Management and Production Engineering Review

Volume 11 • Number 1 • March 2020 • pp. 79–85

DOI: 10.24425/mper.2020.132946

IMPROVEMENT OF RAW MATERIAL PICKING PROCESS

IN SEWING MACHINE FACTORY USING LEAN TECHNIQUES
Kotcharat Srisuk1 , Korrakot Y. Tippayawong1,2
1
Department of Industrial Engineering, Faculty of Engineering, Chiang Mai University, Thailand
2
Excellence Center in Logistics and Supply Chain Management, Faculty of Engineering, Chiang Mai University,
Thailand

Corresponding author:
Korrakot Y. Tippayawong
Chiang Mai University
Excellence Center in Logistics and Supply Chain Management
239, Huay Kaew Road, Chiang Mai, 50200 Thailand
phone: +66 53 944 125
e-mail: korrakot@eng.cmu.ac.th

Received: 2 October 2018 Abstract

Accepted: 14 February 2020 This study demonstrates application of Lean techniques to improve working process in
a sewing machine factory, focusing on the raw material picking process. The value stream
mapping and flow process chart techniques were utilized to identify the value added ac-
tivities, non-value activities and necessary but non-value added activities in the current
process. The ECRS (Eliminate, Combine, Rearrange and Simplify) in waste reduction was
subsequently applied to improve the working process by (i) adjusting the raw material pick-
ing procedures and pre-packing raw material as per demand, (ii) adding symbols onto the
containers to reduce time spent in picking material based on visual control principle, and
(iii) developing and zoning storage area, identifying level location for each row and also
applying algorithms generated from a solver program and linear programming to appropria-
tely define the location of raw material storage. Improvement in the raw material picking
process was realized, cutting down six out of 11 procedures in material picking or by 55%,
reducing material picking time from 24 to 4 min or by 83%. The distance to handle material
in the warehouse can be shortened by 120 m per time or 2,400 m per day, equal to 86%
reduction. Lean techniques proved to provide significant improvement in sewing machine
company operations.
Keywords
Value stream mapping, warehouse improvement, lean logistics, productivity.

Introduction In this work, a sewing machine company locat-

ed in Lamphun, Thailand was used as a case study.
Various industries need to survive during recent Its working process was studied. Its key products
economic downturns, including machine manufactur- are household sewing machines and accessories. Its
ing companies. Therefore, they need to improve their sales offices are located worldwide and quality con-
competitive advantage by reducing cost and increas- trol was among the top priorities of the company.
ing profits. Lean techniques are among the prominent Moreover, the company puts top priority on prod-
techniques that can be used to analyze and improve uct cost controlling and enhancing logistics efficien-
the operation processes. The techniques have been cy that broadens the competitive opportunity to the
used widely in large manufacturing industries such markets nowadays. Thus, the efficiency improvement
as automotive and electronics. However, reports on in factory warehouse process was initiated. The staff
application of Lean techniques to labor intensive as- working in raw material picking process accounted
sembly line and manufacturing SMEs are quite rare. for 42% of the entire employees. The raw material
Valuable insights may be obtained from experiences picking was one of the core processes of warehouse
in applying and practicing these Lean techniques to management which can affect the production process
an SME that may be useful to other SMEs. immediately when the staff picked the wrong mate-

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rial or delayed the process. Therefore, improvement to analyze processes and sub-processes to visualize
of the raw material picking process is among the top improvement potentials [7], and decrease production
priorities for enhancing company performance which lead time [8, 9].
can potentially eliminate wastes or non-value added KAIZEN is a concept of continuous improvement.
activities (NVA) in the warehouse, hence, it can effec- This philosophy seeks to improve all factors relat-
tively reduce the production cost as well as logistics ed to the process of converting inputs into outputs
cost. High performance raw material picking process on an ongoing basis. It covers equipment, materials,
is therefore necessary for expansion plan for produc- methods, and people [10]. Impact from the VSM ap-
tion in the future. proach have been shown to reduce time in raw mate-
The objectives of this study were therefore to ap- rial preparation process, eliminate non-value added
ply Lean techniques in reducing complication and travelling activities in automobile part warehouse
time in the raw material picking process of an SME, since those activities were considered as waste pro-
and to discuss practicality issue of the techniques to cesses [9]. To improve warehouse operations, pick
general manufacturing firms. up process should be initially improved because it
is the most time-consuming activity in the ware-
Literature review house. De Koster and co-workers [11] demonstrated
that there were four ways to reduce travel distance
Various research works concerning warehouse op- in the warehouse for an order-picker, by optimizing
erational process optimizations have been investigat- (1) storage location assignment, (2) warehouse zon-
ed and studied to develop the raw material pick- ing, (3) order batching, and (4) pick-routing method.
ing process in sewing machine factories. Relevant Location assignment in the warehouse was modified
tools such as Lean Techniques, Value Stream Map- by Zhang [12], where correlated storage assignment
ping (VSM), Flow Process Chart Analysis, Contin- strategy was implemented to reduce the travel dis-
uous Improvement based on ECRS principles, ABC tance in the packing process. Meanwhile, Schweitzer
Classification to classify raw materials, Linear Pro- [13] proposed the optimized model or order sequenc-
gramming application to position the raw material ing and order picking system to improve the average
locations have been applied. Simplex and Dual Sim- turnaround times and improved flow of containers in
plex Algorithm by applying Microsoft Excel Solver the automatic container warehouse. Picking improve-
have been adopted to decide best location of raw ments by different techniques have been reported in
material on shelves. various industries such as automotive [9], beverage
Recently, logistics improvement techniques have [14], health care product retail distribution [15]. Dif-
been proved that they can actually reduce signifi- ferent techniques were required for heavy and light
cant logistics cost for SMEs as demonstrated in those weight cargos. Reduction of distance and process-
cases from northern Thailand [1]. The improvements ing time had important influence on the total time
have been reported in terms of the modification of for picking since they were considered having major
physical layout to reduce internal logistics distance contributions in the warehouse picking process [9].
[2], or adjusting the management policies both in Investigation on waste processes in the picking ac-
operation process or warehouse practice. Lean tech- tivity can bring about improving work method and
niques have been found to be intensively implement- eliminating excess processes, leading to better pro-
ed in SMEs operational processes for minimizing ductivity in the warehouse.
costs, using poor quality materials or overloading Based on previous reports, many approaches
workers with work [3]. could potentially be adopted to improve the raw ma-
Lean concepts proved to be popular for devel- terial picking process in this sewing machine facto-
oping production and enabling continuous improve- ry. The picking process was the most expensive ac-
ment [4]. Moreover, from a lean production point of tivity in warehousing operations. It was considered
view, inventory management required a reduction in a top priority to increase productivity [9]. However,
inventory wastes in terms of costs, quantities and it should be pointed out that the best improvement
time of non-added value work [5]. It could further method is to observe the actual process, identify root
reduce cycle time in complex production environ- causes and effects, and listen to employees’ feedback
ment through the application of Value Stream Map- to understand the expectation of internal customers.
ping (VSM) [6]. VSM could be drawn for the en- These practicality issues are important and can shine
tire supply chain, a process or a single sub-process. some lights in successful applications of similar Lean
The VSM have also been used in a non-detailed way techniques to other SMEs.

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Methodology from high to low, left to right to highlight the biggest

problem or most common sources of defects. ABC
This work focused on the improvement resulting Classification, applied in this study, was used to cat-
from elimination of raw material picking processes egorize inventory into 3 types. A was the highest or-
and time. The research approach consisted of three der demand or fast moving, typically accounted for
following steps. 20% of total inventory items. B was inter-class items,
Step 1: Focus areas for improvement were se- with a medium consumption value; and C was low or-
lected by brainstorming among warehouse and head der frequency but high inventory value. Subsequent-
of production staffs to identify initial areas for im- ly, linear programming was integrated to assign most
provement in the warehouse department. The prob- appropriate location for each item. Linear Program-
lems from warehouse activity were listed, and de- ming (LP) is widely known technique and applied to
cision were made herein using the Pareto concept. warehouse allocation problems in previous research
From this stage, it was identified that the picking works. Basically, LP applies mathematical model to
process should be improved since this activity con- provide optimize results based on limited resources.
sumed the highest time among other warehousing The resources could be represented in terms of man-
activities. The ideas and inputs from operators were power, time, space, number of materials, or machine
very important during this stage. capacity. In this study, best location of each spare
part was calculated from (1) with the constraints
Step 2: The raw material picking flow process
from (2) and (3)
was sketched through VSM. The purpose of creating M X N
this diagram was to identify sequence of activities, Min
X
fi eij xij , (1)
time, distance of overall picking process at a cur- i=1 j=1
rent stage. The value added (VA), non-value added N
(NVA) and necessary but non-value added (NNVA) X
Subject to xij = qi , (2)
activities could also be identified from the current i=1
flow. At this stage, changes in work procedures to M
improve VA and NNVA activities were introduced
X
xij ≤ 1; xij = (0, 1), (3)
and real implementation to the factory to eliminate i=1
NVA activities was proposed and carried out.
where the variables are defined as: fi – picking fre-
Step 3: The implementation of appropriate im-
quency of material i, eij – distance between ma-
proving process was put in place. KAIZEN or contin-
terial i to location j, qi – space need to store mate-
uous improvement technique was implemented here-
rial i, xij = 1 – accept to store material i in loca-
in as the idea of changing and process continuous im-
tion j, 0 unaccepted to store material i in location j,
provement. This guideline was widely utilized in in-
M – material lists, N – levels to store raw materials.
stitutes or organizations focusing on three concepts;
The new warehouse layout was subsequently pro-
Eliminate, Reduce and Change. Kaizen can be re-
posed from the output of the calculation. The lay-
ferred to as action to reduce and eliminate unneces-
out was re-arranged, dependent on assembly line and
sary processes by slowly changing working methods
picking frequency. Meanwhile, the vertical storage
step by step to optimize the working efficiency. Con-
shelf was re-assigned, based on picking frequency and
tinuous improvement and employee’s participation
ergonomic concept. Several actual implementations
were the core concepts of the Kaizen principle. ECRS
were conducted in sewing machine manufacturing
is one of the prominent techniques of KAIZEN, which
site. Evaluation was conducted. The number of pro-
was implemented in this study. E is referred to Elim-
cesses, times, and distance in warehouse operations
inate, C is to Combine, R is to Rearrange and S
were expected to improve.
is to Simplify, respectively. This principle was em-
ployed with the ultimate aims at employee partic- Results
ipation to reduce 7 wastes discovered from current
process [4]. Analysis results of current state
Inventory management in this study was basical- Improvement of raw material picking processes
ly managed by ABC Classification similar to that was outlined after brainstorming with the section
in [11]. Those inventories were classified into A, B head and seven warehouse staff. The staff evaluated
and C types, based on picking frequency. Pareto Di- the process in the raw material warehouse by scor-
agram, one of 7 QC tools, was used to analyze and ing the key processes that needed to be improved
classify data of materials in the warehouse to seek to meet the production demand more speedily and
for data arranging problems. The data was arranged accurately. The raw material picking process was

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scored the highest point of 3,800 or equivalent to staffs was assigned to pre-pack the materials after
41.7%. incoming inspection process. The pre-pack was un-
The raw material picking process was studied us- dertaken prior to storing those parts into the ware-
ing VSM by examining the working process. The pri- house. This rearrangement appeared to shorten the
mary data was collected to draw the overview of the raw material picking process in the way that no part
raw material picking process in a current state VSM, had to be counted before the picking. The deliv-
as shown in Fig. 1. There were 11 activities, with av- ery of the packed parts to the production line was
erage picking time of 24 min. Only one VA activity quicker. The improvement was found to eliminate
was found, which was the raw material picking ac- NVA activities, wastes from transportation and over-
tivity that accounted for about 8% of the total time. production, summarized as follows:
After the current state VSM was sketched, over- • the raw material picking activities reduced from
all picking processes became more comprehensible. 11 to 6 activities or equivalent 45%,
The wastes could be detected from each stage. The • the raw material picking time reduced from 24 to
flow process chart appeared to identify one VA, four 6.48 min or equivalent to 72%,
NVA and six NNVA activities from the material pick- • the raw material picking distance reduced from
ing process. Actual implementation was subsequent- 140 to 50 m or equivalent to 64% of raw material
ly carried out in the factory warehouse. For the re- storage area.
sulting improvement, NVA activities were eliminated
and NNVA activities were combined and rearranged.

Improvement of raw material picking process

Improvement of the raw material picking process
was initiated from adding pre-packing method in the
receiving area. This method was started from un- Fig. 2. The pre-packing process in raw material picking
packing the material box and pre-packing into the process.
required number specific part into a plastic bag (Pre-
pack). The key issue was that the number required Apart from improving the picking process, re-
parts in the plastic bag must be equal to the produc- arrangement of the raw material storage area was
tion demands. Thus, the materials were readily pre- also important that could enhance the picking pro-
pared for the future demand once they were received. cess. The storage location was initially arranged to
This improvement was achieved with no additional suit suppliers, facilitating the storing material pro-
operation cost. The pre-packaging was found to meet cess and space utilization, but not particularly useful
the production demand with flexibility in terms of to the picking process. The working staff had to walk
responding to change in quantity. The pre-packing around the warehouse to pick the materials, result-
process is shown in Fig. 2. ing in long picking time and distance. To reduce the
Moreover, line balancing was also applied in the picking time and unnecessary movement, the storage
pre-packing process. One out of 11 material picking area was re-arranged accordingly.

Fig. 1. Current state VSM of picking process.

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Improvement of storage location in warehouse

The data from the preceding one year picking of
approximately 14,000 records were accumulated from
the material picking department. The data were an-
alyzed in terms of picking frequency and rearrange-
ment from fast to slow movement. The picking data
was again divided by production line of each sewing
machine model. The ABC classification was subse-
quently applied to assist in allocating the storage
area of each part based on the corresponding pro-
duction line and the frequency of part picking. The
allocation result was described in the later section.

Zone picking or pick by line area allocation

The storage area was adjusted using the data cat-
egorized from the previous ABC classification. New
storage area was arranged as follows; (i) the area was
alternated from storage by supplier to storage by as- Fig. 3. The storage re-arrangement by assembly line and
sembly line, and (ii) parts/ materials were allocated picking frequency.
on the shelf by fast moving rule. The fast moving
materials/ parts were located at the front line of the
shelves, close to the door where materials were deliv-
ered to the production (fastest turning closest to the
door). The new warehouse arrangement is displayed
in Fig. 3.
Fig. 4. The vertical storage re-allocation by picking fre-
Fixed location storage quency and ergonomics concept.
One shelf contains five levels whose level should
be assigned to each material subsequently. In the From the analysis of picking data for each pro-
previous zoning storage, it was suggested only what duction line zoning, the most frequent pick materi-
materials needed to be kept in the shelf close to als were to be stored at Level X, followed by Y and
the door, but no further information was obtained. the less frequent pick parts were to be stored in Le-
Therefore, the storage shelf was subsequently classi- vel Z. Once the most suitable location of each part
fied into three levels; X, Y, and Z. The shelf position was assigned and implemented, the resultant picking
is shown in Fig. 4 time was then evaluated and found to be reduced
• Level X allowed the position staff to pick the ma- from 6 to 1 min or equivalent to 83% in time reduc-
terials easily and comfortably. tion. The distance travelled required by the staff was
• Level Y required the position staff to stand on tip- also found to be collectively shortened from 50 to
toe or bend down to pick the materials. 10 m, which was 80% saving. The corresponding im-
• Level Z required the position staff to kneel down provement of the raw material picking process using
to pick the materials. ECRS is summarized and can be seen in Table 1.

Table 1
Value analysis of picking raw materials before and after improvement.
Description Before improvement After improvement Amount reduced Percent reduction
Value added (VA) 2 min 1 min 1 min 50%
Non-value added (NVA) 14 min 0 min 14 min 100%
Necessary but non-value added (NNVA) 8 min 3 min 5 min 62.5%
Picking flow 11 flow 5 flow 6 flow 55%
Picking lead time 24 min 4 min 20 min 83%
Picking distance 140 m 20 m 120 m 86%

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A limitation may be noted here that using Mi- References

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