through a continuous
flowing value stream (Hoppmann, 2009). A value stream is the flow of information and materials to produce customer
value (Tapping and Shuker, 2003). ―Value‖ means to create something for which customer are willing to pay. ―Stream‖
is a sequential flow of processes creating information and materials and delivering them to customers. Within value
stream are value-added and non-value-added activities which are used to transform information and materials to
customer needs. It also includes communication between the supplier chain, the network of processes and operations,
as well as channels of channels of information and materials flow.

Since value stream incorporates the main flows required to bring a product to a customer, it helps to visualize both
production flows – Lean Manufacturing (Rother and Shook, 1998), and design flows – Lean Engineering (Haque, 2003;
Freire and Alarcón, 2002). In manufacturing, Value Stream Mapping (VSM) could exhibit the common processing
sequence of a production flow from raw material to finished product (Rother and Shook, 1998). In designing or
engineering, VSM could also exhibit the common engineering sequence of a product family from concept to launch
(Beau Keyte and Locher, 2004). Within each product family, there are three areas of value stream that are tied together
to influence the product cycle: concept-to-launch, order to cash and raw material-to-finished product (Tapping and
Shuker, 2003). The first two areas incorporated lean management processes, while the last one dealt with the
manufacturing processes.

2.4 Lean tools and applications

A number of lean tools and methods are well-defined and applied (Womack and Jones, 1996). Some of the tools and
methods to support lean manufacturing include: pull system, cellular manufacturing, one-piece-flow, standard work,
visual control, Kaizen, quick changeover, 5S and kanban event (Van Goubergen and Van Landeghem, 2002; Rahn and
Consulting, 2001; Feld, 2000; Henderson, Larco, and Martin, 2000; Rother and Shook, 1998). However, compared to
the rich set of lean tools, implementation methods of lean are relatively few (Lian and Van Landeghem, 2002).
Applying tools without understanding the overall value-added process cannot yield sustainable results. Therefore, a
value stream analysis from an overall viewpoint is a good place to begin.

13
In recent years, VSM appears to be the preferred way to implement lean transformation (Beau Keyte and Locher, 2004;
B. Keyte and Branson, 2004; Irani, 1999; Rother and Shook, 1998). It helps map the current state, future state, and
ideal state of a certain production or management process in the value stream. VSM maps the material and information
flow and helps to identify value-added activities in the current state mapping. In the future or ideal state, it helps depict
the efforts toward eliminating non-value-added activities in the values stream (Rother and Shook, 1998). VSM
methodology was derived from the needs of facilitating manufacturing activities; therefore, few companies had
experience of implementing lean principles in the nonproduction areas (Beau Keyte and Locher, 2004). However, since
nonproduction costs took a large amount of the total cost in the product life-cycle (Tapping and Shuker, 2003),
manufacturers tried to apply lean principles in the knowledge-based areas such as design, new product introduction
(NPI), engineering, and product development (PD) (Baines et al., 2006).

To implement a VSM lean transformation in nonproduction area, Tapping and Shuker (2003) incorporated three phases
of lean application to frame a lean office system. These three phases include the customer level, the process level, and
the people’s level. In customer level, manufacturers need to identify customer demand and allocate corresponding work
accordingly. Some tools which can help define the customer demand include: takt time calculation, pitch calculation,
buffer and safety resources. In process level, manufacturers need to create a continuous flow that can ensure both
internal and external customers receive the right work units at the right time, in the right quantity. Some methods that
can apply to create a continuous flow include: in-process supermarkets, kanban system, first-in-first-out (FIFO), line
balancing, standardized work, and work area design. In people’s level, manufacturers have to perform leveling process
to evenly and effectively distribute workloads over the available time that can make the best use of people. Some
methods that were used at this level include: visible pitch board, load leveling (heijunka) box, and runner system. As an
indispensable component comprised of value stream of non-production area, engineering performs an important role
toward maximizing customer’s value (Baines et al., 2006).

In wood products industry, some research utilized Value Stream Mapping methodology. Czabke (2007) conducted a
survey in the secondary wood products industry and list value stream mapping as an important just-in-time production
practice in the lean manufacturing process. Espinoza (2009) utilized value stream mapping to portray the flow of
information and materials and to identify specific quality control activities in the wood products supply chain. Also,
based on the case study of three companies located in Honduras, Costa Rica and Guatemala, the researchers Quesada-
Pineda, Haviarova, and Slaven (2009) utilized value stream mapping to conduct a quantified research analyzing the
value-added times for wood products manufacturing companies in Central America. Key findings in the research
include:

 Raw material inventory accounts for most of the waste in the three case study companies
 Value-added time range from 8.8 to 12.3 percent of total process time, with kiln drying process, contributed the
most to the value-added time while other processes contributed little to the whole value-added time of
manufacturing process.

Furthermore, Norman (2008) proposed a pull-based manufacturing system for the secondary wood product
manufacturers to achieve product lead time reduction and on-time delivery to the final customer. Value stream mapping
was used to evaluate a case study company’s current state production performance. By implementing pull production
and supermarket methodology, the results showed that the proposed future state can achieve the reduction of lead time
from 15.1 hours to 7.5 hours.

Also, Leonard III (2005) utilized value stream mapping to evaluate the current state and design future state of a
southern yellow pine lumber production system. By more closely synchronizing and planning operations with sawmill
output, the lead time reduced from 35.3 days to a range of 10.8 to 14.9 days; future state capital inventory requirements
were less than 50% of the current state inventory requirement.

Although value stream mapping can help manufacturers identify value-added steps and eliminate non-value added
waste (muda) in a value stream (Rother and Shook, 1998), value stream mapping also has some drawbacks (Lian and
Van Landeghem, 2002):

14
 Since VSM originally used ―paper and pencil‖ to depict the current state of a process, it limits the level of detail
and the number of different situations that people could depict. For instance, the difficulty of identifying inventory
levels for various situations throughout the production process (McDonald, Van Aken, and Rentes, 2002).

 For companies undergoing a high product variety and low volume types, value stream mapping is hard to map all
the product value streams.

 Not every person is capable of observing how the VSM could be transformed into the real world; it undervalues
the actual performance of VSM.

Besides VSM, many lean tools and methods had been applied to various production or nonproduction areas (Table 2.7):

Table 2.7 Lean tools and methods

Tools and methods Definition/description
Takt time Determined by ―time available‖ (e.g. daily work time) divided by ―customer demand‖ (e.g.
daily customer demand in terms of how many number of products).
Pull system A system that controls the flow of production based on customer demand
Kanban A scheduling approach that receives the ―pull‖ from the demand and tells people what to
produce, when to product it, and how much to produce.
Buffer resource A level of stock maintained to prevent the risk of stock shortage resulting from volatile
customer demand.
Safety stock A level of stock maintained to prevent the risk of stock run-outs due to uncertainty of
supply and demand.
FIFO ―First in first out‖, a way to manage inventory relative to time and prioritization
Standardization The process of establishing the technical standard to have standard procedures or methods,
avoid unnecessary mistakes, ease training and improve efficiency.
Heijunka A method to balance workload to reduce waste and smooth the production processes for
producing intermediate goods at a constant rate.

Furthermore, Tapping and Shuker (2003) proposed a set of administrative lean methods and techniques to analyze and
transform management processes in three stages: demand, flow, and leveling. These tools, as shown in Table 2.8,
include Pace the takt time, Create pitch, Buffer resource, Safety resource, 5S of working area, Problem solving project,
Pull system, First In First Out (FIFO), Balance workload, Standard work, Work area design, Pitch Board, Heijunka Box,
and Runner. Based on the study of Tapping and Shuker, Thummala (2004) applied value stream management principles
to the software deployment process of a manufacturing company. In the case study, the value stream mapping method
helped the company reduce the overall lead time of conducting the deployment request by 16% in the software
development process. Tischler (2006) also utilized lean principles for the office area to streamline the inquiry processes
of a university’s admissions office.

Table 2.8 Administrative lean tools for different levels of use

Customer Demand Continuous Flow Leveling
Administrative Lean  Pace takt time  Pull System  Heijunka Box
Tools  Create pitch  FIFO  Runner
 Buffer resource  Balance workload  Pitch Board
 Safety resource  Standard work
 Work area design

In the furniture industry, lean strategies have been widely used in the production area (Table 2.3). Hunter, Bullard, and
Steele (2004) proposed a new lean manufacturing system, the non-typical double D assembly cell, for furniture industry.
Motsenbocker et al. (2005) conducted a case study on investigating the effectiveness of using flow-line technology to
increase productivity in furniture industry. The benefits of using flow-line technology resulted in reduced lead time and
inventory, more production space, labor savings, and increased productivity. Czabke (2007) conducted a case study to

15
investigate the lean implementation in two US wood products companies and two German wood products companies.
He found that:

 The implementation of Lean Thinking results in a more efficient and cost effective manufacturing performance.
 Lean thinking is suitable to apply to nonproduction area in secondary wood products industry.
 Other positives can be found by implementing lean practices and principles.
 Communication is a big challenge facing companies implementing Lean Thinking

By implementing lean principles, the result was an increased productivity of these four companies ranging from 10% to
275%.

Hunter (2008) incorporated Toyota Production System (TPS) for the furniture industry by proposing the cellular
manufacturing subsystem in the upholstery furniture company. The benefits of the proposed TPS’s double D cell
included increased productivity, decreased labor cost, improved quality, relaxed line balancing problem, improved
worker ergonomics and achieved continuous process improvement. Other research focused on analyzing the state of
lean application in furniture industry (Quesada-Pineda, Haviarova, and Slaven, 2009; Espinoza, 2009; Quesada and
Gazo, 2007; Cumbo, Kline, and Bumgardner, 2006; Schuler and Buehlmann, 2003). Table 2.9 shows a summary of
lean implementations in the furniture industry.

Table 2.9 Applications of lean in the furniture industry

Author Application of Lean research Results and findings
Schuler and Benchmarking and paradigm shifts Lean manufacturing is an essential element for strategic
Buehlmann renewal of business model for U.S. furniture industry
(2003)
Hunter et al. Propose the implementation of a new By the new manufacturing system, the company achieved
(2004) lean manufacturing system for an 11% increase of productivity and a direct labor
furniture industry reduction
Motsenbocker et Case studies of the application of a The plant wide realized benefits of lean implementation
al. (2005) new flow-line technology based on presented as over 40,000 square feet of floor space
lean manufacturing concepts for the cleared for new uses; lead time reduced by 80%; 83%,
furniture and wood component 78% reduction of finished goods and raw material goods
supplying industries inventory; $800,000 reduction of work-in-process
inventory; $3 million savings in annual labor; and 42%
increase in productivity
Cumbo, Kline, Benchmarking and case study Over half of the 145 investigated wood products
and companies had implemented lean manufacturing.
Baumgardner
(2006)
Czabke (2007) A case study of investigating lean By applying lean manufacturing, the productivity of these
implementation in the US and German four companies increased ranging from 10% to 275%
secondary wood products industry
Quesada-Pineda Benchmarking Lean manufacturing practices, like pull system
and Gazo scheduling, are positively related to the performance of
(2007) furniture manufacturing companies
Hunter (2008) Propose TPS’s double D cellular The productivity increased by 20% and the reduction of
manufacturing subsystem in furniture labor by 36.4%.
industry
Espinoza (2009) Value Stream Mapping for visual Identified specific quality control activities in the product
control supply chain
Quesada- Value Stream Mapping for quantified Identified key wastes in three case study companies;
Pineda, analytical research identified value-added activities in the production
Haviarova, and processes

16
Slaven (2009)

2.5 Summary of literature review

Value stream mapping is an important tool for implementing lean transformation since it facilitates mapping the flows
of information and materials, identifies various types of wastes, and finally it makes the value stream more efficient in
improving future state process (Womack and Jones, 1996a). Value stream mapping demonstrated its effectiveness in
streamlining the manufacturing processes toward maximizing customer value (Womack and Jones, 1996a; Rother and
Shook, 1998). However, nonproduction activities appear to have a significant impact in determining production cost
(Anderson, 1990; Prasad, 1996; Boothroyd, Dewhurst, and Knight, 2001; Ehrlenspiel et al., 2007; Tapping and Shuker,
2003), and manufacturers are trying to apply lean principles in the knowledge-based areas such as design, new product
introduction (NPI), engineering, and product development (PD) (Baines et al., 2006). Applications of VSM in
nonproduction area include the areas of sales process (Barber and Tietje, 2008), health care (Kim et al., 2006),
university’s admission inquiry process (Tischler, 2006) and information management (B. Keyte and Branson, 2004).

Lean principles and techniques were used in previous research to streamline the manufacturing process in secondary
wood products industry, especially to enhance the productivity of furniture manufacturing process (Hunter, Bullard,
and Steele, 2004; Motsenbocker et al., 2005; Hunter, 2008). In wood products industry, VSM as an implementation
tool, showed its effectiveness in streamlining the manufacturing process (Czabke, 2007; Espinoza, 2009; Quesada-
Pineda, Haviarova, and Slaven, 2009). However, other than manufacturing, lean principles could create benefits to
nonproduction processes in the secondary wood products industry (Czabke, 2007). As engineering is an important
process in determining the production cost of wood products, research on combining engineering with lean principles
has not been found in secondary wood products industry.

The literature review incorporates the fields of engineering and value stream mapping. The following (Table 2.10) is a
summary of the literature:

Table 2.10 Summary of literature reviewed

1. Value stream mapping is an effective lean implementation tool to identify and eliminate waste as well as observe
and improve information and material flow.
2. Engineering plays an important role in determining production cost. It is an important process in implementing
design for manufacturability.
3. Engineering change directly affects the product development cost and lead time. Engineering changes for
improvements and engineering changes for errors are two types of engineering change order.
4. The lean implementations applied to non-production area have a similar structure to production area such as
encompassing steps of pacing customer demand, achieving continuous flow, and leveling individual workload.
5. Lean principles have potential to be applied in knowledge-based activities. Lean engineering was developed in
aerospace, construction, and software industries.
6. Process efficiency is an important indicator to the efficiency of information flow in the current value stream.
Improved Process efficiency optimizes the engineering efficiency and can effectively reduce the engineering lead
time.
7. The Lean tools applied to administrative value stream are developed based on adopting and extending the lean
tools applied to the production area.
8. By applying lean principles to optimize the internal business processes, it showed evident improvement in
productivity in the wood products industry.
9. Value stream mapping has been applied to secondary wood products industry mostly in analyzing supply chain and
manufacturing process. Research on applying VSM in product engineering area was almost non-existent in the
furniture industry.

17
 CHAPTER 3 METHODOLOGY

3.1 Introduction

The research will be conducted based on a case study company. The purpose of the case study is to investigate the
current engineering processes addressed in the study objectives of Chapter 1. This investigation is projected to
encompass three phases (Figure 3.1). The first phase, the literature review (pre-study), includes two aspects – a
questionnaire design and an on-site study plan. In the questionnaire section, the appropriate case study company will be
identified. For the selected company, a questionnaire will be designed based on the summary study of literature
reviewed and prepared to investigate the potential company’s engineering process. Concurrently, a phone interview
will be conducted to verify whether the designed questions are applicable to the case study company to guarantee the
best reliability and quality of results.

The second phase, data collection (on-site study), includes two categories – a questionnaire and data for VSM. Through
issuing the questionnaire, multiple forms of information concerning engineering process and engineer performance will
be acquired. Personal interviews will also be conducted to collect corresponding information on the current engineering
process. Besides issuing the questionnaire, data for value stream mapping, such as customer demand, process lead time,
and completion of work unit will be collected. The methods for collecting the data include issuing data collection sheet
and analysis of plant documents content. Additionally, through direct observation, the information concerning process
boundary, process components and types of waste will be identified.

The last phase, data analysis (post-study), includes two categories – data analysis and results/conclusion. The data
analysis section will analyze the data collected from the on-site case study using both quantitative and qualitative
methods. The data will be used to generate questionnaire analysis, current state value stream mapping, and future state
value streaming mapping. The last part will present the results and conclusions from the research, state the limitation of
the research and look ahead at possible future research.

Figure 3.1 Methodology used to develop survey, collect, and analyze data

18
3.2 Questionnaire design

3.2.1 Company selection

Due to a limited budget and time frame for an overseas case study, this investigation will focus on only one potential
company. The selection of the case study company will be based on several aspects such as company size, product type,
customer, location and turnover (Robb and Xie, 2003; McNamara, 1972). Some measurements used to determine the
company size include the number of manufacturing plants, number of employees and turnover. The ideal company for
the case study is one that produces diversified product types, which will help generate sound and practical results for
this research.

Concerning the size of the company, it currently has 10 manufacturing plants employing over 10,000 workers. The
annual sales turnover was around $90 million in 2009. The product types of the company which include both solid
wood and upholstery products for different American and European customers. It has been making furniture products
for 20 years and is located in the northeast part of China. The company is very close to the port. Therefore it shows a
transportation advance in producing furniture products to a great deal of overseas furniture brands. The company has
been making case goods and upholstery products for many established US customers. Most of these customers have
been involved in the furniture business for two decades and their businesses account for a large amount of the
household furniture market share in the US. The product lines of this company are concentrated in American style
furniture but diversified on product architecture (the way to construct the furniture). Because of the wide customer base,
the company carries a wide range of product types and a large engineering group. The company runs four business
units. Three of the business units produce solid wood products and one produces upholstery products. The engineering
group consists of four individual engineering departments associated with different business units. The whole
engineering group has over forty product engineers and over twenty industrial engineers.

3.2.2 Design questionnaire sections and relevant questions

The questionnaire’s design will focus on investigating engineer’s responsibility, process metrics, engineering efficiency
and related impact factors. The questionnaire was organized into four sections – Lean metrics, Engineering lead time,
Job completion and accuracy, and Engineering change.

Lean metrics
Lean metrics could help people understand the impact of their efforts toward continuous improvement and waste
elimination (Tapping and Shuker, 2003), therefore, the questionnaire includes 11 metrics to measure the quality of the
current engineering performance and each metric will be evaluated by each respondent (product engineer). These 11
metrics include process time, value-added time, queue time, engineering error rate, lead time, number of people in the
group, overtime, changeover time, percent of completion, inventory, hardware and software reliability (Keyte and
Locher, 2004; Barzizza, Caridi, and Cigolini, 2001).

Engineering lead time

Many industries focused on development lead time as a measure of competitive performance in the product
development process (Keyte and Locher, 2004; Clark and Fujimoto, 1989). This section will focus on analyzing
different factors affecting engineering lead time. These influential factors include engineering process time,
development tool, and engineer competency (Keyte and Locher, 2004; Clark and Fujimoto, 1989).

Job completion and accuracy

Beau Keyte and Locher (2004) indicated that job completion and accuracy is an important indicator used to measure
the quality of engineering design. The question designed for analyzing this metric includes the average number of
production documents and production document completion rate.

Engineering Change (EC)

19
Engineering change is a significant driver of product development costs and lead time (Loch and Terwiesch, 1999).
Engineering changes (ECs) refer to making design changes to an existing product (Barzizza, Caridi, and Cigolini,
2001). It includes changes for improving production efficiency as well as the changes for assuring product quality and
performance (Balakrishnan and Chakravarty, 1996). The questions designed for this section include engineering error
rate, and the percentage of time on issuing Engineering Change Orders (ECOs).

3.2.3 Phone Interview

To ensure a comprehensive and appropriate questionnaire, phone interviews were conducted after completing the
design of the questionnaire’s first draft. One purpose of the phone interview was to verify the questions in the
questionnaire. The questionnaire was sent in advance through email to the engineering supervisor who helped review
each section of the questionnaire during the phone interview and gave feedback. Thus the viability of each section of
the questionnaire was assessed through the phone interview (Coon, Pena, and Illich, 1998) and the engineering
supervisor was interviewed in this process. The supervisor answered all the inquiries and provided additional
information to help design questions that fit the actual conditions of the engineering group.

The second purpose for the phone interview was to collect pre-study information from the engineering group such as
the experience of the engineers, knowledge of lean concepts and problem-solving methods. Thus additional questions
were developed that complement the four major sections in the questionnaire (Burke and Miller, 2001). Also from the
phone interview, the questionnaire incorporated specific engineering terms used by this company, such as engineering
documents referring to a file that includes all the engineering drawings, bill of materials, specifications, instructions
and other essential materials to facilitate the production process. Furniture engineering signifies the product design
concepts transformed into the final engineering files that could be used to fabricate specific products. Primary furniture
engineering process refers to major value-added engineering activities toward product structure design. Secondary
furniture engineering process refers to subordinate value-added activities used to assist and realize the product
engineering for production.

3.3 On-site study plan

To ensure the quality of the study, the on-site study plan was important due to the limited time frame and budget. The
on-site study plan included key details such as documenting daily activities and information to ensure the needed
results were obtained. The on-site case study was scheduled for 17 days. Each day aimed to finish certain tasks. Table
3.1 shows the Project Agenda during the case study.

20
Table 3.1 Project Agenda during Case Study
ID Task Name Method Duration Start Finish
1 Lean Engineering project start 25 days 7/25 8/13
2 BEFORE CASE STUDY 5 days 7/25 7/29
3 Prepare the Excel Investigation Forms 1 days 7/26 7/27
4 Verify survey 1 days 7/27 7/28
5 DURING CASE STUDY 17 days 8/2 8/18
6 Lean Manufacturing Presentation
8/2 p.m.
7 Send out the survey questionnaire
8 Current State Analysis 15 days 8/3 8/17
9 Identify the value stream 3 days 8/3 8/5
10 Determine the process boundary (customer/supplier) Context diagram 1 days 8/3
Determine customer requirements and supplier Interview(Interface
11
responsibilities analysis)
Work unit routing
Determine product family 1 days 8/4
12 analysis
Pareto diagram
13 Determine each main engineering processes Observation 1 days 8/5
14 Determine unit and metrics Interview/survey
Functional
15 Create Process Flow Chart
flowchart
16 Data collection
Data collection
17 Measuring process lead time 1 day 8/6
form
Data collection
18 Measuring single process (Cycle Time/Queue Time) 1 day 8/9
form
19 Identify VA/NVA activities Observation 1 day 8/10
20 Analyze customer demand Observation 1 day 8/11
21 Measure WIP within processes
22 Collect data for EC orders
Engineering error rate for a certain month of the
23 Observation 2 day 8/12 8/13
period
Engineering improvements for a certain month of the
24 Observation
period
25 Time spent on issuing ECO to the overall lead time Observation
26 ECOs for specific job shops Observation
27 ECOs data analysis (Process Capacity) 2 days 8/14 8/15
28 Current State Mapping
29 Create Process Attribute Sheet Interview 2 days 8/16 8/17
30 Draw current state mapping eVSM/AutoCAD
Initial ECO brainstorming based on current state data
31 8/18
analysis
32 Project Presentation (optional) 1 day 8/18
AFTER CASE STUDY
Verify Results
Analyze data
Proposal for Future State
Project Report and Survey Analysis

21
3.4 Questionnaire application

Concerning the limited time frame and on-site cost during the case study, the questionnaire was considered the primary
method to collect information and address the research objective. The questionnaire was given to the supervisors of
each engineering group and then the supervisors would forward the survey to the engineers of their respective group
(Robb and Xie, 2003; Frey and Oishi, 1995). The sample size was limited to the number of engineers in each
engineering group at the time of study. Therefore, the sample size of the solid wood group was 32 respondents, and the
sample size of the upholstery group was 15 respondents. Before each respondent worked on the survey, questions were
carefully explained as concerns arose from respondents. Then the supervisor in each engineering group helped collect
the completed questionnaire.

During the case study, a number of KPIs, such as engineering lead time, document error rate, and engineering
throughput were identified to understand the current engineering performance. In the meantime, certain key
information collected from on-site study (parallel to the application of questionnaire) included customer demand,
process boundary/components, process metrics, and different types of waste in the current engineering process. The
methods used for collecting the information included data collection sheet, direct observation, and looking over plant
documents (Bonoma, 1985).

3.4.1 Questionnaire application

The survey questionnaire was sent out to the supervisors in each engineering groups. Interviews with these supervisors
were also conducted to assist in assessing validity and methods variance (Robb and Xie, 2003). Before each respondent
completed the questionnaire, questions were carefully explained as concerns arose. These concerns were among the
following: requested illustration of certain questions or definitions, needed permission to answer certain questions, or
whether the answers they gave were in the correct form. Then the supervisor in each engineering group collected and
gave the completed questionnaires to the researcher.

3.5 VSM data collection and interview

The research followed the structure of defining process boundaries, identifying main processes, analyzing customer
needs, selecting and measuring process metric, calculating system metrics as well as and generating current and future
state Value Stream Mapping (VSM) (Keyte and Locher, 2004). A data request form was used to collect data of
processing time and inventory for the VSM (Tapping and Shuker, 2003).

During the case study, interviews were also conducted with multiple supervisors and product engineers. The primary
focus of the interviews was to obtain personal information concerning process sequence and performance. Different
Key Performance Indicators (KPIs) were measured and data was collected using a standard data collection form. For
instance, the expected KPIs results to be collected included lead time, work-in-progress inventory, cycle time and
queue time. The results of these KPIs were gathered from each engineer’s individual answer on the data collection form.
The secondary focus of the interview was to collect process information in order to analyze process boundary, product
family elements, customer demand, and engineering change orders (ECOs).

3.5.1 Determine customer demand

The customer can be either external or internal. An external customer indicates the real customer who buys products or
services, while an internal customer refers to the functions or departments inside the company (Tapping and Shuker,
2003). In this study, the customer was an internal customer and defined by engineers through interviews and
discussions. By accessing the customer’s requirements, the specific needs of the engineering process could be better
understood so a more demand driven or ―pull system‖ could be designed to level and better allocate the engineering
resources. The following Table 3.2 is a summary of information collected by analyzing the customer demand profile:

22
Table 3.2 Accessing the Customer Demand
Data samples Data Collection Method
(1) Average number of orders per month (in the last six months) Content analysis of plant document
(2) Number of orders for the current month Content analysis of plant document
(3) Available days of work time (during a month) Personal interview
(4) Average products per Day = (1) / (3)
(5) Daily available work time Content analysis of plant document
(6) Takt time = (5) / (4)
(7) Total process cycle time Current state VSM
(8) Engineers needed = (7) / (6)
* TBD: To be determined

The fundamental data for customer demand analysis, which is an electronic version of engineering archives for the
previous six months, was requested before the case study started. Then through personal interviews, the data of
monthly and daily engineering work time was collected. Also the number of orders in the current month was obtained
from the existing engineering documents.

Before collecting data, a unit for collecting data was determined. This unit gave a basis to further calculate the work-in-
progress inventory (number of units/customer daily demand). An appropriate unit provided much more convenient
future lean implementation, such as pacing takt time. Based on a previous study, ―drawing‖ or ―order‖ were the ideal
units for analyzing an engineering process (Keyte and Locher, 2004).

After having a suitable unit defined, the customer demand was analyzed. The following table (Table 3.3) is a summary
of data collection method for two different kinds of units.

Table 3.3 Data Collection for Certain Type of Units

Measurements for drawing unit Measurements for order unit Data collection method
Orders for a certain period Orders for a certain period Departmental documents
Drawings per order Calculation of existing data
Total Drawings per month Calculation of existing data
Available workdays within a measuring Available workdays within a Personal interview
period measuring period
Drawings per day Orders per day Calculation on existing data
Available engineering hours per day Available engineering hours per Personal interview
day
Takt time Takt time Calculation on existing data

After accessing the customer demand and identifying the takt time, a Worker Balance Chart helped compare the current
processing time of each engineering step in relation to takt time. WBC aided in determining whether the current
engineering staffing level is in pace with customer demand or not. In order to calculate customer demand and to
conveniently apply lean tools for streamlining the future state value stream mapping, the average number of monthly
customer demand was calculated based on the most recent three month data (Keyte and Locher, 2004).

3.5.2 Identify supplier and customer boundary requirements

During the case study, the supplier and customer of the engineering process were identified. The supplier was the last
upstream internal process. The engineers were interviewed to collect their requirement demands for the upstream
supplier. Different customers of the engineering process were interviewed as well and information was collected about
what their specific requirements for the engineering process were. A context diagram was utilized for this analysis.

23
Context Diagram (supplier/customer) was used for system engineering which reflected the interaction between a
system and its outside interfaces (Kossiakoff and Sweet, 2003).

3.5.3 Process Metrics

Each main engineering process and its sequence were defined through personal interviews with the supervisors and
manager, and then consistent metrics were used as the basis to identify both value-added and non-value-added time for
each engineering process. The metrics helped identify and quantify both value-added and non-value-added functions
and then determined the suitable lean tools for improvements. During the case study, the actual data of essential process
KPIs, such as cycle time, demand rate, queue time, percentage of job completion and accuracy, engineering error rate,
were collected through the data request form and survey questionnaire.

In order to obtain accurate original data of processing time for each essential engineering phase, the data request form
was used to collect processing results from different product engineers, then the average value was obtained to
determine the processing time for each engineering process in the value stream. From direct observation, the
information on the number of engineers was also obtained.

The inventory data in terms of unfinished design tasks was obtained from the case study company’s Engineering
Completion Report. This report was posted on the notification board inside the engineering department for the
convenience of each team member to keep track of the current month’s projects.

3.5.4 Waste and error Investigation

After the process value analysis, the waste was explicitly identified and categorized it into the classification of nine
types of waste as stated in the literature review (Keyte and Locher, 2004; Prasad, 1996). Also, a waste analysis chart
helped summarize the waste activities in the process (Table 3.4). Waste type lists all nine types of waste in the non-
production area. Process refers to all the essential single processes that comprise an engineering environment. ―Waste
element‖ is all the waste activities identified in the value stream.

Table 3.4 Waste Analysis and Data Collection method

Waste Type Process Waste Element
Overproduction Direct observation Direct observation
Correction Direct observation Direct observation
Material movement Direct observation Direct observation
Extra processing Direct observation Direct observation
Inventory Direct observation Direct observation
Waiting Direct observation Direct observation
Excessive motion Direct observation Direct observation
Underutilized people Direct observation Direct observation
Unnecessary transfer of information flow Direct observation Direct observation

The data of engineering errors was obtained from the Engineering Change Summary Report. This report included
information on the statistics of engineering errors from the previous months.

3.6 Data analysis

Data analysis falls into two parts. The first part uses different quantitative and qualitative methods to analyze the data in
the questionnaire. The second part uses VSM method to analyze the current engineering efficiency.

24
3.6.1 Questionnaire analysis

Descriptive statistics were used to analyze and explain the data in the study (Sprinthall, 2003). Bar and pie charts were
used to show the response rate, distribution, and variance of data. In addition, the radar chart helped show the response
frequency and the box plot chart was used to indicate the survey data’s average, median, and quartiles distribution (Ott
and Longnecker, 2008). Inferential analysis – the Unequal Variance Two-sample t-Test (Ruxton, 2006), was used to
compare the actual customer demand (in terms of orders) of solid wood and upholstery engineering groups.

3.6.2 Current State Value Stream Mapping

Process boundary analysis: after acquiring the information on process boundaries (customer and supplier), the context
diagram was used to analyze the requirements from the customer end and also the engineering requirements for the
supplier end.

Main process analysis: in order to analyze the overall engineering process first, the functional flowchart was used to
depict the whole process flow (including non-upholstery engineering and upholstery engineering).

Then, VSM was utilized as a visualization tool to describe the current state of an engineering process and to help
incorporate potential process improvement for the future state implementations. The VSM focussed on one product
family instead of tracking the whole product collection. Focusing on a single product family by analyzing a set of
similar product architecture provided an easy way to track down the general engineering procedures.

For creating the current state VSM, data collected from on-site visit was converted, calculated, adjusted, and
summarized. The data of monthly customer demand was converted into the basis of daily demand. The daily demand
was used for calculating the inventory (in form of days) within the processes. To analyze the metrics of each essential
individual process, a process categorization was conducted first in order to combine similar or unnecessary small
processes into more generalized main processes. This was necessary to extract and present only important process
information to the current state VSM. Then metrics such as process time, number of operators, error rate and tool
reliability were calculated for each process.

Next, the data collected was utilized to generate the current state value stream mapping (VSM). The current state VSM
focused on identifying the waste within the engineering process and then potential improvement methods will be
proposed for the future state VSM. Figure 3.2 shows an implementation diagram that illustrates the processes for
generating the overall project.

25
 Figure 3.2 Value stream mapping method

3.6.3 Future State Value Stream Mapping

Based on current state value stream mapping, different types of waste were identified in the engineering process. The
identified waste items were categorized into several types of waste defined in section 3.5.4. Furthermore, by analyzing
and comparing processing time and inventory of each process, the bottleneck processes were identified. Root causes
analysis of these types of waste was further conducted by using Ishikawa Diagram (Fishbone Diagram) methodology.
Then countermeasures were proposed and incorporated into the future state value stream mapping. The future state
value stream mapping followed the direction of five lean principles (Womack and Jones 1996a) and processes in
different stages such as defining customer demand, creating continuous flow, and leveling workload (Tapping and
Shuker 2003). Many lean tools and methods were used to streamline and transform the engineering process. According
to the literature review, a set of lean tools had been used to transform the administration area which included: pace the
Takt Time, create pitch, buffer resource, safety resource, 5S of work area, problem-solving project, pull system, FIFO,
balance workload, standard work, work area design, visible pitch board, Heijunka box and runner (Beau Keyte and
Locher 2004; Tapping and Shuker 2003).

3.7 Summary of Methodology

The overall methodology falls into three stages. The first stage was mainly to design the survey questionnaire and
verify the usability of each question. The second stage was to conduct the on-site case study. Research data was
collected for two purposes. One purpose was to collect data from the survey questionnaire. The data was used to
achieve the first objective of the research. The other purpose was to collect data for value stream mapping. The data of
value stream mapping was collected by issuing standard data request form, conducting personal interviews and using
direct observation. The data was used to realize the research’s second and third objectives. The third stage was to
analyze the existing data for research results and conclusions.

26
 CHAPTER 4 MEASURING ENGINEERING PROCESS EFFICIENCY

4.1 Abstract

Efficient engineering processes are critically important for furniture manufacturers. However, most furniture
manufacturers have been controlling their product drawings and engineering documents merely by the release date
without a systematic method to measure internal processes and how it affects product cost, engineering quality and
customer satisfaction. This research was conducted through a case study in a furniture plant located in China,
producing American style furniture products. The objective was to investigate the company’s current engineering
process, identify non-value-added activities and analyze the engineering performance based on certain Key
Performance Indicators (KPIs) such as lead time, document error rate, and engineering throughput. A survey
questionnaire was sent out to the engineering group to determine the current engineering efficiency. Results show that
―product complexity‖ and ―engineer competency‖ are the two most influential factors that impact the engineering
process lead time. Most engineers spend 10 to 20% of their daily work time issuing engineering change orders (ECOs).
Upholstery and non-upholstery (solid wood) engineering groups showed a difference in engineering throughput,
customer diversity, and production document error rate. From this research, it is concluded that ECOs are significant
drivers of engineering lead time. Also, the current processes include a large amount of non-value adding activities,
interfering with engineers’ ability to prepare production documents for downstream jobs and affecting the overall
manufacturing process.

4.2 Introduction

The goal of Lean Thinking is to use the least amount of resources and time to deliver desired customer value through a
continuous flowing value stream (Womack and Jones, 1996). In the furniture industry, lean strategies have been widely
used in the production area (Cumbo, Kline, and Bumgardner, 2006). Schuler and Buehlmann (2003) indicated that lean
manufacturing is an essential element for strategic renewal of the business model in the U.S. furniture industry.
Moreover, through a survey of 145 wood products companies in the US, Cumbo, Kline, and Bumgardner (2006) found
that a majority (55%) of these companies had been implementing lean manufacturing at the time of the study. Within
the subsectors, 56% of cabinet makers, 71% of upholstered and 53% non-upholstered furniture manufacturers indicated
they were doing lean implementations. Quesada-Pineda and Gazo (2007) illustrated that lean manufacturing practices,
like pull system scheduling, are positively related to the performance of furniture manufacturing companies.
Motsenbocker et al. (2005) conducted a case study to investigate the effectiveness of using flow-line technology to
increase productivity in the furniture industry. The benefits of this technology were reflected on reduced lead time and
inventory, more production space, labor savings, and increased productivity. In another case study, Czabke (2007)
investigated lean implementation in two US wood products companies and two German wood products companies. He
found that:

 The implementation of Lean results in a more efficient and cost effective manufacturing performance.
 Lean is suitable for nonproduction areas in the secondary wood products industry.
 Communication is a big challenge to implement Lean

Hunter (2008) proposed to incorporate the Toyota Production System (TPS) in the furniture industry by the
implementation of a cellular manufacturing subsystem in upholstery furniture production. According to the author, the
benefits of the proposed TPS’s double D-shaped manufacturing cell include increased productivity, decreased labor
cost, improved quality, relaxed line balancing problem, improved worker ergonomics and continuous process
improvement.

The application of lean thinking in nonproduction areas, especially the engineering process, has been given extra
attention in other industries during the last decade (Donald Reinertsen, 2005; Middleton, Flaxel, and Cookson, 2005;
Browning, 2003; Haque, 2003; Freire and Alarcón, 2002). However, research on lean thinking has not been conducted
in the furniture industry. In the wood furniture industry, engineering also plays an important role in the product life
cycle. Engineering not only helps materialize design concepts, but also facilitates mass production and mass

27
customization (Da Silveira, Borenstein, and Fogliatto, 2001). Therefore, there is a need in the furniture industry for an
efficient engineering process. This research aims to analyze the current engineering performance and key performance
indicators through a survey questionnaire given to the case study company’s engineering group.

4.3 Theoretical Background

The lean thinking concepts were introduced in 1990 by (Womack, Jones, and Roos, 1990) in their study that compared
the manufacturing performance of the automobile industry between Western and Japanese car makers. The goal of lean
thinking is to use the least amount of resources and time to deliver customer value through a continuously flowing
value stream (Womack and Jones, 1996). It encompasses five basic principles to eliminate ―waste‖ (waste in this
context is understood as any activity that does not add value from the customer’s point of view):

 Specify value
 Identify the value stream
 Implement flow
 Implement pull
 Pursue perfection

The first principle means to ―specify the value‖ from the customer perspective, not from the engineers’ point of view
(or any other people within an organization). ―Identify the value stream‖ signifies figuring out all the processes to
deliver a product or service to customers. ―Flow‖ indicates generating continuous value-creating steps, making them
flow, and reducing batch sizes for a single-task process. ―Pull‖ represents developing customer value from a pull
system instead of push. Every process along the value stream should be aligned with the customer’s needs and satisfy
these needs in a timely manner. ―Pursue Perfection‖ signifies to endlessly strive for perfection, avoiding waste and
errors, and keep implementing continuous improvements (Womack and Jones, 1996). The same authors indicated that
lean principles also fit in areas outside manufacturing operations. Baines et al. (2006) pointed out that lean principles
have great potential benefits when applied to knowledge-based activities such as new product development (NPD) and
engineering. Karlsson and Ahlstrom (1996) classified engineering as one of the interrelated techniques in lean product
development. Morgan and Liker (2006) described the engineering process as that which ―raw materials consist of
information – customer needs, past product characteristics, competitive product data, engineering principles and other
inputs that are transformed through the product development process into the complete engineering of a product that
will be built by manufacturing.‖

Engineering plays an important role in determining the production costs. Prasad (1996) depicted the cost associated
with fixing a mistake in the product life-cycle and indicated that fixing problem at the early stages in the product life-
cycle costs less than detecting and fixing the problem during later stages. He also stated that this allows more
opportunities for making improvements. Moreover, Anderson (1990) in his book ―Design for Manufacturability‖
mentioned that ―by the time a product has been designed, only about 8% of the total product budget has been spent. But
by that point, the design has determined 80% of the cost of the product.‖ Similarly, Boothroyd, Dewhurst, and Knight
(2001) stated that over 70% of production costs are determined in the product design stage. Ehrlenspiel et al. (2007)
also discussed how significant the decisions made in the product development stage are for the product lifecycle.
However, in traditional sequential engineering processes, manufacturing engineers lack an effective communication
channel with the product engineers, and thus the best opportunity to use engineering guidelines to control cost and
achieve manufacturability is missed at an early stage of product life cycle (Eppinger et al., 1994).

Considering the previous findings, this research aims to conduct a current state analysis of the engineering process for a
typical manufacturer of American-style furniture through a questionnaire study, and to try and find the influential
factors controlling the engineering lead time, error rate, job completion and accuracy.

4.4 Methods

Case study methods were used to evaluate the current state of the engineering process, including questionnaires,
personal interviews, analysis of plant documents, and direct observations all of which helped to increase the reliability

28
of the data collection process (Bonoma, 1985). Considering the travel cost as well as the scattered locations of each
interviewing group during the case study, a questionnaire was utilized as the major case study method (Moser and
Kalton, 1972; Hochstim and Athanasopoulos, 1970). Another consideration for using the questionnaire method was the
time availability the respondents in the engineering groups, thus by using a questionnaire, the respondents were free to
allocate their time to complete the questions without interrupting their work (Hoyle, Harris, and Judd, 2002). The
questionnaire was structured in five parts:

 Engineering experience and awareness of lean concepts and problem-solving methods

 Engineering process metrics
 Factors affecting engineering lead time
 Factors affecting job completion and accuracy
 Engineering changes

In order to obtain the most reliable results for the research, the quantitative data was combined from the questionnaire
with the qualitative data from interviews and observations to generate results (Bourgeois III and Eisenhardt, 1988). For
detailed methods on data collection and data analysis, refer to chapter 3 – Methodology.

4.5 Results and Discussion

The results section is organized in five major parts. The first part displays the results of engineer experience and
knowledge of lean concepts and problem-solving methods. The second part is the process metric section that indicates
the important metrics to reflect the engineering performance. The third part reveals the factors that could influence the
engineering lead time. The fourth part illustrates the job completion and accuracy of the current engineering process. In
the last part, the most frequently occurring errors in the engineering documents are presented, as well as the analysis of
the impact of issuing Engineering Change Orders on engineering lead time.

4.5.1 Engineering experience and awareness of lean concepts and problem-solving methods

In this case study company, the non-upholstery (solid wood) and upholstery engineers exhibited different experiences
of product engineering. Figure 4.1 shows that 38% of the upholstery engineers had more than 6 years of experience
while the majority of solid wood engineers, in Figure 4.2, had 3-5 years of work experience. However, the junior
engineers (less than 2 years) in the upholstery engineering group account for 39% of the overall engineering crew,
whereas in the solid wood group they account for 30% of the crew among the overall solid wood unit. Furthermore,
there are 31% of entry-level engineers (less than 1 year) in the upholstery engineering group compared to just 6% of
entry-level engineers in the solid wood engineering group. Thus, from the survey results, the overall number of
engineers above the junior level in the solid wood engineering group is larger than the same level of engineers in the
upholstery engineering group.

29
 Upholstery
Less than 1
year
More than 6 31%
years
38%

1 - 2 years
8%

3 - 5 years
23%

Figure 4.1 Engineering Experience of upholstery group

Solid Wood
More than 6 Less than 1
years year
30% 6%

1 - 2 years
24%
3 - 5 years
40%

Figure 4.2 Engineering Experience of solid wood group

The reason that the upholstery engineering group lacked experienced engineers was because, at the time of the study,
this group was preparing and training junior level engineers for a new upholstery plant. So the number of entry level
engineers in this group looks relatively high. Another reason was that some experienced upholstery engineers left the
company for various reasons. On the other hand, the engineers in the solid wood plant were relatively stable, and few
entry-level engineers were recruited in recent years. The current engineering capacity can also be reflected on the lead
time of production documents. The solid wood products group had a lead time 17% faster than that of upholstery
products.

Also of interest in this study was learning how much experience each engineer has on lean concepts and problem-
solving methods. So a question was asked, based on a 1 to 5 scale, of how familiar the engineer was with the lean
concepts and problem-solving methods defined in the questionnaire.

30
 Figure 4.3 Knowledge of lean concepts and problem-solving methods

The company has been implementing lean principles in the production area since 2003, and like most other companies,
they started with the ―5S‖ initiative (Feld, 2000). This is the reason why 5S was the most acknowledged lean method
known by all the engineering groups. On the other hand, some lean concepts like ―kanban system,‖ ―kaizen,‖ and
―standard work‖ (Van Goubergen and Van Landeghem, 2002; Rahn and Consulting, 2001; Feld, 2000; Henderson,
Larco, and Martin, 2000; Rother and Shook, 1998), had been implemented by the company but were not as effective as
―5S.‖ Thus the rating on some of these methods, in Figure 4.3, was not as high as 5S. The on-site lean manufacturing
workshop not only let the associates have an in-depth understanding of the lean principles that they had implemented,
but also familiarized them with other useful lean methods and problem-solving methods.

4.5.2 Engineering process metrics

From the personal interview, the engineering manager helped us to define that the furniture engineering process
referred to all kinds of product engineering activities to generate engineering documents for the downstream
manufacturing process. Lean metrics could help people understand the impact of their efforts toward continuous
improvement and waste elimination in this process (Tapping and Shuker, 2003). Therefore, the questionnaire included
11 metrics that reflect the quality of the current engineering performance and each metric was evaluated by all
engineers. These metrics are described and defined in Table 4.1:

31
Table 4.1 Metrics
Metrics Description
Process time The accurate time spent on making engineering documents
Value-added time The total sum of each major process time
Non value-added time The time not spent on making engineering documents
Engineering error rate The total number of errors that has been made during a period of time divided by the
total number of engineering documents made within the same period
Lead time The sum of process time and non-value-added time
Number of people The total number of engineers in the engineering group
Overtime The extra time spent on doing work after the regular work time
Changeover time The time required to prepare an engineering task to change from making good
results of the last engineering task to making the first good result of the new
engineering task
Percent of completion The percentage of production documents that delivered on time
Inventory Unfinished engineering orders from customers
System reliability The percentage of time that a specific hardware or software does work

Figure 4.4 shows that ―Processing Time,‖ ―Engineering Error Rate,‖ ―Engineering Lead Time,‖ and ―Completion and
Accuracy Rate‖ were the top-rated metrics; this reflects the current engineering performance in both solid wood and
upholstery engineering groups.

Processing time
Reliability of 5.00 4.75
hardware or value added time
software 4.00 3.83
3.66 3.00
Inventory 2.00 Queue time
2.96 3.03
1.00
0.00
Completion and Engineering Error
Accuracy Rate 4.11 4.27 Rate

2.88 4.11
Engineering Lead
Changeover Time
Time
4.02 3.92
Number of
Overtime
Engineer(s)

Response rate on a scale of 1 to 5, 1 is ―unimportant‖, 5 is ―very important‖

Figure 4.4 Identified Engineering Performance Metrics

4.5.3 Factors affecting engineering lead time

The engineering lead time refers to the total amount of time each engineer spent on making preproduction documents
and mass production documents. The production lead time means the total lead time of each product life cycle toward
delivering customer desired products, which encompasses the processes of selling and marketing, design, engineering,
manufacturing, packaging and all other necessary steps. Thus the engineering lead time is a portion of the production
lead time. So the engineering lead time positively impacts the on-time delivery of products to the customer. In this
context, it is necessary to know the percentage of time the engineering process takes toward the overall production lead
time. Generally, the shorter the engineering lead time the more it will be reserved for the other necessary manufacturing
processes. Figure 4.5 shows that over half of the engineers perceive the current engineering lead time accounted for 21%
to 40% of the overall production lead time. Some products may even take up to 61% to 80% of production lead time on
engineering. These products are usually custom furniture with a high price, even in a small batch of orders.

32
 Upholstery engineering Solid wood engineering

Response rate
Response rate

Engineering lead time over production lead Engineering lead time over production lead
time time
Figure 4.5 Engineering lead time versus production lead time in two engineering groups

To further explore which factors are the major contributors of longer lead times, ten factors were included in the
questionnaire for evaluation purposes. The results showed, from both solid wood and upholstery engineers, that
―Engineers experience/competency‖ and ―Product architecture complexity‖ were the top two factors that could
influence the engineering lead time. The results were concluded from the responses of thirty-three solid wood engineers
and fifteen upholstery engineers. Also, ―Tool‖ was considered the least influential factor that could impact the
engineering lead time. However, the company had been using two engineering design tool kits at the same time –
SolidWorks and AutoCAD. These tools exhibited different impacts on engineering jobs (other than lead time) in terms
of the capability to enhance collaboration, facilitate computer-aided manufacturing, maintenance engineering
documents, and automation generation of bills of material. Figure 4.6 explains that these two engineering solutions are
supposed to have different impacts on the engineering lead time. SolidWorks had been mainly applied in the upholstery
engineering process in this company. The results, in Figure 4.6, imply that SolidWorks might provide more benefits
for the upholstery engineering process. From direct observation it was seen that the upholstery products usually needed
to create the 3D model for product frames, and SolidWorks explicitly presented its advantage on creating complex
frame models, generating bill of materials, reducing design errors, and creating reader-friendly drawings.

Performance Difference Between SolidWorks and AutoCAD on Engineering

Development
Upholstery
Enhance collaboration 3.21
2.53 Solid wood

Facilitate CAM 3.57

3.25

Doc maintenance 3.29

2.19

Auto BOM 3.07

2.28

Dwg readability 3.64

3.41

Reduce error 4.07

3.72

Shorten modelling time 3.14

2.22

Ease late changes 3.50

2.19

1.00 2.00 3.00 4.00 5.00

Response rate on a scale of 1 to 5, 1 is ―strongly disagree‖, 5 is ―strongly agree‖

Figure 4.6 Performance difference using SolidWorks as the primary engineering design tool

33
To help illustrate how product complexity has an impact on engineering lead time, a question was designed to select the
corresponding lead time for developing each product within a standard product set. In this question, two standard sets
of products for solid wood product lines and upholstery product lines were separately defined. Engineers indicated the
time spent on completing each engineering task within a certain standard product set. The products within the standard
solid wood products set included mirror, nightstand, drawer chest, armoire base, armoire hutch, dresser, and bed. The
products within the standard upholstery product set included ottoman, chair, sofa chair, loveseat, tufted chair, sleeper
sofa, and sofa.

Following the standard product sets in the non-upholstery group, Figure 4.7 shows that the bed, armoire hutch, and
dresser are the top three products that need longer engineering time, for which most engineers need ―5 to 6 days‖ to
finish these products. From the upholstery group results, it could be observed that more upholstery products require ―5
to 6 days‖ of engineering lead time compared to solid wood products. These upholstery products include sofa chair,
sleeper sofa, tufted chair, love seat, and sofa. In fact, the reason more upholstery products take a longer lead time is
because the upholstery products usually include more engineering steps compared to the solid wood products. For
example, upholstery products usually need a certain amount of time to wait for the fabric suppliers to deliver the
samples for making the mock-ups; every piece of fabric needs to be measured on a special device to digitalize the
contour and dimension of the fabric; and every product needs a fabric specification in addition to the manufacturing
specification to facilitate the mass production process. All these tasks need extra engineering lead time of upholstery
products.
Figure 4.8 presents a summary of the average lead time to complete each type of product within a standard set of
product line. The variation of lead time to finish each type of product illustrates product architecture complexity has a
positive relation to the engineering lead time. For example, in a solid wood product set, beds (which usually have the
most difficult product structure) take the longest engineering lead time which is about 5.8 days, whereas the nightstand
(which usually has the easiest product structure) takes about 1.9 days of engineering lead time.

Solid Wood Upholstery

3.3%
Sofa
Bed 18.8% 37.6% 30.6% 9.7% 30.8% 46.2% 7.7% 15.4%
chair
3.3%
Armoire Sleeper
50.3% 27.6% 12.1% 6.7% 76.9% 23.1%
base sofa
Armoire Tufted
35.2% 37.0% 18.2% 9.7% 15.4% 61.5% 7.7% 15.4%
hutch chair
3.0% 3.3%
Mirror 78.2% 15.5% Ottoman 46.2% 46.2% 7.7%

Dresser 18.8% 56.4% 15.2% 9.7% Chair 46.2% 38.5% 15.4%

3.3%
Drawer
53.3% 30.6% 6.1% 6.7% Loveseat 15.4% 69.2% 15.4%
chest
6.4%
Night
74.8% 12.1% 6.7% Sofa 7.7% 69.2% 7.7% 15.4%
stand

0.0% 20.0% 40.0% 60.0% 80.0% 100.0% 0.0% 20.0% 40.0% 60.0% 80.0% 100.0%
Response rate Response rate

1 to 2 days 3 to 4 days 5 to 6 days 7 to 8 days 9 to 10 days 1 to 2 days 3 to 4 days 5 to 6 days 7 to 8 days 9 to 10 days

Figure 4.7 Average lead time distribution of each product

34
 Solid wood engineerng group Upholstery engineering group
Time of completion (in days)

Time of completion (in days)

8.0 8.0

6.0 6.0

4.0 4.0

2.0 2.0
1.9 3.6 4.5 4.7 5.4 5.5 5.8 2.9 5.0 5.4 5.6 5.8 6.0 6.0
0.0 0.0
Mirror Night stand Drawer Armoire Armoire Dresser Bed Ottoman chair sofa chair loveseat tufted chair sleeper sofa
chest base hutch sofa

Figure 4.8 Average engineering lead time for each product

4.5.4 Factors affecting job completion and accuracy

4.5.4.1 Customer Demand

To find whether the fluctuation of customer demands impacts engineering performance, an investigation was conducted
to find how many customers each engineer had served during the last six months. Although the overall T-test, in
Figure 4.9, shows there are no significant differences between solid wood engineering and upholstery engineering in
the average number of customers that were served, it is still easy to notice that upholstery engineers on average had
dealt with ―1 to 2‖ customers in the last six months, while most solid wood engineers had served ―3 to 4‖ customers
within the same time period.

The number of customers in the last six months

Solid wood
Upholstery 3.82
Upholstery

Solid wood 3.73

0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00

Number of customers
Figure 4.9 Average customer number

4.5.4.2 Engineering Throughput

To understand the current engineering throughput, each engineer was asked the number of engineering documents they
could generate per month. The engineering documents include both preproduction documents and mass production
documents. From their answer, Figure 4.10 shows that most engineers were likely to complete ―3 to 4‖ engineering
documents per month for the job shops. It could also be observed that, in the upholstery engineering group, there is no
difference in the quantity of preproduction and mass production documents released per month. Figure 4.11 shows that
there is a difference in the number of production documents generated in the solid wood engineering group and
upholstery engineering group. This somehow reflects the previous results which showed that the solid wood engineers
have more experience than the upholstery engineers. So the average number of jobs completed by solid wood engineers
was higher than the jobs completed by upholstery engineers.

35
Generation of Preproduction Documents

Solid Wood Upholstery

More than 10: 13% More than 10: 7%
1 to 2: 6% 9 to 10: 0%
9 to 10: 0% 1 to 2: 29%
7 to 8: 0%
5 to 6: 14%
7 to 8: 12% 3 to 4: 41%

3 to 4: 50%
5 to 6: 28%

Generation of Mass Production Documents

Solid Wood Upholstery

More than 10: 9% More than 10: 7%
1 to 2: 3% 9 to 10: 0%
9 to 10: 0%
7 to 8: 0%
1 to 2: 29%
7 to 8: 19% 5 to 6: 14%

3 to 4: 53%

5 to 6: 16%
3 to 4: 50%
Figure 4.10 Respondent distribution on engineering throughput
Production documents
Upholstery
Solid wood
3.5
Mass production
4.6

3.5
Preproduction
4.5

0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0

Number of documents

Figure 4.11 The average number of preproduction and mass production documents
generated per month in each engineering group.

4.6 Engineering Change

4.6.1 Error rates

Error rate is an important factor that influences the overall performance of the engineering process. Consequently, the
amount of errors on average each engineer made in their engineering documents was measured. Figure 4.12 and
Figure 4.13 show that the majority of engineers in both groups had ―1 to 2 errors‖ for each type of engineering error.
From this observation, it was found that each type of error would inevitably happen but differed on how many it had
occurred. There were just a few countermeasures used to prevent errors from happening. Through personal interviews
with engineering supervisors, it was discovered that checking errors manually is probably the only way to prevent them.
Although SolidWorks software could help to detect some drawing errors, it still cannot detect errors in the bill of
materials (BOMs) because most of BOMs jobs still rely on manual entry instead of automated generation of BOMs.

36
 Solid Wood
3.3%
Drawing errors 66.7% 20.0%
Missing essential drawings 40.0% 53.3% 6.7%
Wrong architecture applied 56.7% 36.7% 6.7%
Wrong material applied 60.0% 33.3% 6.7%
Wrong hardware receiving dept. 30.0% 60.0% 10.0%
Hardware missing 23.3% 70.0% 6.7%
Wrong amounts of hardware 6.7% 76.7% 16.7%
Wrong hardware applied 20.0% 66.7% 10.0%
Dimension missing 30.0% 63.3% 6.7%
Parts counting error 10.0% 83.3% 6.7%
Part dimension error 13.3% 73.3% 13.3%

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% 100.0%

Percentage of response

none 1 to 2 errors 3 to 4 errors

Figure 4.12 Respondent distribution of engineering error rate in solid wood engineering group
Upholstery

Drawing errors 16.7% 58.3% 8.3%

Missing essential drawings 58.3% 25.0% 16.7%
Wrong architecture applied 58.3% 41.7%
Wrong material applied 75.0% 16.7%
Wrong hardware receiving dept. 50.0% 41.7%
Hardware missing 41.7% 58.3%
Wrong amounts of hardware 33.3% 50.0% 16.7%
Wrong hardware applied 50.0% 41.7% 8.3%
Dimension missing 25.0% 66.7% 8.3%
Parts counting error 33.3% 58.3% 8.3%
Part dimension error 16.7% 66.7% 16.7%

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% 100.0%

Percentage of response

none 1 to 2 errors 3 to 4 errors

Figure 4.13 Respondent distribution of engineering error rate in upholstery engineering group

Comparing individual errors, Figure 4.12 and Figure 4.13 also show that ―drawing errors‖ and ―part dimension errors‖
are the most frequently occurring errors in both engineering groups. Furthermore, it could also observe that for almost
each type of error except ―dimension missing‖, the average number of errors for the solid wood group is higher than the
upholstery group. A reason for this might be because the solid wood group made more engineering documents than the
upholstery group, so it has a relatively higher possibility of generating more errors.

37
4.6.2 Engineering Change

Because engineering change is a significant driver of product development cost and lead time (Loch and Terwiesch,
1999), a question was designed to ask what percentage of time each engineer spends daily on issuing Engineering
Change Orders (ECOs). Thirty-three solid wood engineers and thirteen upholstery engineers provided valid responses.
Figure 4.14 and Figure 4.15 show that most of the engineers spent less than 20% of their daily engineering time on
issuing the ECOs. Engineers were also asked to give a specific time period. Twenty-three percent of upholstery
engineers gave ―5%-15%‖ of their daily work time and forty-six percent of engineers provided the answer of ―10%-
20%‖ of their daily work time. On the other hand, in the solid wood section, eighteen percent of engineers answered
that issuing ECOs seize ―5%-15%‖ of their daily work time, forty-five percent of engineers spent ―10%-20%‖ of their
daily time on issuing the ECOs and three percent of engineers answered of ―1%-10%‖ of his daily engineering time.
The current state implies that most engineers spent 10%-20% of their daily working time on the rework. That
accounted for almost 50 minutes to nearly 2 hours in a day (8-hour work days) doing non-value-added work. In the
current engineering process, usually right after releasing the mass production documents, there is a severe increase of
engineering changes needing ECOs. Sometimes the engineers were required to spend the whole day working on the
ECO without doing any other engineering tasks.

Response rate of ECO Percentage of time to issue ECO, daily

80% 67% 69% Solid Wood Solid wood
60% Upholstery 19.69
Upholstery Upholstery
40% 27% 23%
20% 3% 8% 3% Solid wood 20.07
0%
0%
Less than 20% 21% - 40% 41% - 60% 61% - 80% 0.00 10.00 20.00 30.00 40.00 (%)
Ranges of Engineering time percentage Percentage of daily working time

Figure 4.14 Response rate on ECO percentage Figure 4.15 Time spent on ECO

4.7 Conclusions

The current engineering process in this particular case study exhibits unnecessary engineering tasks regarded as waste.
These wasteful processes might interfere with the engineers’ ability to effectively and efficiently prepare production
documents for downstream jobs. ―Generate production documents‖ is the top responsibility for furniture product
engineers. But, currently, most engineers were distracted by many non-value-added tasks. For instance, 10%-20% of
engineering time was spent on releasing Engineering Change Orders (ECOs). In order to leave more engineering time
on addressing value-added activities, for example, the company might consider assigning some responsibilities to
specific people in production to help engineers issue a portion of ECOs, such as adding screws for strengthening certain
product structures. This type of modification does not need big changes of product design or architecture. In this sense,
it not only helps balance the workload and provides more flexibility for the product engineers, but also solves the
dilemma where product engineers do not have time to issue ECOs for an urgent production change and industrial
engineers in production cannot work on this change until they receive the relevant ECOs from engineering.

Processing time is one of the most important lean metrics used to measure engineering performance and it varies
depending on the type of customer and products. Although the average number of customers serviced in upholstery
engineering and solid wood engineering shows no statistically significant difference, the average number of production
documents generated by each engineering group is different. The difference indicates that the engineering capacity (in
terms of completed customer orders) of the solid wood group appears to be larger than the capacity of the upholstery
group.

From the case study, it was learned that:

 Lean concepts and problem-solving methods are still deficient in the current engineering group.
 ―Processing Time,‖ ―Engineering Error Rate,‖ ―Completion and Accuracy Rate,‖ and ―Engineering Lead Time‖

38
 are four of the most important factors to impact engineering performance in the case study company.
 Engineering lead time accounts for a large portion (21 to 40%) of the overall production lead time.
 Product complexity and engineer competency are two of the most significant influential factors that impact the
engineering lead time.
 Upholstered products usually have longer lead times than solid wood products.
 Currently, the average throughput (in terms of the average number of production documents) of the solid wood
engineering group is higher than the upholstery group.
 The frequency of each type of error is similar between the solid wood engineering group and upholstery
engineering group.
 Engineering change orders (10 to 20%) account for a big portion of engineers’ daily work time.
 3D engineering design solution is having positive impacts on household furniture engineering tasks in terms of
enhanced collaboration, facilitated Computer-aided-Manufacturing, easy document maintenance, automatic BOM
generation, readable drawings, reduced engineering errors, shortened modeling time, easy to make late
engineering changes.

This research presents some limitations. First, the time period of this case study was short. Second, only the
engineering groups from this single case study company were included in the survey. The research did not include
more companies to make a broad conclusion on the whole industry. Third, the numbers of engineers involved in the
survey were not equally distributed between the upholstery engineering group and the solid wood engineering group. It
was not easy to generate better statistic results.

Based on this study, future research should focus on:

 Using lean principles to further identify waste in furniture engineering processes through value stream mapping
 Develop specific methods to further eliminate waste and improve engineering efficiency, with emphasis on:
- Shortening process times and overall engineering completion lead time
- Reduce engineering job batch sizes
- Countermeasures to prevent engineering errors
- Increase customer satisfaction
 Finding opportunities to promote other companies involved in this type of research that focuses on finding lean
opportunities in the non-production area.

39
 CHAPTER 5 USING VALUE STREAM MAPPING TO ANALYZE AN UPHOLSTERY ENGINEERING
PROCESS

5.1 Abstract

This study presents a systematic approach of streamlining an upholstery furniture engineering process based on a case
study in one of the largest export-oriented furniture manufacturers in China. The approach encompasses an analysis of
the current state of the engineering process and the proposal of a lean future state value stream map (VSM). The current
state analysis includes the definition of the product family, analysis of current customer demands, and the definition of
the process metrics of the engineering process. Data was collected during a half month visit to the furniture plant in
China. Results from the current state VSM shows that the value-added ratio of the current engineering process is 26.0%.
A lot of engineering steps present deficiencies such as the processes of creating drawing, compiling mass production
documents, checking and signing-off engineering documents, creating CNC programs, and generating packaging files.
After the current state VSM, it is found that unpredictable process cycle time and expediting engineering change orders
are two major problems in the current engineering process. Based on current state VSM, the research focuses on
countermeasures to solve the root causes of the major problems and proposes the best practices for the future VSM.

5.2 Introduction

The goal of Lean Thinking is to use least resources and time to deliver desired customer value through a continuous
flowing value stream (Hoppmann, 2009). Among different types of lean implementation methods such as pull system,
cellular manufacturing, one-piece-flow, standard work, visual control, Kaizen, quick changeover, 5S, and kanban event
(Rahn and Consulting, 2001; Van Goubergen and Van Landeghem, 2002; Feld, 2000; Henderson, Larco, and Martin,
2000; Rother and Shook, 1998), value stream mapping (VSM) appears as an important tool to facilitate the lean
transformation because it maps both the information flow and materials flow, identifies various types of wastes, and
streamlines the value stream to the future state (Womack and Jones, 1996b).

VSM has demonstrated its effectiveness in streamlining the manufacturing processes to maximize customer value
(Womack and Jones, 1996b; Rother and Shook, 1998). However, nonproduction activities such as design and
engineering, appear to have a significant influence on production cost and lead time (Ehrlenspiel et al., 2007; Tapping
and Shuker, 2003; Boothroyd, Dewhurst, and Knight, 2001; B. Prasad, 1996; Anderson, 1990), so a lot of industrial
participants are trying to engage in applying lean principles in the nonproduction activities of knowledge-based areas
such as design, new product introduction (NPI), engineering, and product development (PD) (Baines et al., 2006).
Other applications of VSM in non-manufacturing industries could be found in sales process, health care, admission
inquiry process and information management (Barber and Tietje, 2008; Kim et al., 2006; Tischler, 2006; B. Keyte and
Branson, 2004).

In the secondary wood products industry, lean principles and techniques had demonstrated its effectiveness, especially
on enhancing the productivity of furniture manufacturing process (Hunter, 2008; Motsenbocker et al., 2005; Hunter,
Bullard, and Steele, 2004). VSM also showed its power in streamlining the manufacturing process for the wood
industry (Quesada-Pineda, Haviarova, and Slaven, 2009; Espinoza, 2009; Czabke, 2007). However, lean principles
could also create benefits to nonproduction processes in the secondary wood products industry such as the engineering
process (Czabke, 2007). The impact of the engineering process in the production cost is extremely important (Baines et
al., 2006); however, research emphasis in the application of lean principles to the engineering process has not been
found in furniture manufacturing industry. This study exhibits a road map to evaluate current state value stream
mapping of furniture engineering processes to identify both value-added and non-value-added engineering activities
towards fulfilling customer requirements. In the meantime, future state will be analyzed and evaluated according to
KPIs found through survey questionnaire and process efficiency investigated through on-site study to give solutions as
to how valid and useful the future state would be to the industry.

40
5.3 Literature review

5.3.1 Lean engineering

Lean Thinking principles have been mostly applied to manufacturing activities. However, practitioner and researcher
have given so much attention to the implementation of lean principles and the mapping of manufacturing processes,
that they overlooked the importance of other non-manufacturing processes such as design and engineering that directly
affect the cost in the product life-cycle (Baines et al., 2006). Womack and Jones (1996a) indicated that lean principles
are also a fit for areas outside manufacturing processes and these principles have great potential and benefits if applied
to knowledge-based activities such as design, new product development (NPD), engineering, and product development
(PD) (Donald Reinertsen, 2005; Middleton, Flaxel, and Cookson, 2005; Browning, 2003; Haque, 2003; Freire and
Alarcón, 2002). Some examples of lean applications in engineering process can be found in the aerospace, automotive,
software and construction industries (Baines et al., 2006). For example, Freire and Alarcón (2002) developed a lean
design process for a construction project based on lean manufacturing concepts and methods. They proposed four
stages to carry out effective methods in the design process for improvements:

• Diagnosis and evaluation

• Changes implementation
• Control
• Standardization

Following the above methodology, Freire and Alarcón applied seven lean tools on five potential areas of a product
development process in the construction industry. The applied lean tools resulted in an effective engineering
performance which led to increased value-added activities, reduced product unit errors, largely decreased waiting time
and reduction of cycle time.

Furthermore, Haque (2003) conducted a research of lean engineering in the aerospace industry. He restated five-step
lean principles applied to a manufacturing process (Rother and Shook, 1998; Womack and Jones, 1996a) and further
redefined each principle in a lean engineering manner. Then he applied three different lean applications (Kaizen on a
design process, Single piece flow in New Product Introduction (NPI), off-line development to speed time to market) at
three different levels – process hierarchy, detailed design, and project management, on three case study companies. He
also mentioned the importance of modular design as a lean tool to facilitate product engineering on easing future
modification or evolution of products and the reuse of design elements. In the case of an ―off-line development of
products‖ illustration, modular design showed its effectiveness on reducing lead time by 25-50%. Other research by
Browning (2003) came up with the conclusion that applying lean to the product development processes is not all about
minimizing cost, shortening cycle time and reducing waste, but its application can also maximize customer value.
Middleton, Flaxel, and Cookson (2005) also showed an application of how the lean manufacturing concepts could be
transferred to lean implementation in software development. The techniques and principles were utilized to streamline
the software engineering process include in Table 5.1:

41
Table 5.1 Lean practices in software engineering
Methods Explanation
Continuous-flow processing By handling work in small batches, jobs can begin earlier and certain
mistakes in requirements can be quickly identified.
Customer defined value By visiting customer, cross-functional team can ensure the product features
that is under development can meet all the customer requirements
Design structure matrix (DSM) and flow Use Kano analysis to connect the voice of the customer with data, which
enables scope/features trade off decisions that are developed on facts
Takt time Pace work according to customer demand; break down projects into
manageable units
Linked processes By placing component parts near one another, travelling within the office
building is effectively reduced
Standardized procedures Enable transfer of people between projects as needed
Eliminate rework Try to find the root cause of a defect and then permanently resolve it;
meanwhile, invest more time understanding the customer need and context
Balancing loads Analyze the skills needed per unit of work and rearrange skills to eliminate
the bottlenecks and finally eliminate the delays
Posting results To give constant feedback to learn where problems and errors are, then the
staff can figure out when the work can be done and how much capacity is
available
Data driven decisions Enable self-management of team and reduce supervision costs. Also reduce
the number and duration of meetings.
Minimize inventory Breakdown the project into smaller parts, only a small amount of work can
go through the system at any given time

Reinertsen (2005) incorporated lean manufacturing methods to deal with the inherent variability in product
development process. Five key methods were applied to streamline the product development process, queue
management, batch size reduction, cadence, rapid local adjustments, and waste elimination. Table 5.2 shows some of
most important past research on lean product development and engineering.

42
Table 5.2 Literature on lean product development and engineering
Author Title Outcomes
Freire and Achieving Lean Design Process: Proposed a methodology to achieve a lean design process
Alarcón 2002 Improvement Methodology for the construction industry by applying seven tools for
improvement based on five areas – client, administration,
project, resources, and information.
Haque 2003 Lean Engineering in the Aerospace Proposed applying lean principles to three different levels
Industry of engineering processes:
• Detailed design level
• Project management level
• Design strategy level
Browning On Customer Value and Improvement in Demonstrated the effectiveness of ―maximizing value‖ as
2003 Product Development Processes a preferred way to incorporate ―lean‖ in the product
development process architecture compared to the
effectiveness of ―minimizing cost and time‖
Reinertsen Let It Flow Proposed to apply five key methods of lean manufacturing
2005 to address the inherent high variability of product
development. The methods encompassed queue
management, batch size reduction, cadence, rapid local
adjustments, and waste elimination
Middleston et Lean Software Management Case Study: Demonstrated the effective application of lean principles
al. 2005 Timberline Inc. in software engineering.

The above examples show the similarities of specific methods used for streamlining the engineering process were
inherited from the lean production methods.

5.3.2 Value Stream Mapping (VSM) in wood products industry

In the wood products industry, research had utilized Value Stream Mapping methodology. Czabke (2007) conducted a
survey in the secondary wood products industry and listed value stream mapping as an important Just-in-time
production practice in the lean manufacturing process. Espinoza (2009) used value stream mapping to portray the flow
of information and materials and to identify specific quality control activities in the wood products supply chain. Also,
based on a case study of three companies located in Honduras, Costa Rica, and Guatemala, Quesada-Pineda, Haviarova
and Slaven (2009) utilized value stream mapping to conduct quantified research analyzing the value-added times for
wood products manufacturing companies in Central America. Key findings in the research included:

 Raw material inventory accounts for most of the waste in the three case study companies
 Value-added time ranged from 8.8 to 12.3 percent of total process lead time. The kiln drying process should be
targeted first rather than other processes to improve the value stream.

5.4 Methods

This research was conducted through a case study of a large household furniture manufacturer in China. Seventeen
days were spent in the upholstery product engineering department collecting relevant process information including
process time, inventory, customer demand, error rate, and types of processing waste. The methods used for collecting
the process data included data entry sheet, direct observation, and engineering archives. Then, the current state VSM
was generated based on these process data. Furthermore, through waste analysis, several improvement opportunities
were proposed and the future state VSM was applied. For data collection and analysis method used, please refer to
chapter 3.

43
5.5 Results

The results section shows the general engineering functional flow chart to help give an initial understanding of the
engineering processes in the case study company. Before proceeding to VSM, several analysis were conducted
concerning process metrics. First, customer demand was calculated on a daily basis. Then the product family was
defined for further planning for the VSM. Second, the process analysis section was composed of process boundary
analysis and main process analysis. The boundary analysis used the context diagram to analyze the interaction between
the engineering system and its external factors. The main process analysis identified and categorized each main process.
Additionally the process metrics were analyzed and current state VSM presented. The next step was to discover the
waste and unnecessary steps in the current state mapping. Several proposals were given to streamline the process and
then the future state VSM was developed.

5.5.1 General Engineering Function

Before proceeding into the details of the engineering process, a brief functional flowchart (see Figure 5.1) provides an
overall understanding of the whole engineering function associated with other departments in this company. This
process flowchart represents a typical engineering sequence for designing most of the case goods and upholstery
products in this company.

44
 Functional Flowchart of the Furniture Engineering Process

Product Development Engineering Production Packaging engineering

Research and Product

compile customer architecture
requirements research meeting

Round dimension
and create Create Packaging
perspective Drawing
drawings

Yes Check Packaging

Revise design
Documentation

No

Create Detailed Yes Need

Drawings Modification

No

Need NC Yes
Generate NC code
Michining

No

Create Bills of
Check NC code
Material

Yes
Check Drawings Revise Code

No

Revise
Drawings Produce Mock-up
Yes

No

Review, Sign-off
Preproduction Preproduction
Documentation Wrap-up

Distribute
Preproduction
Documentation Drop Test

Revise
Engineering
Design
No
Yes
Mass Production

Figure 5.1 A typical furniture engineering process by using functional flow chart

By using the functional flowchart shown in Figure 5.1, the typical furniture engineering process was identified.
Engineering interacts with several internal departments. The department of Product Development is considered as the
supplier of the engineering department since they provided the original files and product specification to the
engineering process. Also the production department can be seen as the internal customer of the engineering process
since engineering gives the production documents to fabricate the products.

45
From the chart (Figure 5.1), it was observed that the Product Development department took the product specification
and original drawings to the Engineering department through product structure discussion meeting. Then the engineers
started to round dimensions on the original drawings and created the perspective drawings. As long as the overall
dimension was defined, packaging engineer could work on preparing the packaging files for Production. At the same
time, product engineers gave their feedback on where changes to the original design were needed to accommodate
production capacity. Their feedback was sent back to Product Development department for customer confirmation and
then the next iteration was started. After product engineers confirmed the information from the customers’ drawings,
they generated detailed drawings. Since the detailed drawings contained the fabrication drawing for each component,
certain parts of the drawings that needed accurate fabrication were sent to Computer Numerical Control (CNC)
programmers to complete the NC code and later were sent to the CNC machining group in the Production for
debugging and making adjustments. As detailed dimensions had already existed in the drawings, the bills of material
(BOM) could be generated at this time. Except for some specifications formulated to facilitate the production process,
the production document was almost finished. Next, the engineering supervisor checked the preproduction documents
and returned them to the responsible engineer for any further necessary modification. If no more changes were needed,
the engineering manager signed-off the preproduction document and distributed it to Production for fabrication.

The mock-up group in the manufacturing plant used the preproduction document to fabricate the mock-up. Since the
CNC machining group in the production had already debugged the CNC code, the fabrication template and any
essential mold (like dies) program for fabrication was generated for the mock-up process. When the mock-up products
were built, production used the packaging file and wrapped the products up for the first trial and then tested for the drop
test. If any problems arose during the mock-up, the production associates informed the engineer who was responsible
for the product to make modifications on the mass production documents. When all the necessary revisions and
iterations were completed and no more changes were made at this stage, the mass production document was compiled
and issued to the manufacturing plant to begin mass production.

5.5.2 Product family and customer demand analysis

5.5.2.1 Product family analysis

Product family refers to a set of products that share a common platform but have individual features and functionality
satisfying a variety of customer needs (Meyer and Utterback, 1993). By focusing on the product family and analyzing
a process of similar product architecture, an easy way for new product development could be provided that could save
engineering time, improve product quality and reduce manufacturing costs.

The product family is defined by two considerations – engineering procedures and historical customer demand
(frequency of orders). If a collection of products possessed a similar structure and manufacturing methods, it could be
considered a product family. On the other hand, if a collection of products with similar structure and engineering
procedure had been ordered frequently by customers, it made sense to create a product family for these product groups
to ease engineering and manufacturing efforts.

In the furniture engineering and manufacturing process, the product architecture is diversified for different products.
Solid wood products and upholstery products are two types of general product classifications for household furniture.
Solid wood furniture typically includes the collection of bedroom, living room, and dining room furniture such as
drawer chest, armoire, bed, china cabinet and so on. Therefore case goods are the typical products in the solid wood
collection. On the other hand, the upholstery products mainly include sofa, ottoman, chair, bench, loveseats and so on.
The majority of products in the upholstery plant are fabric-based products. Since this case study was conducted in the
upholstery plant, the product family was defined from a set of typical upholstery products that shared similar structure
with the same engineering procedures and had a constant demand from the existing customer base.

After researching customer orders for all collections of upholstery products incurred in the last six months (Beau Keyte
and Locher, 2004), in Figure 5.2, it was observed that five types of products accounted for 86.4% of orders. The
products included sofa, chair, ottoman, sofa chair, and loveseat. Three products (sofa, chair, and loveseat) shared the
very same product architecture but were differentiated in length within each product collection. In other words, an

46
engineer had to create sofa engineering documents, and then the documents of loveseat and chair could be easily
created by scaling and stretching the design elements in the existing documents. Since these three types of products
shared the same product architecture, their engineering, manufacturing, planning and packaging process were similar in
complexity. From the order frequency perspective, these three types of products represented 60 percent of customer
orders during the previous six months. From the above analysis, the product family was identified as sofa, loveseat, and
chair products.
Order distribution - upholstery products
100% 100%
94.5% 98.2% 99.1% 100.0%
90% 90.9% 90%
86.4%
80% Percent 80%

Cumulative Percentage
76.4% Cumulative
Relative Frequency

70% 70%
65.5%
60% 60%
50% 50.0% 50%
40% 40%
30% 26.4% 30%
23.6%
20% 15.5% 20%
10.9% 10.0%
10% 4.5% 3.6% 3.6% 10%
0.9% 0.9%
0% 0%
Sofa Chair Ottoman Sofa chair Loveseat Settee left arm Right arm Corner Bench
tufted tufted
sofa sofa

Figure 5.2 Customer demand of upholstery products in the last six months

5.5.2.2 Customer demand analysis

A few indicators were used to analyze the customer demand in the primary and secondary engineering process based on
the data for the last six months. These indicators include ―average orders per month‖, ―total number of current monthly
orders‖, and ―orders per day‖. Based on these important indicators, two important measurements were calculated
(―Work-In-Progress (WIP) inventory‖ and ―takt time‖) for analyzing the process efficiency. The WIP inventory is the
basis for calculating the total lead time for delivering the finished products or service in the value stream (Beau Keyte
and Locher, 2004). The takt time synchronizes the pace of completing each work unit to the pace of customer demands
(Rother and Shook, 1998).

As the total number of orders within the product family for the last six months was 159 product orders, the information
shown in Table 5.3 was summarized for the primary engineering process:

Table 5.3 Indicators for primary process

Indicators Unit Value
Average orders per month Orders 26.50
Total # of cur. monthly orders Orders 43.00
Available monthly work time Days 24.50
Orders per day Orders 1.76
Daily available work time Min. 480.00
Takt time Hr. 4.50

47
The ―orders per day‖ is essential for further calculating the days used to consume the inventory (in terms of engineering
orders) within different processes. This information allows calculations for the elements of value stream mapping.

5.5.3 Process analysis

5.5.3.1 Process boundary analysis

Context diagram was used to show the interaction between a system and its important external factors (Kossiakoff and
Sweet, 2003). It was used to analyze the system boundary of the engineering process. From Figure 5.3, two suppliers
were identified in the current engineering design system: Product Development and Production. In this situation,
Product Development performed the following tasks:

 Fabricated original product samples and ship to customer for confirmation

 Confirmed with customer on design changes and acquire product original drawings from customer
 Compiled engineering and fabrication specifications for each product collections and handover to engineering to
generate production documents
 Delivered the customer-confirmed color board to facilitate finishing and production

On the supplier side, the production department needed to make sure that they could deliver the updated production
plan to the engineering department on a timely basis since this schedule was the foundation for creating the engineering
plan. Production plan was developed based on customer orders. The production time was calculated backwards from
the shipping date on the order. Because engineering usually took a significant portion of production lead time, an
accurate engineering plan could ensure the on-time delivery of products. According to the survey results (see previous
chapter), engineering accounted for 21%-40% of production lead time.

Figure 5.3 Engineering design context diagram

From the customer perspective, engineering provided service for a number of manufacturing processes. These
processes were the downstream customers of the engineering processes. The interactions between engineering
department and downstream customers are explained below:

 Rough mill: responsible for processing the raw material into treated material to be prepared for machining process.
So engineering provided BOMs for the rough mill by providing the following information:
 The quantity of materials needed to be prepared
 The rough and net dimension of each pre-machining component
 The number of each component
 The board dimension for panel gluing or brick stacking

48
 Machining process: engineering needed to provide machining process with a number of essentials:
 Fabrication drawings for making components
 Assembly drawings for subassembly and final assembly of products
 Profile drawings for verifying the precision of component fabrication accuracy
 Programs for CNC manufacturing
 BOMs to check component dimension and part number
 BOMs to require hardware and accessories for assembly

 Production quality control: engineering provided essential assembly drawings, instructions, and specification to
help ensure the quality of products during production process

 Thermoforming center: in general, this process had three functions:

 Provide wood-based panel to production plants. In this situation, engineering needed to prepare bills of
material for thermoforming process that indicated the amount and dimension of the material in demand.
 Fabricate fancy panel for production. For this, engineering provided them with veneer drawings for
parquetting veneer on face panels.
 Fabricate plywood panel. In this case, the engineering provided drawings to verify the shape of fabricating
panels. Also, the CNC engineers were responsible for providing programs for the die fabrication.

 Carving process: engineering provided carving drawings to the carving mills

 Packaging process: packaging engineer was in charge of generating packaging documents for packaging process.
A packaging document typically includes the drawings, bills of material, and instructions for a specific furniture
product.

 Procurement department: engineering provided drawings and specification for the new material and tooling
purchase.

 Mock-up team: this team implemented preproduction, a necessary step before mass production. It had the full
function in mass production. Thus engineering not only provided preproduction documents for this process, but
also tracked the fabrication progress and helped solve problems due to design flaws.

5.5.3.2 Main Process analysis

Andersen and Fagerhaug (2001) defined a process as ―a logic series of related transactions that converts input to results
or output.‖ The engineering process is an important component of a business process since it is ―a chain of logical
connected, repetitive activities that utilizes the enterprise’s resources to refine an object (physical or mental) for the
purpose of achieving specified and measurable results/products for internal or external customers‖ (Gothenburg, 1993)

After having identified the product family, the different processes of engineering used to make the family of products
were identified as well. Figure 5.1 shows a typical furniture engineering process by using a functional flow chart.
Furthermore, based on the initial study, 15 major processes for engineering the sofa products were identified. Each
process is explained in Table 5.4:

49
Table 5.4 Main Engineering Process
ID Process Interpretation
1 Research Product Generally, this process is fulfilled by a product architecture discussion meeting.
Architecture The attendees include associates from three departments which are Product
Development, Engineering, and Production. The goal of this meeting is to figure
out product architecture in the context of customer requirements, engineering
feasibility, and product manufacturability.
2 Create drawings and bills of Drawings include perspective drawings, assembly drawings, part drawings,
material (BOM) cutting tool drawings for fabrication. BOM includes both bills of material and
bill of hardware.
3 Create fabric cutting The previous step completes the drawings for solid wood and wood-based
drawings components. Since most of the upholstery products contain fabric material, the
fabric cutting drawing is generated to telling the production associates how to
process the fabric.
4 Apply new material SKU# Since new product inevitably needs to use new material, so engineers need to
apply new SKU# for each type of material to facilitate the procurement process
5 Create law tag This is a mandatory tag shows that the product attributes are compliance with the
local law for distributing and selling in the destination market
6 Fill out material purchasing As long as the SKU# is approved, engineer can start to fill out the purchasing
form form to order certain materials and attach essential drawings and specification to
the use of suppliers
7 Create sofa specifications The specifications include both design specification for engineering details and
manufacturing specification for fabrication details
8 Create 2.5 axis CNC The programs include all the precision machining by the CNC machine such as
programs certain component fabrication templates, part routing programs, and plywood
dies for the thermoforming process
9 Check/sign-off/distribute After all the above processes, preproduction documents are established which
preproduction documents contain all the essential drawings, bills of material, instruction, and
specifications for fabricating a product or product family. Next, the engineering
supervisor will check the document, then the document will sign-off by the
engineering manager and distribute to the manufacturing plant.
10 Follow up preproduction After releasing the preproduction document, engineers also need to coordinate
mock-up process with production associate on fabricating the mock-up and collect feedback on
fabrication difficulties in the mock-up process
11 Compile mass production According to the fabrication feedback in the mock-up process, engineers could
document start improving the engineering design and making adjustments in the mass
production document
12 Check/sign-off/distribute Engineering supervisor and manager do the same process to check, sign-off, and
mass production documents distribute mass production documents
13 Create fabric manufacturing This process paralleled with the process of generating production documents.
specification The document not only include detail design specifications, but also contains
detailed information on fabric material and what specific area of a certain
product will apply this material
14 Create packaging document This process happens after the process of generating production documents. The
packaging document include all the drawings, BOM, and specification for
packaging a furniture product
15 Create 5-axis CNC program This process parallel with the process of generating production documents. It
usually deals with 3D-shaped components that are difficult to generate in the
2.5-axis CNC machine.

50
5.5.3.3 The differentiation of primary and secondary engineering process

Depending on the attribute of the engineering tasks, the engineering process could fall into two major engineering
activities – the primary engineering process and the secondary engineering process. Through the interview, the
engineering supervisor defined the primary furniture engineering process as major value-added engineering activities
toward product architecture design. Secondary furniture engineering process refers to subordinate value-added
activities used to assist and realize the product engineering for production.

Primary engineering process encompasses all the regular engineering activities toward generating the production
documents, whereas the secondary engineering process encompasses specific engineering tasks that are only performed
by certain technical engineers. Some engineers have multiple roles in completing engineering tasks in both primary and
secondary process. Table 5.5 lists the primary engineering process and the secondary engineering process.

Table 5.5 Engineering Process

Primary engineering process: • Research Product Architecture
• Create drawings and bills of material (BOM)
• Create fabric cutting drawings
• Apply new material SKU#
• Create law tag
• Fill out material purchasing form
• Create sofa specifications
• Create 2.5 axis CNC programs
• Check/sign-off/distribute preproduction documents
• Follow up preproduction mock-up process
• Compile mass production document
• Check/sign-off/distribute mass production documents
Secondary engineering process: • Create fabric manufacturing specification
• Create packaging document
• Create 5-axis CNC program

5.5.4 Process metrics and unit

Lean metrics could help people understand the impact of their efforts toward continuous improvement and waste
elimination (Tapping and Shuker, 2003). In order to determine the appropriate process metrics, a relatively larger
selection base which has 11 metrics (Table 5.6) was prepared. Then the engineers gave their individual rankings of
these metrics on a scale of 1 to 5. The final process metrics were determined from the top four higher ranked metrics.

51
Table 5.6 Definition of each process metric
Metrics Interpretation
Processing time The time that the engineer spent on generating the production documents without doing any
(cycle time) other tasks
Value-added time The sum of each process cycle time
Queue time The time that the engineer did not spend on value-added activities such as making phone calls.
Error rate The number of error occurred in each production document divided by the total number of
production documents
Engineering lead From the moment that Product Development department handed the new products over to the
time moment that the production documents were completed and distributed to the production plants
Number of The total number of engineers in an engineering unit
engineers
Overtime The extra time spent outside the normal work time
Changeover time The time that engineers needed to convert from one task to another
Completion & The number of on time delivered and minor error production documents divided by the total
accuracy rate number of production documents
Inventory The number of unfinished engineering tasks between the processes
Reliability of tool The reliability of all the essential software and hardware in completing the engineering tasks

Four most highly ranked lean metrics for the value stream mapping were identified: ―processing time,‖ ―queue time,‖
―lead time,‖ and ―completion & accuracy rate‖. Since the ―processing time‖ equals the ―lead time‖ minus the ―queue
time‖, the process metrics were chosen as ―processing time‖ and ―completion & accuracy rate‖.

5.5.5 Process cycle time and Lead Time

Because of the time limit of this on-site case study, it was difficult to track the process time of each engineer. So under
the recommendation of the engineering supervisor, three engineers were selected from the engineering group that could
represent the most accurate process cycle time an engineer typically took to complete each engineering process. An
evaluation form was used to collect results from these engineers. The average value of process cycle time for
completing each engineering process is shown in Table 5.7. From this, the value-added time was calculated as 8.8 days.

The results of non-value-added time were collected by using the following methods. First, a day was defined as the
checkpoint to count the unfinished orders within different processes. Second, an evaluation form was sent out to each
of the engineers (15 upholstery engineers). On the form, the engineers indicated which step they had completed from a
current order and how many orders they had not finished. Thus, knowing how many orders had not been finished
(inventory) prior to certain engineering steps (Table 5.7), the total lead time could be calculated by summing up all the
value-added time and non-value-added time. Thus, the lead time of the primary engineering process was calculated as
133.9 days.

52
Table 5.7 Value-added time versus non-value-added time
Value-added Time (Process cycle time): Min. Non value-added Time: Days
1. Research product architecture 120 Prior ―Research product 1.3
architecture‖
2. Create frame and fabric drawings and Prior ―Create frame and fabric 2.1
dimension table 714 drawings and dimension table‖
3. Create fabric cutting drawings and Prior ―Create fabric cutting 2.2
hardware table 274 drawings and hardware table‖
4. Apply new material code 15 Prior ―Apply new material code‖ 2.2
5. Create law tag 20 Prior ―Create law tag‖ 2.2
6. Fill out material purchasing form 15 Prior ―Create material purchasing 2.2
form‖
7. Create sofa manufacturing specification 20 Prior ―Create sofa frame 2.2
description‖
8. Create 2.5-axis and 5-axis CNC 375 Prior ―Create template and CNC 10.2
programs programs‖
9. Check/Sign-off/Distribute preproduction Prior ―Check/Sign-off/Distribute
documentation 1080 preproduction documentation‖ 19.3

10. Create packaging docs. Prior ―packaging docs.‖

310 18.0

11. Compile mass production 605 Prior ―Compile mass production 25.0
documentation documentation‖
12. Check/Sign-off/Distribute mass 696 Prior ―Check/Sign-off/Distribute
production documentation mass production documentation‖ 12.2

Total process cycle time (in days) 8.8 Total lead time (in days) 133.9

5.5.6 Value Stream Mapping – Current State

Before generating the current state VSM, some single steps in the main engineering processes in Table 5.7 needed to
be grouped together to form major processes in the current state VSM. In this case, the processes of ―create frame,
fabric drawings/dimension table,‖ ―apply new material code,‖ ―create law tag,‖ and ―run new material purchasing
work flow‖ were combined as ―create drawings and instructions‖. Similarly, ―Create fabric cutting drawings and
hardware table‖ and ―create sofa manufacturing specification‖ were combined as ―create BOMs and specifications.‖ So
steps were integrated from 12 steps to 8. The reason for separating the processes ―create drawings and instructions‖ and
―create BOMs and specifications‖ during the investigation was that it was much easier to track the process cycle time
of each smaller activity instead of tracking the whole activity, which usually took a longer period of time in a
discontinuous basis.

53
 Figure 5.4 Group some of the small events into individual activity

After grouping, integrated value-added time and non-value-added activities are presented in Table 5.8.

54
Table 5.8 Restructured primary engineering process
Value-added Time (Process cycle time): Min. Non value-added Time Days
1. Research (research product architecture) 120 Prior to ―Research product 1.3
architecture‖
2. Drawing (create drawings and Prior to ―Create drawings and 8.7
instructions) 764 instructions‖
3. BOM (create BOM and specification) Prior to ―Create BOM and 4.4
294 specification‖
4. CNC (create 2.5 and 5 axis CNC 375 Prior to ―Create 2.5 and 5 axis CNC 10.2
programs) programs‖
5. Check (check/sign off preproduction 1080 Prior ―Check/sign off/distribute 19.3
docs). preproduction docs‖
6. Packaging (create packaging docs). 310 Prior ―Create packaging docs.‖ 18.0
7. Compile (compile mass production 605 Prior ―Compile mass production 25.0
docs) docs‖
8. Check (check/Sign-off mass production 696 Prior ―Check/Sign-off/Distribute
docs). mass production docs.‖ 12.2

Total process cycle time (in days) 8.8 Total lead time (in days) 133.9
Total processing time (in days) 34.8

55
Figure 5.5 Current State Value Stream Mapping (VSM)

56
5.5.7 Current State Analysis

Current state overview:

As all the elements in the value stream had already been identified, a current state VSM was generated to have an
overall picture of the current engineering process (Figure 5.5). In the current state VSM, both supplier and customer
are internal. The internal customer is production. Production informed engineering of the production schedule four
weeks prior to anticipated need. Based on the production schedule, engineering developed a schedule for making new
products. The engineering supervisor oversaw the monthly schedule and triggered each individual engineering activity.
A Material Requirement Planning system was used to develop and manage this schedule.

The supplier is the internal Product Development department. Product Development oversaw communication with
external customers, collecting all the customer requirements, compiling these into specification files, and delivering
original drawings and customer specifications to engineering. New product requirements were handed over to
engineering through group discussion meetings where Product Development presented important new product designs
and engineering specifics to the engineering group. This meeting was organized twice a month, which meant
Engineering requested customer specifications for new product development every two weeks.

In the engineering process, there were nine individual engineering activities which are listed in Table 5.5. The process
cycle time varied from 120 minutes (research product architecture) to 1080 minutes (check preproduction production
document). The work-in-progress orders between each engineering activity varied from 1.3 days to 25 days. The
engineering lead time was about 133.9 days, whereas the value-added time was just 34.8 days. The value-added ratio
was 26.0% which is represented by using the value-added time (34.8 days) divided by the non-value-added time (133.9
days).

Problems:
From current state value stream mapping, two major contributors to the overall lead time, shown in Figure 5.5, are
excessive work-in-progress orders and unbalanced process cycle time. Recall the initial study in chapter 4, a couple of
things had been distracting engineers’ value adding capability. The two most important ones were the unpredictable
and unbalanced process time, making it difficult to level workloads and distractions due expediting engineering change
orders (ECO). The following discussion will focus on finding the root causes of these problems. By identifying root
causes to these problems, a future state VSM can be developed to present the countermeasures.
Process cycle time
1200 1080
1000 764 Takt: 273 min
696
Minutes

800 605
600 375
400 294 310
120 145
200 Process cycle time
0

Figure 5.6 Takt time versus process cycle time

In Figure 5.6, it shows that only three processes could keep pace with customer demands. Several processes exhibited
very high cycle times. For instance, engineering could not work on compiling mass production documents for a couple
of days before they got all the production feedbacks from mock-up process. Furthermore, engineering supervisors and
managers could not guarantee their regular day time work to check engineering documents because they got interrupted
all the time. So significantly and costly overtime must be used or the company got behind. From observations, many
interruptions led to ―unpredictable and unbalanced process cycle time‖ as well as ―excessive engineering change orders
(ECO).‖ This translates into excessively long cycle times to complete an engineering activity. These interruptions can

57
be summarized as different types of waste. From direct observation, the following types of waste (Table 5.9) could be
identified that constantly interrupted engineers’ value-added work:

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Table 5.9 Interruptions in the engineering process
Type of Waste Examples
Waiting  Waiting the design changes from the customer approval
 Waiting the feedback from the mock-up process
Extra processing  Interruption while creating drawings (phone calls, inquiries, computer
breakdowns).
 Various copies/formats of part drawings
Correction  Work on engineering changes
Excess motion  Printer and plotter were far from reach
Transportation  Long travel distance in the process of generating engineering documents
(review)
Underutilized people  Unevenly distributed tasks
 Limited authority of engineers (waiting for approval)
Inefficient information flow  Inefficient Office Automation (OA) system for engineering inquiry
 Inefficient communication between product engineers and production associates

5.5.8 Root Causes Analysis:

The root causes of the two major problems found in the previous section, unpredictable and unbalanced process cycle
time, as well as expediting engineering change orders (ECO), in the current engineering process can be explicitly
expressed in Figure 5.7. Each root cause is explained the following discussion.

Figure 5.7 Root causes of two major problems

Lack of standardization:
In the current process, many parts and assembly models did not have standard drawings. The engineers employed their
own designs of commonly used parts and assembly, and this lack of standardization led to parts proliferation and large
inventory in the manufacturing process. Also, the lack of standardization increased the possibility of errors in the
engineering design and finally product engineers took a large portion of time issuing engineering change orders (ECO).
From the previous study in chapter four, 67%-69% of the engineers answered that it took 10%-20% of their daily work
time to address ECOs. ECOs were considered as reworks and did not create value to customers.

Inefficient communication:
Inefficient communication includes the communication with external and internal customers. External customer refers
to the real customers who purchased the products. Sometimes, a design change needed to be confirmed with the
external customers, which took several weeks. This made the engineering lead time unpredictable. From the previous
study in chapter four, engineering lead time accounted for 21%-40% of the overall production lead time. The
confirmation process contributed to the engineering lead time.

59
Communication with internal customers in production was another problem. From the current state VSM in Figure 5.5,
the ―compile‖ process had the longest process cycle time which implied overtime was used to keep pace with customer
demand. A major cause for overtime was the mock-up process. Engineering had to wait a couple of days to collect the
mock-up feedback before they worked on compiling the mass production document. This waiting time created
unpredictability in the compiling process cycle time and it also contributed significantly to the overall engineering lead
time.

Insufficient engineering capacity:

Lack of people on certain tasks resulted in unbalanced process cycle time and inevitably increased overtime. For
example, there was one supervisor in charge of checking all the engineering documents. Although checking and
signing-off engineering documents was one of their responsibilities, the supervisors also had other tasks, such as
preparing engineering work plans, solving engineering-driven problems in production, communicating with suppliers
and meeting with customers. Therefore the supervisor in each engineering group had difficulty managing all these tasks.
The available working time of an engineering supervisor was 480 minutes a day and the takt time was 273 minutes.
This meant the supervisor needed to check, sign-off, and have someone distribute the engineering document at least
once a day. The supervisors were too busy to check the production document once a day. Sometimes they needed to
travel and no one could take over their tasks.

Inefficient work layout:

In the current office environment, engineering and other departments share one printer. The printer was placed in a
separate room where on average it took 25 to 30 seconds for an engineer to travel by foot to pick up a piece of paper.
Even worse, the printer was packed with print-outs from several departments and it took a while for the engineers to
search for their documents and collect all the drawings needed.

Inefficient engineering design tool:

Based on the survey study in chapter 4, ―drawing errors‖ and ―part dimension errors‖ were the two most frequent errors
in the engineering documents. Also from the survey study, the results showed that SolidWorks (a 3D engineering
design software) was capable of reducing design errors and generating bills of material (BOM), which demonstrated
the importance of an efficient design tool for improving engineering performance.

Next, the use of future state VSM has the potential to solve these root causes in the engineering process. Although the
future state is not the ideal state; it shows the big picture of lean transformation process for a specific value stream. The
future state VSM will not solve all the problems but it could be the next stage of improvement that is likely achievable
within a specified time and cost budget.

5.5.9 Future State Analysis:

Countermeasures for ―Lack of standardization‖:

In current engineering process, standardization is supposed to focus on two things. One is the standardization for
managing the work load; the other is the standardization of quality engineering design. The effects of work load
management is indicated in the huge process cycle times in steps such as ―Drawing‖, ―Compile‖, and ―Check‖. The
engineers are responsible for managing and evening out their work load. Without a standardized procedure, none of
engineers were efficient in managing their work loads.

Besides, the effects of quality design are evident in several parts that do not have a standard model to generate
drawings. This lack of standardization results in confusion and errors in the downstream processes. Engineers develop
individual designs and architecture leading to parts proliferation in the manufacturing process and excessive
engineering errors. Also no standard drawing format exists for production documents, which causes difficulty finding
useful information on the drawings when needed.

60
A potential countermeasure for solving the work management problem is to balance and level engineer work load
through process combination and automation. An implementation is to combine ―Drawing‖, ―BOM‖, ―Check‖
(preproduction document), and ―Compile‖ (mass production document) into one process ―DWG/BOM‖, then focus on
changing the way of creating drawings and automating generation of BOM based on existing design. Previously, each
engineer created drawings from beginning to end for a product. This led to large process cycle time because no method
existed to manage the work load. However, work load balance could be better managed if parts drawings were
separated into smaller job pieces. For instance, the supervisor could assign one person to create drawings for a sofa arm
frame, another person to create one for a back frame and so on; in the end, a new engineering document will be
compiled by putting together the drawings from each engineer. Furthermore, by using SolidWorks, the engineering
team could also generate bills of material (BOM) based on an established 3D model. So the process cycle time for
creating BOM will be zero. In this way, work load would be managed at a smaller scale and could predict processing
time more accurately.

Countermeasures for ―Inefficient communication‖:

The inadequate communication between engineering and external customers led to situations in which the customer
could make changes anytime during the engineering process. This inevitably resulted in a lot of rework and an
unpredictable process cycle time. Therefore it was necessary to establish a Frozen Zone to control the number of
customer changes. The Frozen Zone set an end point where customers could not make further product changes.

On the other hand, it can be observed from Figure 5.5, that the process cycle time of the ―compile mass production
document‖ process is much longer than the takt time. This is because engineering could not start compiling the mass
production document until they received the summary report of changes from the mock-up process. So the ―compile‖
processing time is not long (less than one work day) based on the investigation, but the process cycle time shows a
longer time period which averaged ten days. While waiting, engineers started working on other projects to offset their
time loss. In this case, the countermeasure was to create a mock-up progress log which recorded the feedback from
mock-up processes on a daily basis, so engineers could work on the engineering changes immediately instead of
waiting for the final report. The processes of ―check preproduction document‖ and ―compile mass production
document‖ could be eliminated because all the changes were completed in time and conducted in a steady pace in
parallel with the mock-up process instead of on a sequential basis, which involved a lot of waiting. Also the same work
log solution could be applied to the processes of ―CNC‖ and ―Packaging‖ which could reduce process cycle time by 30%
(from 375 minutes to 263 minutes) and 20% (from 310 minutes to 248 minutes) respectively.

Countermeasures for ―Insufficient engineering capacity‖:

According to the current state VSM, the ―check‖ process runs out of capacity and it is hard to catch up with customer
demand. Therefore, appropriate check methods and capacity planning are needed to deal with the bottleneck.

The proper check method helps to shorten the process cycle time. Usually, after completing the engineering documents,
the engineer printed out all the drawings, bills of material, and specifications for the engineering supervisor or manager
to review. Then these files were returned to engineers to make changes and print again for sign and distribution. This
process involved waste and extended the engineering process cycle time. The online checking does not need to print
every drawing or file and each engineer can work on corrections immediately as long as they receive the electronic files
from supervisors or manager.

Furthermore, from Figure 5.5, check process had one operator (which was one of the two engineering supervisors).
Due to not enough operators in this process, it could not keep pace with t customer demand therefore caused significant
overtime. In order to meet to the takt time, in the future state, the check process involves all the engineering
management in this process, which includes two engineering supervisors and one manager. Also there will be just one
―check‖ process in the future state VSM. So the process cycle time of checking engineering documents would be
reduced from 1776 minutes on average to 296 minutes, plus the effect of on-line review is supposed to reduce 10% of
process cycle time to 266 minutes. In this way, the process cycle time of the check process is more close to the takt
time. .

Countermeasures for ―Inefficient work layout‖:

61
Currently, the engineering work layout is not well organized. Some engineers had to walk around to deliver material to
the supervisor on the other side of the work area. The printer and plotter were far away forcing the engineers spend a
portion of their day traveling back and forth to print out drawings. It is necessary to propose a work cell layout to
enhance productivity so supervisors and engineers can physically work together and office supplies are easy to reach.

Countermeasures for ―Inefficient engineering design tool‖:

The appropriate design tool can help prevent ―drawing errors‖ and ―part dimension errors‖ identified in previous study
(chapter 4). Although SolidWorks cannot guarantee improvement on the speed of engineering design, it can help
improve the quality of engineering design with less errors and flaws. The design features in SolidWorks are helpful in
solving excessive engineering change orders (ECO) problems. For instance, SolidWorks can check the existing 3D
model and find any interference (overlapped area of components in the assembly) in the current design to prevent
potential design flaws in the drawing. This proactive solution can help reduce design changes. Additionally,
SolidWorks can also automate bills of material (BOM) which needed manual entry before.

Table 5.10 is a summary of all the root causes, countermeasures, and kaizen events. According to the countermeasures,
the future state VSM is generated suggesting target improvement areas and the potential improvement outcomes that
could be achieved.

62
Figure 5.8 Future State Value Stream Mapping (VSM)

63
In the future state VSM (Figure 5.8), engineering planning sends work instruction to the first process step at the
beginning of the value stream. The overall process is flowing in a First-In-First-Out basis. The starting point of the
process is to send new orders to ―research‖ process from Product Development. The FIFO lane will keep the order
inventory in 1 day maximum. Then researched orders will pass on ―DWG/BOM‖ process for creating drawings and
bills of material in a 2-day FIFO maximum. Specific kaizen events aim to balance certain processes and improve
engineering performance. For instance, the kaizen events proposed for ―DWG/BOM‖ process include standardization,
BOM automation, new design tool, frozen zone, and work layout planning. The downstream processes like ―Fabric‖,
―CNC‖, and ―Packaging‖ will also receive jobs on FIFO basis. Finally, all the work will send to ―check‖ process for
final approval. The total lead time of future state VSM is 15.0 days, or an 88.8% reduction from the current state VSM.
The processing time of future state VSM is 9.0 days, or a 74.1% reduction from the current state VSM.

Table 5.10 Summary of countermeasures and kaizen implementation

Root causes Countermeasures Kaizen burst
Lack of  Process ―Standardization‖: Standardize design models, drawing formats
standardization standardization: ―Automation BOM‖: Writing special micro program in SolidWorks
combine and eliminate to automate the process of generating BOM
processes
 Work standardization:
separate and balance
engineer work load
Inefficient  Improve ―Frozen zone‖: Control the expediting changes from customer
communication communication with
customer ―Work log‖: Summarize production feedback on daily basis for
 Improve engineers. Increase the speed of making essential changes for mass
communication with production documents before releasing
supplier
Insufficient  Improve work method ―Online-check‖: The engineering management check the documents
engineering  Increase people on-line to eliminate paper waste and unnecessary processing time
capacity utilization ―Capacity‖: Utilize all the engineering supervisors and managers for
checking process
Inefficient  Reorganize work ―Layout‖: Move necessary office supplies close to engineers;
layout layout propose work cell layout for current work environment
Inefficient  Use 3D dimension- ―Design tool‖: utilize SolidWorks to reduce the chance of making
engineering driven engineering design errors and reduce the number of ECO
design tool design solution –
SolidWorks

The following Table 5.11 is a summary of what could be implemented and improved in the future state VSM compared
to current state VSM:

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Table 5.11 Metrics comparison – current state versus future state
Process cycle time Error rate Rework time
Current Future Change Current Future Change Current Future Change
state state state state state state
Research 120min 120min 0% 3% 3% 0% 0% 0% 0%
Drawing 764min 257min 66.4% 1.3/doc 1.0/doc 23% 20% 10% 50%
BOM 294min 2.0/doc 20%
CNC 375min 263min 30% 5% 2% 60% 10% 5% 50%
Check 1080min - - 2% - - 5% - -
(Preproduction)
Packaging 310min 248min 20% 5% 3% 40% 5% 3% 40%
Compile 605min - - 3% - - 5% - -
Check 696min 266min 61.8% 2% 1% 50% 3% 1% 66.7%
(Mass
production)
Fabric 145min 145min 0% 3% 3% 0% 10% 10% 0%

From Table 5.10, it can be observed that the proposed countermeasures will help to balance and level the process cycle
time, and also reduce the error rate. This table would establish a dashboard of target performance metrics with which
design engineers can gauge, monitor, and sustain their improvement progress toward the Future State Value Stream.

5.6 Conclusions:

The results indicate the current engineering process is inefficient. The processes of ―Drawings‖, ―Check‖, and
―Compile‖ exhibited long processing cycle times. The current state process takes a lot of overtime to address
expediting orders. Waiting, interruption, inefficient engineering system and uneven workload were typical problems
resulting in long lead time for engineering

Insufficient engineering capacity is a major contributor resulting in the ―Check‖ bottleneck. There is only one
supervisor in charge of checking and signing-off all the engineering drawings and documents. However, the supervisor
also needs to deal with other important tasks and it is difficult to guarantee the daily work time needed to check and
sign-off engineering documents. Another bottleneck process, ―Compile,‖ also takes a large process cycle time. This is
because sequential engineering involves a lot of time to fix design flaws and errors before releasing the final
engineering documents.

Bottlenecks and large inventories also showed in secondary engineering processes such as ―CNC‖ and ―Packaging.‖
Lack of people in the secondary processes also led to capacity shortage especially when overproduction happened in
the upstream processes (primary processes), which made it even harder to pace the customer demand. Excessive
inventory piled up between these processes.

In future state VSM, several fundamental countermeasures were proposed to balance and level the engineering process.
Point kaizens, such as standardization and setting up frozen zone, helped significantly to reduce design iterations so
that only one ―Check‖ process was needed and ―Compile‖ process could be eliminated. From the future state VSM, the
lead time was reduced from 133.9 days to 14.7 days. The FIFO lane was used to make the overall processing time
predictable. Standardization also helped group similar product structures which saved several engineering efforts in
new product development. Also, cross training was an essential measurement implemented to buffer the unexpected
demands.

From this case study, the current engineering process was shown exhibiting many types of waste such as different
interruptions distracting engineering from creating value-added work. By using VSM, the process was streamlined by

65
identifying the steps of the longest processing time and the largest inventory. Then the proposed countermeasures were
used to flow the whole value stream. The results indicated the following conclusions to facilitate future research.

• Identifying the product family, customer demands, process boundary, main process and defining process metrics
and calculation is essential prior research to depict accurate data on the current state VSM.

• In the current state VSM, the processes of creating drawing and bills of material, checking and signing-off, and
compiling the mass production documents develop bottlenecks, and point kaizens are an effective means to
streamline these individual processes for more balanced process cycle time.

• FIFO lanes are helpful for the overall engineering process flow and reduce lead time.

• An appropriate engineering design tool is important to facilitate engineering performance such as fast drawing
delivery and reduced error rate. For instance, the design features in SolidWorks are helpful in solving the
excessive engineering change orders (ECO) problem, by having predefined design models. Also, SolidWorks has
the function to check existing 3D model to locate any interference (overlapped area of components in the
assembly) in the current design, preventing potential flaws in the drawings. This proactive solution can greatly
help reduce design errors.

However this research has some limitations. First, the research was based on a case study of one furniture manufacturer,
although it was an ideal candidate for this research, there was still not sufficient evidence to generate sound results for
the overall industry. Second, the respondents for collecting accurate processing time only included three product
engineers. Although they were best associates available to generate meaningful data, it was still not sufficient to reflect
the performance of the overall system. Third, the limited time frame restricted the research to be conducted within one
month period. More accurate and exclusive conclusions could be made if there were enough time to address more of
the monthly data. Fourth, it would be ideal to have several kaizen events be implemented based on this study in the
case study company. However, the geographical constraints and limited research funding prevented the
countermeasures from this research to be implemented and the results verified.

66
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Appendix A Questionnaire

Survey Questionnaire on Current Engineering Process

The survey is intended to collect information from each product engineer on their understanding of the current
engineering process. The results will help us to better analyze and improve the existing engineering process. Personal
information will not be revealed to any third party. Please feel free to give us your best knowledge of the current
process. Thank you for your participation!

RESPONDENT INFORMATION

1. What Business Unit are you currently working at?

 Unit 1 (Plant 5  | Plant 7 )  Unit 2 (Plant 3  | Plant 6 )

 Unit 3 (Plant 10  | Plant 11 )  Unit 4 (Plant 8  | Plant 9 )

2. What is your position?

 Engineering manager  Engineering supervisor

 Product engineer
Other position(s), please indicate: _________________

3. What is your current experience level in the engineering job?

 Entry level (less than 1 year)  Junior (1 – 2 years)

 Mid level (3 – 5 years)  Senior (6 years and more)

4. What kinds of the following tasks are you responsible for as an engineer in your business unit?

 Determine the product architecture

 Complete production documents (bills of materials, bills of hardware, detailed drawings)
 Making procurement material (drawings and specification) to suppliers
 Plot drawings for product profile verification in the manufacturing process
 Issue Engineering Change Orders, revised drawings based on customer requirements and production needs
 Production documents maintenance
 Check production documents
 Sign-off production documents
 CNC programming
 Product packaging engineering
 Create customer-confirmed component files for archive
Other responsibilities, please indicate: _____________________________________

5. How many engineers are there in your business unit? _____

6. Please check the products making by your engineering group:

 Bedroom  Living room  Kitchen

 Upholstery  Dining room 
Other product collections, please indicate: _________________

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ENGINEERING PERFORMANCE

7. How important are the following Key Performance Indicators (KPIs) on describing the current engineering
performance? (1 = Unimportant; 2 = Of Little Importance; 3 = Moderately Important; 4 = Important; 5 = Very
Important)

Unimportant Moderately Very

Important Important
1 2 3 4 5
    
 Processing time (The accurate time spent on making
    
production documents)
 Value-added time (The total sum of each processing time)     
 Queue time (The time not spent on making production
documents and the time suppose to spend on completing the     
documents wait in the queue. It is the non value-added time)
 Engineering error     
 Lead Time (The sum of processing time and queue time)     
 Number of people     
 Overtime     
 Changeover time (e.g. The time spent to change the paper in
the printer; or the time to load another software from the     
current)
 Percent complete and accurate (the completion rate of
accuracy of the first time delivering of documentations by     
deadline)
 Inventory (unfinished tasks in the queue)     
 Hardware and software reliability     
Others, please indicate:___________________

8. How many production documents on average you made per month for your plant?

1-2 3-4 5-6 7-8 9-10 More than 10

 Preproduction      
 Production      

9. How many customer have you served in the last six months?

# of Customer(s) 1-2 3-4 5-6 7-8 9-10 More than 11

     

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10. If you are a upholstery product engineer, please answer the question of 10-b;
If you are a solid wood product engineer, please answer the question of 10-a.

10-a. In a standard bedroom product collection, what are the average engineering hours for you to complete each of the
following type of product:

Days 1-2 3-4 5-6 7-8 8-9 More than 10

     
Nightstand      
Drawer Chest      
Dresser and Mirror      
Mirror      
Armoire Hutch      
Armoire Base      
Bed      

10-b. In a standard upholstery product collection, what are the average engineering hours for you to complete each of
the following type of product:

Days 1-2 3-4 5-6 7-8 8-9 More than 10

     
Sofa      
Loveseat      
Chair      
Ottoman      
Tufted chair      
Sleeper sofa      
Sofa chair      

11. What is the percentage of time on average you spend to issue the Engineering Change Orders per day?

 Below 20% per day, please indicate a specific range _____% - _____%
 21%-40% per day
 41%-60% per day
 61%-80% per day
 Above 81% per day, please indicate a specific range _____% - _____%

12. What is on average of your engineering design ERROR rate caused by the following reasons in the production
documents that you made?

Number of errors: None 1-2 3-4 5-6 7-8 Above 8

 Part dimension error      
 Wrong amount of assigned parts      
 Dimension missing      
 Wrong hardware applied      
 Wrong amounts of hardware      
 Hardware missing in BOM      
 Wrong hardware receiving dept.      
 Wrong material applied      
 Wrong architecture applied      
 Missing essential drawings      
 Drawing errors      

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13. Please indicate on a scale of 1 to 5 of the following factors (1 = Unimportant; 2 = Of Little Importance; 3 =
Moderately Important; 4 = Important; 5 = Very Important) that you think would be important to affect the engineering
hours and lead time?

Unimportant Moderately Very

Important Important
1 2 3 4 5
    
Product architecture complexity     
Development tool (e.g. AutoCAD vs.
    
SolidWorks)
Engineering process (e.g. traditional vs.
    
simultaneous engineering)
Engineering design specifications     
Changes required by customers or
manufacturing plants (e.g. time to modify and     
reissue drawings)
Cost consideration     
Sample delivery speed from vendors     
Engineers experience and competency     
The research effort to ensure the quality     
Communication and collaboration     

14. What percentage of time does Engineering take in the overall product delivery time (From the time of customer
placing the order to the time of products are produced and ready for shipping)?

 Below 20% of the product lead time

 21%-40% of the product lead time
 41%-60% of the product lead time
 61%-80% of the product lead time
 Above 81% product lead time

15. Has your engineering department ever used ―Design for Manufacturing‖ methodologies to develop new products
(such as Design For Assembly, Group Technology, modular design, drawing retrieval systems, parts commonality list,
feature commonality list, etc.)

 Yes.
 No.

ENGINEERING TOOLS

16. What CAD software have you been used or using for product engineering?

 AutoCAD
 SolidWorks
 SurfCAM
 ChinaCAM
 Gerber
 Other CAD/CAM tools or applications, please indicate: _________________

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17. Compared to AutoCAD, what benefits you agree of using SolidWorks for product engineering?

Strongly Somewhat Don’t Somewhat Strongly

Disagree Disagree Know Agree Agree
    
1 2 3 4 5
Easy to make late design changes     
Shorten the engineering time     
 Reduce the engineering error rate     
Improve readability of drawings     
Facilitate the auto generation of BOM     
Ease documentation maintenance     
Facilitate CAM     
Enhance team collaboration and CE     

LEAN CONCEPTS AND APPLICATIONS

18. To what degree are you familiar with the following lean concepts? (1 = No idea; 2 = Not familiar; 3 = Heard about
it; 4 = Familiar; 5 = Very familiar)

No idea Heard about it Very familiar

Lean Tools and systems 1 2 3 4 5
    
Pull System     
Cellular Manufacturing     
One-piece-flow     
 Standard work     
 Visual control     
 Kaizen     
 Kanban system     
 SMED/Quick changeover     
TPM     
5S     
FIFO     
Heijunka Box     
Value Stream Mapping     

No idea Heard about it Very familiar

Problem-solving 1 2 3 4 5
    
Cause-and-effect diagram     
(Fishbone)
Five why’s     
PDCA     
 A3 Report     

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Appendix B Permission to use Figure 2.1

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