This slide contains information about a case study of six sigma methodology, DMAIC approach. How to do an analysis, find the root cause and area to be improved through DMAIC methodology, just covered in this slide.

1. Six Sigma Approach for Industrial Quality
Improvement and Defect Elimination
Md. Injamamul Haque
St. Id. 117001
Md. Saiful Amin Chowdhury
St. Id. 117005
Shaim Mahamud
St. Id. 117012
Supervised by:
Engr. Prithbey Raj Dey
Assistant Professor
Dept. of Industrial & Production Engineering
Dept. of Industrial & Production Engineering
Dhaka university of Engineering and Technology, Gazipur.

2. Objective with specific Aims
2
• Identifying a set of defects occur in the production system.
• Evaluating the major defects by statistical analysis.
• Obtaining sigma level of the current state of the quality.
• Finding the background causes of the major defects.
• Proposing the appropriate tool to reduce the defect rate.

3. Motivation
3
Ready Made Garments (RMG) sectors in Bangladesh faces some common
problems:
• High rate of rejection.
• Rework.
• Wastage of resources.
• Long cycle time.
• Low productivity.
Data taken from:
1. A Plus industries Ltd.
2. Anthony Young Garments Ltd.

4. Outline of Methodology
4
• Collecting the relevant data.
• Developing the probability distribution function.
• DPMO and sigma level calculation.
• Selecting the major defects
• Cause Effect diagrams to identify the root causes.
• Suggesting appropriate and efficient solutions to eliminate the defects.

5. What is Six Sigma?
5
• Six Sigma is a disciplined, data-driven approach for process improvement
Methodology Set of statistical tools Metric

6. Graphical representation of Six Sigma
6

7. Objectives of Six Sigma
7
 Overall
Business
Improvement
 Remedy Defects
 Reduce Costs
 Reduce Cycle Time
 Increase Customer
Satisfaction

8. 8
Define
Measure
Analyze
Improve
Control
Analyze
Design
Verify
Six Sigma Methodologies

9. DMAIC Approach
9
Define Measure ControlAnalyze Improve
Problem
Project
goals
Customer
requirements
Data
collection
Process
performance
Identify root
causes of
defects
Prioritize
opportunities
to improve
Identify
sources of
variation
Identify
possible
solutions
Select
solution
Implement
Define
control
method
Implement
&
Document

10. DMADV Approach
10
Define Measure VerifyAnalyze Design
Problem
Project
goals
Customer
requirements
Explore data
Design
solution
Predict
performance
Develop
detailed
design
Refine
predicted
performance
Develop pilot
Identify
customers
Research
VOC
Benchmark
Quantify
CTQs
Evaluate
pilot
Scale-up
design
Begin
production

11. DMAIC Approach: Case Study
11
Skip stitch Uneven Stitch missing
Broken stitch Puckering Shading

12. Analysis for A Plus Industries Ltd.
12
Number of
skipped
stitch
Quantity
found
0 771
1 127
2 39
3 20
4 10
5 10
Total 977
Fig. Poisson distribution curve for line 1
Production line no. : 1 Section: Sewing

13. Analysis for A Plus Industries Ltd.
13
Number of defects
Defects L-1 L-2 L-3 L-4 L-5 L-6 L-7 L-8 L-9 L-10Total
Shading 0 13 16 0 0 17 3 22 8 29 108
Uneven 11 0 20 2 53 0 26 24 14 29 179
Stitch Missing 0 0 11 2 0 0 0 19 0 0 32
Broken Stitch/ Uncut 0 0 12 2 0 0 0 5 0 0 19
Puckering 16 0 18 9 0 0 0 16 15 17 91
Bubble 0 0 12 8 19 0 0 16 12 0 67
Skip Stitch 49 108 16 13 59 76 16 16 13 14 380
Stain/Dirt spot/Oil mark 44 0 10 4 12 10 0 21 1 6 108
Slanted 16 0 10 13 0 0 0 8 0 21 68
Damage fabric 0 2 5 0 0 4 0 16 0 0 27
Total 136 123 130 53 143 107 45 163 63 116 1079
Fig. DPMO calculation for
A Plus Industries Ltd.

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Pareto Analysis: A Plus Industries Ltd.
380
179
108 108 91 68 67
32 27 19
35.2%
51.8%
61.8%
71.8%
80.3%
86.6%
92.8%
95.7%
98.2%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
0
200
400
600
800
1000
NumberofDefects
Types of Defects
Pareto Chart

15. Control Chart: A Plus Industries Ltd.
15
To find out the relative impact of defects in different lines, control charts are drawn for each
defect. Among defects, Stitch skip causes that the maximum number of production line (L-2,
L-5, and L-6) out of control.
UCL 56.493
CL 38.000
6.8
26.8
46.8
66.8
86.8
106.8
126.8
L-1 L-2 L-3 L-4 L-5 L-6 L-7 L-8 L-9 L-10
NumberofDefects
Line No
Skip Stitch
Fig. Control chart for Skip Stitch

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Analysis for Anthony Young Garments Ltd.
Defects
Design
Specification
Allowable
Tolerance
AQL* level
Uneven in Sleeve length shoulder 63 ±1.5 >4.0
Uneven in Cuff Height 5 ±0.5 >4.0
Uneven in bottom height 7 ±0.4 >4.0
Uneven in Collar Stand Height 3 ±0.2 >4.0
Uneven in Neck Width 20 ±0.5 >4.0
Uneven in Pocket Length Centre 12.5 ±2.4 >2.5
Uneven in Placket width 3 ±0.4 <2.5
Uneven in Placket Length 31 ±4.5 =2.5
Uneven in Pocket width Upper 12.5 ±1.0 >4.0
Uneven in Shoulder Across 42 ±1.5 >2.5
Allowable tolerance for Uneven Defects

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Analysis for Anthony Young Garments Ltd.
Fig. 4.24 Normal distribution curve for uneven in
sleeve length shoulder
Line No: 1 Section: Sewing
Defect Name: Uneven in Sleeve length shoulder
Designed Measure (Mean) = 63 cm
Standard Deviation = 1.66
Number of defected items = 18

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Analysis for Anthony Young Garments Ltd.
Number of defects
Defects L-1 L-2 L-3 L-4 L-5 L-6 L-7 L-8 L-9 L-10 Total
Shading 2 6 1 0 0 2 1 3 8 2 25
Uneven 180 60 110 110 60 40 20 30 70 40 720
Stitch Missing 1 4 2 0 4 6 2 7 7 6 39
Broken Stitch/ Uncut 2 1 0 1 4 1 3 5 2 3 19
Puckering 6 2 0 2 6 0 2 10 7 2 37
Bubble 1 0 0 4 7 2 0 9 9 5 37
Skip Stitch 5 12 5 3 2 4 2 9 11 10 63
Stain/Dirt spot/Oil mark 1 0 5 3 1 3 2 0 2 0 17
Slanted 1 0 2 5 3 5 3 2 7 0 28
Damage fabric 0 0 0 0 1 1 4 3 2 2 13
Total 199 85 125 128 88 64 39 78 125 70 998
Opportunities 500
Defects 998
Units 10
DPMO 199,600
% Defects 19.96
% Yield 80.04
Sigma 2.34
Cp 0.78
Fig. DPMO calculation
for Anthony Young
Garments Ltd.

19. Pareto Analysis: Anthony Young Garments Ltd.
19
720
63
39 37 37 28 25 19 17 13
72.1%
78.5%
82.4%
86.1%
89.8%
92.6%
95.1% 97.0% 98.7%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
0
100
200
300
400
500
600
700
800
900
NumberofDefects
Types of Defects
Pareto Chart

20. Control Chart: Anthony Young Garments Ltd.
20
To find out the relative impacts of defects, control charts are drawn for each one. Among defects,
Uneven causes that the maximum number of production line (L-1, L-3 and L-4) out of control.
Fig. Control chart for Uneven
UCL 97.456
CL 72.000
LCL 46.544
11.5
31.5
51.5
71.5
91.5
111.5
131.5
151.5
171.5
191.5
L-1 L-2 L-3 L-4 L-5 L-6 L-7 L-8 L-9 L-10
NumberofDefects
No. of Line
Uneven

21. Cause-effect Diagram for Skip Stitch
21

22. Cause-effect diagram for Uneven
22

23. Suggested Solutions
23
Category Skip stitch Uneven Shading Oil Mark puckering
Man 1. Train unskilled
operator.
2. Maintain SOP.
3. Time study & Motion
study.
1. Train properly
2. Incentive
1. Supervision 1. Must stop
mishandling.
2. ‘5S’ should be
practiced.
1. Provide
adequate
training on
sewing.
Machine 1. Adjust timing
between needle &
looper.
2. Adjust fabric tension,
select good thread.
1. Automatic marker
lay.
2. No. of fabric plies
less than 300.
1. Clean machine at
least twice a day.
1. Must avoid high
tension in fabric.
2. Avoid rusty
eyelids and
thread guide.
Method 1. Adjust right thread
and needle size.
2. Follow SOP.
3. Reduce gap between
pressure foot and
needle plate.
1. Sewing speed must
be controlled.
2. Use checking
devices.
1. Set SOP
before
operation.
1. Keep workplace
neat and clean.
1. Set the right SPI.
2. Fix the right
pressure foot.
Material 1. Needle, thread and
fabric’s combination.
1. Ensure homogeneous
fabric.
1. Fabric
inspection.
1. Avoid twisted
thread.

24. Results
24
A Plus Industries Ltd.
• Sigma level For A Plus Industries Ltd. was 2.56.
• That means 1,45,261 defects per million opportunities.
• Major defect was Skip Stitch
Anthony Young Garments Ltd.
• Sigma level For Anthony Young Garments Ltd. was 2.34.
• That means 1,99,600 defects per million opportunities.
• Major defect was Uneven

25. Limitations & Future Scope
25
Limitations:
• Time consuming
• Data privacy
Future Scope:
• Growing awareness in small and medium manufacturing
industries.
• Much broader than other quality management programs
• It can be applied to every process of an organization.

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