This document summarizes a case study conducted at a garment factory in Bangladesh called Vision Composite Knit Limited. The study aimed to minimize sewing defects in the factory's products using Six Sigma methodology. The measure phase found a defect rate of 12.61% originating mainly from the sewing section. Analysis identified the major defects and their causes. Improvements like training, equipment upgrades, and process changes were implemented. This reduced the defect rate to 7.7% and improved the factory's sigma level, showing the effectiveness of Six Sigma in minimizing defects and improving quality.

1. NATIONAL INSTITUTE OF FASHION TECHNOLOGY
2017
Corporate Restructuring
through Quality
Initiatives
Minimization of Sewing Defects in the RMG
Industry
Ajay Gayakwar
Bittu Singh
Radhe Kumar
Shubham Singh
DFT - V
G A N D H I N A G A R , G U J A R A T

2. 1. Introduction
The selected case study was conducted on a garment factory named “Vision Composite Knit
Limited” located at Savar, Dhaka. Quality improvement of products is vital to keep any RMG
factory in good health. Manufacturers now give more priority to reducing defects in their
products and become competitive. As the financial situation across the world is changing
rapidly, industries are now giving more focus on customer demand for superior quality
product, turnover and enhanced productivity.
2. Problem
In RMG industry; product quality, lead time and manufacturing costs are vital factors which
get hindered because of the defects in a product. Defect rate directly affects the profit
margin of the product and increases the Cost of Quality too. Defects play a vital role in the
productivity factor. If a defect is detected in the final inspection, the defective piece has
gone a long way. The cost of the production process for a defective garment is totally
wasted as the product cannot be sold anymore. Generally, defects usually come from the
fabric section, cutting section, sewing section or finishing section. Among those the sewing
section is the largest and most complex in operations.
3. Problem Identification
At first preliminary investigation was carried out at cutting, sewing, washing, finishing and
packing sections to identify the area where most of the defects are occurring. Secondary
data of the sewing section was collected from the management of the factory. Data sheets
were collected of the product for 3 months. So, the aim of the analysis was targeted
towards minimizing the defect percentage. It was found that the sewing section highly
suffered from defect and rework problem. 75% of the defects detected in the final
inspection were found to be originating from the Sewing section. Using the end line quality
data provided by the management, some repetitive defects that occur in the sewing section
were identified.
4. Objectives
a. To ensure quality of products by minimizing sewing defects
b. To identify major defects and their causes pertaining to sewing
c. To establish solutions for minimizing defects
d. To minimize non-productive activities such as re-work

3. 5. Mission
 To decrease the percentage of defect to lowest level, increase quality and
productivity and therefore reduce overall production costs
6. Quality tool applied : Six Sigma DMAIC methodology
a. Define phase – DMAIC stands for Define, Measure, Analyze, Improve & Control. It
defines the problems and the goals of the project. It also specifies processes which
need to be improved to achieve higher “Sigma level”.
Problem identified – Garment manufacturers experience high volume of rejections
of their products owing to defects.
Goal – To lower the defect percentage.
SIPOC process map – It shows output of the process of a factory upon which its
quality is judged. It includes Suppliers, Inputs, Process, Outputs and Customers.
Suppliers Inputs Process Outputs Customers
Altex fabric
Ltd.
Unstitched
cloth
Cutting T-Shirt C&A
Machinery Sewing Polo shirt Tesco
Thread Washing Pant Maskos
Fabian Group Needles Ironing
Button Finishing
Zipper Packaging
Label
SIPOC flow of the selected factory
b. Measure phase – In this phase, percentage of defects, frequency of defects, Defects
per Million Opportunity(DPMO) and Sigma level of the factory are calculated.

4. Total checked pieces 4670
No. of defectives 589
% Defectives 12.61
Defects per Opportunity(DPO) 0.126
DPMO 126124
Sigma level 2.64
Quality parameters prior to Six Sigma implementation
Defects Total occurrence % of occurrence
Broken stitch 137 23.26
Skip stitch 58 9.85
Down stitch 48 8.15
Raw edge 52 8.83
Joint stitch 41 6.96
Uneven stitch 51 8.66
Puckering 47 7.98
Hole/Damage 18 3.06
Spot/Oil stain 39 6.62
Reject 11 1.87
Slanted 9 1.53
Uncut thread 1 0.17
Size mistake 5 0.85
Process missing 47 7.98
Reverse 25 4.24
Total 589 100
Frequency of defects

5. Pareto chart – It is graphical representation of type of defects. The chart was derived
by MiniTab software which specializes in statistical consulting. The chart showed
that only 8 defects were responsible for around 81.7% of total defects percentage.
These 8 defects were :
 Broken stitch
 Skip stitch
 Raw edge
 Uneven, Up/Down
 Down stitch
 Process missing
 Puckering
 Joint stitch
c. Analyze phase – This phase is essential to search for solutions of the problems
identified in the previous phase.
Brainstorming - This problem solving tool helps to identify the issues, solutions and
opportunities. This session was carried out by the Round Robin method.

6. Attendant Numbers
Factory Manager 1
Sewing Floor Manager 1
Industrial Engineer 2
Growth, Production & Quality 2
End Line Quality Inspector 3
Line Supervisor 3
Sewing Machine Operator 5
Attendants at the Brainstorming session
Cause & Effect diagram – The potential causes are identified by inspections and
root-cause analysis in the previous stage itself.
d. Improve phase – This phase helps to derive solutions of the problems identified in
the previous stages. Potential solutions are worked out and put to test. The
implemented solutions are implemented and the results are evaluated. A pilot
implementation is conducted prior to full scale roll-out of the changes.

7. Areas Causes Suggested solutions
Man Carelessness Improve supervision
Inadequate training and
operator inefficiency
Train operators efficiently
Machine Machine is threaded
incorrectly or excessive
thread tension
Maintain proper thread
tension
Dull or bent sewing
machine needle and knife
Replace the needle and
knife with new ones
Excessive pressure on the
presser foot
Decrease the pressure on
presser foot
Method Incorrect size of the
needle and thread for
operation
Needle and thread sizes
should be synchronized
Incorrectly inserted
needle
Correct the needle
position
Comparatively long stitch
for type of fabric in work
Set stitch length according
to the type of fabric
Material Poor quality thread Use good quality thread
Poor quality needle Use good quality needles
Suggested solutions for all major defects with corresponding causes
Corrective actions Amounts
Replacement of dull or bent sewing
machine needles
18
Replacement of dull knives 8
Number of machines re-threaded 20
Correction of needle insertions 13
Replacement of faulty bobbins 3
Training provided 3 hours
Corrective actions and its amounts

8. e. Control phase – Once the solutions are implemented, the management took
cognizance of the positive output. The main defects are already known by this time
and can be reduced to an extent. Developing a defect control plan is easy as
compared to assure that the plan is always and continuously followed. For this
purpose, a control plan is prepared.
Control Plan :-
 Garment operators should be trained from time to time pertaining to issues
of quality.
 Good quality threads, needles and accessories must be used.
 Preventing defects should be the top priority rather than correcting them.
 Quality control should be strict in line.
 A well-planned Quality Management System should be developed by the
organization.
7. Impact
Parameters Before Quality tools
implementation
After implementing quality
tools
Total checked pieces 4670 6740
No. of defectives 589 519
% Defectives 12.61 7.7
DPO 0.126 0.077
DPMO 126124 77003
Sigma level 2.64 2.9255

9. 8. Conclusion
Rapidly changing conditions such as cut-throat competition, decreasing profit margins and
increasing customer expectations are continuously pushing the manufacturers to reduce the
production costs through improving quality. Minimization of defects results in reduced
production costs and better quality. Six Sigma is an efficient tool to analyse and address the
quality related problems as evident by the selected case study.