QUALITY PLANNING

and
CONTROL

Didem Demir

1
 Getting Started

–Introduction

–Syllabus

–Expectations

2
 Objectives of This Course
• This course will:
– Provide training on basic and advanced quality
improvement tools
– Teach you the Six Sigma Process Improvement
Methodology, DMAIC
– Provide an introduction to Minitab statistical
software

3
 Syllabus
Define
Quality control systems and quality management
Process Mapping
Measure
Measurement Systems Analysis
Data Collection and Patterns in Data
Process capability analysis
Acceptance sampling
Analyse
Confidence Intervals
Hypothesis tests
Design of experiments (if time permits)
Improve
FMEA (Failure Modes and Effects Analysis)
Control
Methods of statistical process control (SPC)

4
Textbook

5
Software

6
DMAIC Pathway

7
 Expectations
• Your expectations from this course?

8
 Why do we even bother?
• What is the purpose of a (commercial, profit
oriented) business?
– Sell/serve/manufacture???
– Make profit/money???

• Nicer words  make it look like complicated!

– Advantage over competitors
– Sustain in the “global” marketplace

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 Why do we even bother?
• How to sustain and stay competitive?
– Lower costs
– High quality
– Short time
• Examples…
– Cars, appliances, electronics and computers, …
– Hospitals, eateries, banks, hairdressers, …

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Manufacturing/Product vs. Service
• Simultaneous production and consumption

– critical aspects are intangible, not all…

– no inventories or buffers
– considerable variability in delivery
– “substantive” and peripheral components

11
 Product/Service Life Cycle
A typical product realization cycle

It starts with defining the customer needs,

Need and it goes back to the customer again
(market)
Planning

Development

Manufacturing
Sales
(market)
Recycle

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 Quality of a Washing Machine
• How do you define “quality” of a washing
machine?

13
1.1 Definitions – Meaning of Quality and Quality
Improvement
1.1.1 The Eight Dimensions of Quality

1. Performance
2. Reliability
3. Durability
4. Serviceability
5. Aesthetics
6. Features
7. Perceived Quality
8. Conformance to Standards

14
•This is a traditional definition
•Quality of design
•Quality of conformance

15
This is a modern definition of quality

16
The Transmission Example

17
 After Sales Service “Timeliness”
9
LSL USL

8
(Lower (Upper
7
 
Specification Specification
Limit)
 Limit)
6
  
5
   
4
     
3
      
2
      
     
1
0   
-50 -40 -30 -20 -10 0 10 20 30 40 50
Monday Tuesday Wednesday Thursday Friday
Planned Real Delta Real Delta Real Delta Real Delta Real Delta
09:00 08:47 -13 08:49 -11 09:10 10 08:31 -29 08:50 -10
10:00 10:09 9 10:32 32 09:39 -21 09:23 -37 10:04 4
11:00 10:53 -7 10:46 -14 11:14 14 10:47 -13 10:21 -39
12:00 12:15 15 12:23 23 11:38 -22 11:56 -4 11:51 -9
14:00 13:55 -5 13:46 -14 13:37 -23 13:52 -8 14:01 1
15:00 15:15 15 14:42 -18 14:29 -31 15:24 24 14:53 -7
16:00 16:28 28 15:11 -49 15:59
18 -1 16:29 29 16:07 7
17:00 16:51 -9 17:12 12 17:05 5 17:16 16 17:08 8
• The transmission example illustrates the utility of this definition
• An equivalent definition is that quality improvement is the
elimination of waste. This is useful in service or transactional
businesses.

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1-1.2 Terminology

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 Terminology cont’d
• Specifications
– Lower specification limit
– Upper specification limit
– Target or nominal values
• Defective or nonconforming product
• Defect or nonconformity
– Not all products containing a defect are
necessarily defective

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1.2. History of Quality Improvement

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23
24
25
1.3 Statistical Methods for Quality Control
and Improvement

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 Statistical Methods
• Statistical process control (SPC)
– Control charts, plus other problem-solving tools
– Useful in monitoring processes, reducing variability
through elimination of assignable causes
– On-line technique
• Designed experiments (DOX)
– Discovering the key factors that influence process
performance
– Process optimization
– Off-line technique
• Acceptance Sampling
27
Walter A. Shewart (1891-1967)
• Trained in engineering and physics
• Long career at Bell Labs
• Developed the first control chart
about 1924

28
 1.4 Management Aspects of Quality
Improvement
Effective management of quality requires the
execution of three activities:
1. Quality Planning
– Strategic level
2. Quality Assurance
– Tactical level
3. Quality Control and Improvement
– Operational Level

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1.4.1 Quality Philosophy and Management Strategy

W. Edwards Deming

• Taught engineering, physics in the

1920s, finished PhD in 1928
• Met Walter Shewhart at Western
Electric
• Long career in government
statistics, USDA, Bureau of the
Census
• During WWII, he worked with US
defense contractors, deploying
statistical methods
• Sent to Japan after WWII to work
on the census

35
 Deming
• Deming was asked by JUSE to lecture on
statistical quality control to management
• Japanese adopted many aspects of Deming’s
management philosophy
• Deming stressed “continual never-ending
improvement”
• Deming lectured widely in North America
during the 1980s; he died 24 December 1993

36
 Deming’s 14 Points
1. Create constancy of purpose toward improvement
2. Adopt a new philosophy, recognize that we are in a time of
change, a new economic age
3. Cease reliance on mass inspection to improve quality
4. End the practice of awarding business on the basis of price
alone
5. Improve constantly and forever the system of production and
service
6. Institute training
7. Improve leadership, recognize that the aim of supervision is
help people and equipment to do a better job
8. Drive out fear
9. Break down barriers between departments

37
 14 Points cont’d
10. Eliminate slogans and targets for the workforce such as zero
defects
11. Eliminate work standards
12. Remove barriers that rob workers of the right to pride in the
quality of their work
13. Institute a vigorous program of education and self-
improvement
14. Put everyone to work to accomplish the transformation

Note that the 14 points are about change

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 Deming’s Deadly Diseases
1. Lack of constancy of purpose
2. Emphasis on short-term profits
3. Performance evaluation, merit rating, annual
reviews
4. Mobility of management
5. Running a company on visible figures alone
6. Excessive medical costs for employee health care
7. Excessive costs of warrantees

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40
Deming’s Obstacles to Success

41
42
 Joseph M. Juran
• Born in Romania (1904-
2008), immigrated to the US
• Worked at Western Electric,
influenced by Walter
Shewhart
• Emphasizes a more strategic
and planning oriented
approach to quality than
does Deming
• Juran Institute is still an
active organization
promoting the Juran
philosophy and quality
improvement practices

43
 The Juran Trilogy
1. Planning
2. Control
3. Improvement

• These three processes are interrelated

• Control versus breakthrough
• Project-by-project improvement

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 Some of the Other “Gurus”
• Kaoru Ishikawa
– Son of the founder of JUSE, promoted widespread use of
basic tools
• Armand Feigenbaum
– Author of Total Quality Control, promoted overall
organizational involvement in quality,
– Three-step approach emphasized quality leadership,
quality technology, and organizational commitment
• Lesser gods, false prophets

45
 Total Quality Management (TQM)
• Started in the early 1980s, Deming/Juran
philosophy as the focal point
• Emphasis on widespread training, quality
awareness
• Training often turned over to HR function
• Not enough emphasis on quality control and
improvement tools, poor follow-through, no
project-by-project implementation strategy
• TQM was largely unsuccessful
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Quality Systems and Standards

The ISO certification process focuses heavily on quality

assurance, without sufficient weight given to quality planning and
quality control and improvement

48
 Six Sigma
• Use of statistics & other analytical tools has grown
steadily for over 80 years
– Statistical quality control (origins in 1920, explosive growth
during WW II, 1950s)
– Operations research (1940s)
– FDA, EPA in the 1970’s
– TQM (Total Quality Management) movement in the 1980’s
– Reengineering of business processes (late 1980’s)
– Six-Sigma (origins at Motorola in 1987, expanded impact
during 1990s to present)

51
Focus of Six Sigma is on Process Improvement with an
Emphasis on Achieving Significant Business Impact

• A process is an organized sequence of activities that

produces an output that adds value to the
organization
• All work is performed in (interconnected) processes
– Easy to see in some situations (manufacturing)
– Harder in others
• Any process can be improved
• An organized approach to improvement is necessary
• The process focus is essential to Six Sigma

52
What is Six Sigma as a statistical measure?
– Every process/procedure has an expected outcome/
measurement called a “mean”
– Every outcome/measurement has some variability
– The measure of that variability is called “ “
– Reducing variability and defects is good …
… and is the essence of Six Sigma
Customer
Specification
LSL MEAN USL

6
1 1σ

53
 Importance of Reducing Variation
• To increase a process performance, you have to decrease variation.

“Customers don’t experience averages…

they experience the variation”

54
 How Good is Six Sigma Performance?
Measures how good or bad a process is doing

Requirement 6
Sigma DPMO 5
4
1 680,000 3
2 298,000
3
Industry 2
67,000 Average
4 6,000 1
5 400
6 3.4

Defect! OK!

55
 Why “Quality Improvement” is Important:
A Simple Example
• A visit to a fast-food store: Hamburger (bun, meat, special sauce,
cheese, pickle, onion, lettuce, tomato), fries, and drink.

• This product has 10 components - is 99% good okay?

P{Single meal good}  (0.99)10  0.9044

Family of four, once a month: P{All meals good}  (0.9044)4  0.6690
P{All visits during the year good}  (0.6690)12  0.0080

P{single meal good}  (0.999)10  0.9900, P{Monthly visit good}  (0.99)4  0.9607
P{All visits in the year good}  (0.9607)12  0.6186

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 Why do I need six of them?

# of Steps Yield/Step Rolled Throughput

Yield
10 99% (4σ) 90.4%

10 99.9997% (6σ) 99.997%

100 99% (4σ) 36.4%

100 99.9997% (6σ) 99.97%

6σ is a practical standard for most business processes…

57
 DMAIC Solves Problems by Using
Six Sigma Tools
• DMAIC is a problem solving methodology
• Closely related to the Shewhart Cycle
• Use this method to solve problems:
– Define problems in processes
– Measure performance
– Analyze causes of problems
– Improve processes  remove variations and non-
value-added activities
– Control processes so problems do not recur

60
11
Overview of the DMAIC Method

IMPROVE

62
 Define Measure Measures
I P O
The
DMAIC Road Map Business
Case Develop
measures

for Six Sigma Explain why it is

important to work
on this project
based on
CTQ’s and
SIPOC map
Input
Measures
Process
Measures
Output
Measures

Project Charter
Data Collection Plan
Problem Statement: Develop charter to include project
Data Collection Plan
Goal: description, baseline measures, What questions do you want to answer? Develop a
Business Case: business results, team members, Data Operational Definition and Procedures
data
WhatMeasure type/
How Related SamplingHow/
Scope: schedule. Use Benchmarking as Data type measured conditionsnotes where collection
Cost Benefit Projection: appropriate to establish some of plan
Milestones: the initial targets.
How will you ensure What is your plan for
consistency and stability?
starting data collection?
How will the data be displayed?

Gage R&R
Col# 1 2 3 4 5 6
Inspector A B
Sample # 1st Trial 2nd Trial Diff 1st Trial 2nd Trial Diff
1 2.0 1.0 1.0 1.5 1.5 0.0
2 2.0 3.0 1.0 2.5 2.5 0.0
3 1.5 1.0 0.5 2.0 1.5 0.5
S C Validate your 4 3.0 3.0 0.0 2.0 2.5 0.5
5 2.0 1.5 0.5 1.5 0.5 1.0
U U measurement system Totals 10.5 9.5 3.0 9.5 8.5 2.0
P SIPOC S Averages 2.1 1.9 0.6 1.9 1.7 0.4

Control Define P T Sum 4.0 Sum 3.6

L O XA 2.0 R
A XB 1.8 RB

I Inputs Process Outputs M

E E
R R
S S Data Display
Innovative
Improvement Measure 1000
UCL

Display the data in X

0
Analyze graphic form to show
LCL
current variation and -1000

other patterns
10 20 30
Complete high-level
“as is” process map D B F A C E Other
with 5 to 7 key steps
that capture the main 6

action in the process 4

0
7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Gather / display
VOC
6

data verifying
6

5
5

3
Plot defects over time.
customer needs
4

3
2

0
Stratify frequency plots
and do Pareto analysis
7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

and 1
6

requirements 8 9 10 11 12 13 14 15 16 17 18 19 20 21 3

0
7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

VOC Key Issue CTQ

Delighters
Determine Process Sigma
More Is Better
LSL USL

Must Be Process Calculate current

process sigma
Sigma =
2.7 63
BB_Trans_DMAIC Roadmap
Analyze Improve Generating Solutions
Control Product Name
QC Process
Chart
Date of Issue:
Revision Date
Issued by:
Reason
Approved by:
Signature

Process Name
Process Code #
Act Plan
Develop and deploy a plan
Stratification A for how to respond to
Flowchart
Work
Control/Check PointsResponse to Abnormality
InstructionsCode # Charac-Control
Method
teristicsLimits
ImmediatePermanent
Who Fix Fix Who
Notes

4 Check Do

B 1 process changes 1

Queue 1 C 3 2

Process Analysis D 2 12

Process Change
VA NVA Cost-Benefit Analysis
Management
Generate solutions Before After
Queue 2 including Benchmarking
and select best ideas }Improvement Ensure everyone has the
based on screening A1 A2 A3 A4 A2 A1 A3 A4
knowledge, skills, tools, and
Before After
Perform cost-benefit criteria Good
mindset required.
}Improvement
analysis for the }
Remaining Gap
Step 4 changes Target
preferred solution implemented

Perform a detailed Stratify the data to focus your

Selecting the Documentation &
process analysis to project on key problems Solution Standardization
identify problems
Training
Document new process, Curriculum
Training
using training manuals and Manual
other tools to ensure
Assessing Risks standardization
Fill to here
Cause & Effect
Monitoring
Display your
FMEA Recommend a
theories about root solution involving UCL Monitor the process using control
causes using a key stakeholders. charts to ensure process stays in
cause & effect control and conforms to
diagram specification
LCL

Use FMEA to identify

Evaluate Results
risks associated with LSL USL
Hypothesis-Testing the solution and take Piloting Proce
preventive actions Recalculate Process ss
Full scale Sigma and long-term
Test Sigm

Chi-Square t-test
Regression Original financial impact a =
2.7
² ANOVA Analysis
Y
Process
Regression Key Sigma =
X1
Implementation Planning Learnings 3.7
Results
Verify Root causes 1 2 3 4 5 6 7 8 9 10
Use hypothesis A Pilot the solution Document results and
through statistical Learnings
testing to identify B
on summarize key learnings.
tools •
differences C
D a small scale and • Identify potential future projects
•
EG evaluate the and possibilities for replication.
F Recommendations
G
results next
Communicate via JJQM
Design of Experiments H I J Knowledge Network

Develop a full plan Hand off the improvement

Use DOE to
for implementation and project to the process
quantify
change management owner for on-going Closure
relationships
management and 64
rewarding and celebrating
the improvement team.
 Why the Rigor?
Harvesting the Fruit of Six Sigma
Sweet Fruit PPM
Design for Six Sigma

Process Entitlement
5 Sigma Wall, Improve Designs 230
Bulk of Fruit
Process Characterization
and Optimization

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - ---------------- 4 Sigma Wall, Improve Processes 6,210

Low Hanging Fruit
Seven Basic Tools

---------------------------------- 3 Sigma Wall 66,800

Ground Fruit
Logic and Intuition

THE VISION OF SIX SIGMA

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2 . 20
 What Makes it Work?
• Successful implementations characterized by:
– Committed leadership
– Use of top talent
– Supporting infrastructure
• Formal project selection process
• Formal project review process
• Dedicated resources
• Financial system integration
• Project-by-project improvement strategy
(borrowed from Juran)
66
67
 Six Sigma Focus
• Initially in manufacturing
• Commercial applications
– Banking
– Finance
– Public sector
– Services
• DFSS – Design for Six Sigma
– Only so much improvement can be wrung out of an
existing system
– New process design
– New product design (engineering)

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Design for Six Sigma (DFSS)
Taking variability reduction upstream from manufacturing (or
operational six sigma) into product design and development
Every design decision is a business decision

69
 DFSS Matches Customer Needs
with Capability
• Mean and variability affects product performance and cost
– Designers can predict costs and yields in the design phase
• Consider mean and variability in the design phase
– Establish top level mean, variability and failure rate targets for
a design
– Rationally allocate mean, variability, and failure rate targets to
subsystem and component levels
– Match requirements against process capability and identify gaps
– Close gaps to optimize a producible design
– Identify variability drivers and optimize designs or make designs robust
to variability
• Process capability impact design decisions
DFSS enhances product design methods.
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71
 Lean Systems
• Focuses on elimination of waste
– Long cycle times
– Long queues – in-process inventory
– Inadequate throughput
– Rework
– Non-value-added work activities
• Makes use of many of the tools of operations
research and industrial engineering

72
73
Little’s Law

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Lean Focuses on Waste Elimination
• Definition
– A set of methods and tools used to eliminate waste in a
process
– Lean helps identify anything not absolutely required to
deliver a quality product on time.

• Benefits of using Lean

– Lean methods help reduce inventory, lead time, and cost
– Lean methods increase productivity, quality, on time
delivery, capacity, and sales

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76
Quality Costs

77
 Legal Aspects of Quality
• Product liability exposure

• Concept of strict liability

1. Responsibility of both manufacturer and
seller/distributor
2. Advertising must be supported by valid data

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Implementing Quality Improvement

•A strategic management process, focused along the

eight dimension of quality

•Suppliers and supply chain management must be

involved
•Must focus on all three components: Quality Planning,
Quality Assurance, and Quality Control and Improvement

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 Product and Quality Control
Off-line Off-line
Quality Planning Quality Control
Supplier
+ Acceptance Sampling

Inspection
Specs

Planning Design/
Dev. Manuf. Assembly

Specs

Inspection
On-line Inspection
Raw Material Quality Control
(SPC)
82 Sales
 Read..
• Chapters 1 and 2 from your textbook.

84