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Performance improvement of manufacturing industry by reducing the Defectives using Six Sigma Methodologies

Authors:
C.s. Chethan Kumar at RIT Visvesvaraya Technological University
C.s. Chethan Kumar
  • RIT Visvesvaraya Technological University
N V R Naidu
N V R Naidu
N V R Naidu
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Abstract

Studies have investigated how quality management can be employed in lean manufacturing to improve the performance of various issues in the whole business processes of various industries. This research work develops an application guideline for the assessment, improvement, and control of wastes in garment industry using six-sigma improvement methodology. Improvements in the quality of processes lead to cost reductions as well as service enhancements. An attempt is made to introduce and implement DMAIC methodology in Sun garment industry located in Coimbatore. Define Phase Research Case: As quality plays a pivotal role in all aspects of life, reducing the number of defectives in garment industry is an important function. Garment industries in India are facing stiff competition from Sri Lanka, Bangladesh and China. At this critical juncture, it is paramount for the manufacturers to reduce defects in their products and become competitive. Problem Statement: The garment industries are suffering from high rate of rejections of their products. Goal Statement : o To reduce the defect% to minimum level and thereby improve quality, reduce wastes and increase productivity Team : 3 members CTQ (Critical to Quality Characteristic) : Defective % of shirts SIPOC: The SIPOC Table.1.1 is developed to identify the requirements of the customers and other processes.
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Chethan Kumar C S, Dr. N V R Naidu, Dr. K Ravindranath/ IOSR Journal of Engineering
(IOSRJEN) www.iosrjen.org
Vol. 1, Issue 1, pp. 001-009
www.iosrjen.org 1 | P a g e
Performance improvement of manufacturing industry by reducing
the Defectives using Six Sigma Methodologies
Chethan Kumar C S1
1Assistant Professor, I.E.M Dept, M.S.R.I.T, Bangalore-560054
Dr. N V R Naidu2 Dr. K Ravindranath3
2HOD, I.E.M Dept, M.S.R.I.T, Bangalore-560054 3Principal, SVCE, Tirupati
Abstract:
Studies have investigated how quality management can be employed in lean manufacturing to improve the
performance of various issues in the whole business processes of various industries. This research work develops an
application guideline for the assessment, improvement, and control of wastes in garment industry using six-sigma
improvement methodology. Improvements in the quality of processes lead to cost reductions as well as service
enhancements. An attempt is made to introduce and implement DMAIC methodology in Sun garment industry
located in Coimbatore.
Define Phase
Research Case: As quality plays a pivotal role in all aspects of life, reducing the number of defectives in
garment industry is an important function. Garment industries in India are facing stiff competition from Sri
Lanka, Bangladesh and China. At this critical juncture, it is paramount for the manufacturers to reduce
defects in their products and become competitive.
Problem Statement: The garment industries are suffering from high rate of rejections of their products.
Goal Statement :
o To reduce the defect% to minimum level and thereby improve quality, reduce wastes and increase
productivity
Team : 3 members
CTQ (Critical to Quality Characteristic) : Defective % of shirts
SIPOC:
The SIPOC Table.1.1 is developed to identify the requirements of the customers and other processes.
Chethan Kumar C S, Dr. N V R Naidu, Dr. K Ravindranath/ IOSR Journal of Engineering
(IOSRJEN) www.iosrjen.org
Vol. 1, Issue 1, pp. 001-009
www.iosrjen.org 2 | P a g e
Table.1.1: SIPOC flow at Sun Garments
Measure Phase:
In this phase, after discussions with the managers and supervisors data is collected with the help of team members.
1. Data Collection Period
Table.1.2: Data collection period
2. The company manufactures variety of garment products like shirts, pants and Jackets. One product, i.e.,
Executive Shirt is inspected for defects since this was the critical product for the company as it had lot of
demand and the profit margin for this particular product is high. Table.1.3 indicates the total number of
shirts checked and the number of defectives.
Table.1.3: Inspection of Shirts.
Batch
Number
Checked
pieces
Defectives
1
237
15
2
525
23
3
626
33
4
757
26
5
754
35
6
807
38
7
1064
33
8
719
26
9
363
20
10
310
17
Supplier
Inputs
Process
Output
Madura
Coats
Unstitched
cloth.
Machinery
Threads
Needles
Cutting
Fabric
components
Stitching
Pressing
Packaging
Stitched shirt
Period
Variables (CTQ)
Responsibility
May-December
2009
Total Checked
Defectives
Team
Chethan Kumar C S, Dr. N V R Naidu, Dr. K Ravindranath/ IOSR Journal of Engineering
(IOSRJEN) www.iosrjen.org
Vol. 1, Issue 1, pp. 001-009
www.iosrjen.org 3 | P a g e
11
315
16
12
242
15
Total = 6719
Total = 297
3. Capability Study:
The analysis is carried out using MiniTab Software. The results are evident from the Figure.1.1
Sam ple
P r opo r tio n
121110987654321
0.075
0.050
0.025
0.000
_
P=0.04420
U C L=0.0 8384
LC L=0.00456
Sam ple
% Def ec tiv e
12108642
6.0
5.5
5.0
4.5
4.0
Summary Stats
0.00
PPM D ef: 44203
Lower C I: 39413
U pper C I: 49394
Process Z: 1.7 039
Lower C I:
(using 95.0% confidence)
1.6508
U pper C I: 1.7575
% De fectiv e: 4.42
Lower C I: 3.94
U pper C I: 4.94
Target:
Sam ple Siz e
% Def ec tiv e
900600300
8
6
4
2
6543210
3
2
1
0
Tar
Binomial Process Capability Analysis of NC
P Char t
Tests performed w ith unequal sam ple sizes
Cumula tiv e %D efe ctive
Ra te of Defecti ve s
Dist of % Def ect ive
Figure 1.1: Capability study
4. Analysis:
The outcome is given in the Table.1.4. Showing % defectives as 4.42.
Table 1.4: calculation of dpmo
Sl.No
Total Checked
6719
1
No. of
Defectives
297
2
% Defectives
4.42%
3
dpmo
44203.0064
4
Sigma
3.20
5
dpo
0.044203
Chethan Kumar C S, Dr. N V R Naidu, Dr. K Ravindranath/ IOSR Journal of Engineering
(IOSRJEN) www.iosrjen.org
Vol. 1, Issue 1, pp. 001-009
www.iosrjen.org 4 | P a g e
Analyze Phase
The past data was collected on the causes or type of defects and is given in Table 1.5
Table 1.5: Types of defects
Sl.No
DEFECTS
Occurrence
% Occurrence
1
UNEVEN
13
4.32%
2
RUNDOWN
64
21.26%
3
BROKEN
139
46.18%
4
CUFF UP& DOWN
16
5.32%
5
SIDE SEAM UNEVEN
5
1.66%
6
FRNT PLKT UP& DOWN
6
1.99%
7
WCL BTN MISS
13
4.32%
8
OPENSEAM
11
3.65%
9
BTN 2 HOLE
7
2.33%
10
RAW EDGE
12
3.99%
11
0THERS
15
5.0%
Total
301
The major causes or types of defects were identified through Pareto Chart
Count
Percent
DEFECTS
Count 6 5 15
Percent 46.2 21.3 5.3 4.3 4.3 4.0
139
3.7 2.3 2.0 1.7 5.0
Cum % 46.2 67.4 72.8 77.1
64
81.4 85.4 89.0 91.4 93.4 95.0 100.0
16 13 13 12 11 7
Other
SID
E SEAM UNEVEN
FRNT PLKT UP& DOWN
BTN 2 HOLE
OPENSEAM
RAW EDGE
WCL BTN MISS
UNEVEN
CUFF UP& DOWN
RUNDOWN
BROKEN
300
250
200
150
100
50
0
100
80
60
40
20
0
Pareto Chart of DEFECTS
Chethan Kumar C S, Dr. N V R Naidu, Dr. K Ravindranath/ IOSR Journal of Engineering
(IOSRJEN) www.iosrjen.org
Vol. 1, Issue 1, pp. 001-009
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Figure 1.2 Pareto chart for types of defect
The major defects from Pareto Chart is considered for analysis and the defects are listed in Table: 1.6.
Table.1.6: Major defects identified from Pareto chart
Through brainstorming with the shop supervisors, all potential causes were identified. The identified causes
are given in Figure 1.3 Cause & Effect diagram. Only the major types of defects are considered for the cause
and effect diagram
Broken
Run down
Cuff up and down
Uneven
Wcl Btn miss
Material Mix
Not following process instructions
Improper training to operators
outsourcing
Grouping of garment components Training not taken seriously
Product drawings not referred Improper quality check
Figure.1.3: Cause and Effect diagram
Sl.No
Defect Types
1
BROKEN
2
RUNDOWN
3
CUFF UP& DOWN
4
UNEVEN
5
WCL BTN MISS
Chethan Kumar C S, Dr. N V R Naidu, Dr. K Ravindranath/ IOSR Journal of Engineering
(IOSRJEN) www.iosrjen.org
Vol. 1, Issue 1, pp. 001-009
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Improve Phase
Through discussions with the managers and supervisors the following remedial actions were implemented for the
each cause which is indicated in the Table.1.7
Table.1.7: Defects and remedial actions
DEFECTS
Action
BROKEN
The broken threads are due to the fabric and the initial swatch test is tightened so
that wrong fabric does not roll out.
RUNDOWN
The stitches are extended than required and the operators are trained to control the
speed of the machine
CUFF UP& DOWN
The operators are compelled to refer to the drawings whenever they are stitching
Cuffs.
UNEVEN
The operators are trained to check for unevenness by using a sample fabric
pattern
BTN MISS
Operators are trained to check for the total number of buttons exhausted before
passing the product
Implementation
Based on the Cause and Effect diagram, the operators are trained in all aspects of their job and after the remedial
actions are taken, the products are checked for defects. The details are indicated in Table.1.8
Table.1.8: Number of defectives for each batch
After remedial actions are taken to reduce the defects, the results are encouraging as shown in the Table.1.9
Batch Number
Checked
Pieces
Defectives
% Defectives
1
243
4
1.65%
2
489
10
2.04%
3
655
11
1.68%
4
723
15
2.07%
5
769
17
2.21%
6
807
18
2.23%
7
932
15
1.61%
Chethan Kumar C S, Dr. N V R Naidu, Dr. K Ravindranath/ IOSR Journal of Engineering
(IOSRJEN) www.iosrjen.org
Vol. 1, Issue 1, pp. 001-009
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Table: 1.9: Types of defects and % Occurrence
DEFECTS
Occurrence
% Occurrence
UNEVEN
3
2.50%
RUNDOWN
15
12.50%
BROKEN
42
35.00%
CUFF UP& DOWN
7
5.83%
WCL BTN MISS
5
4.17%
Total
72
Capability Study: Based on the Data recorded the capability study is conducted and is as shown in the Figure. 1.4
Sam ple
P r opo r tio n
7654321
0.045
0.030
0.015
0.000
_
P=0.01949
U C L=0.0 3307
LC L=0.00590
Sam ple
% Def ec tiv e
7654321
2.50
2.25
2.00
1.75
1.50
Summary Stats
0.00
PPM D ef: 19489
Lower C I: 15700
U pper C I: 23902
Process Z: 2.0 644
Lower C I:
(using 95.0% confidence)
1.9791
U pper C I: 2.1520
% De fectiv e: 1.95
Lower C I: 1.57
U pper C I: 2.39
Target:
Sam ple Siz e
% Def ec tiv e
900600300
4
3
2
1
2.11.81.51.20.90.60.3-0.0
2.0
1.5
1.0
0.5
0.0
Tar
Binomial Process Capability Analysis of Defectives
P Char t
Tests performed w ith unequal sam ple sizes
Cumula tiv e %D efe ctive
Ra te of Defecti ve s
Dist of % Def ect ive
Figure.1.4: Capability Study after implementation
The results are indicating that the % defectives has been reduced to 1.95% as indicated in Table 1.10
Chethan Kumar C S, Dr. N V R Naidu, Dr. K Ravindranath/ IOSR Journal of Engineering
(IOSRJEN) www.iosrjen.org
Vol. 1, Issue 1, pp. 001-009
www.iosrjen.org 8 | P a g e
Table.1.10: calculation of dpmo
Total Checked
4618
No. of Defectives
90
% Defectives
1.95%
dpmo
19488.96
Sigma
3.56
Control Phase:
The positive results are discussed with the managers of the garment industry. The major defects are identified and
reduced. The real challenge is to sustain the improvements made in improving the process.
Control Plan: The following are the mandatory actions that has to be taken by the management to sustain
the results after lean sixsigma implementation.
The operators of garment industry must be given training on a continuous basis on the issue of
quality.
The drawings of the product must be made available at all the machines. The final garment pattern
should be referred by all the operators.
The management should give incentives for high quality performance.
The focus should be on preventing defects rather than correcting defects.
Tight quality controls should be enforced on those products coming from subcontractors.
Training the subcontractors on the importance of quality on continuous basis.
Conclusion:
The garment industry in focus was exporting the final product to European countries. It was operating at a
percentage defective of 4.42. After implementing the DMAIC methodology the percentage defective is reduced to
1.95. The same approach can be utilized to other products of the company which will reduce lots of defects. If the
quantum of defectives are reduced and converted into cash flows, the company will benefit through increased
revenues.
Many medium scale garment industries in India are not aware of the lean sixsigma concepts and this implementation
will trigger a positive wave across the garment industries and become more competitive.
Chethan Kumar C S, Dr. N V R Naidu, Dr. K Ravindranath/ IOSR Journal of Engineering
(IOSRJEN) www.iosrjen.org
Vol. 1, Issue 1, pp. 001-009
www.iosrjen.org 9 | P a g e
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[9] Kapuge, A.M. and M. Smith, (2007), “Management practices and performance reporting in the Sri Lankan
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[10] Karim, S. (2009), “The Impact of Just-in-Time Production Practices on Organizational Performance in the
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  • Apr 2021
In recent years, regenerative model pumps have become more interested in various commercial processes. Havells India Limited Produces regenerative water pumps which is mostly used in domestic application. Duration of assembly of regenerative water pump we found from the quality supervisors and production monthly data, a self-priming mono block regenerative pump (M1 model) have jamming issue. Due to this jamming of pump rejection is 20% of monthly production which is a major problem. For solving this problem, two techniques are used. The result of the project was to reduce the overall refusal rate in the production line from 20% to 2%, which enabled the production line to meet demand-using DMAIC. This analysis presents the current product improvement based on the DMAIC approach as a preferential method for defect identification and process improvement using various statistical tools such as the Cause and Effect Diagram.
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Network Meta-Analysis for Determining the Best Lean Tools Synergy to Improve Productivity by Reducing Rework in Garment Factories
Article
Full-text available
  • Mar 2024
The textile industry plays an important role in the global economy; however, it faces persistent challenges related to reducing rework for improving productivity. The purpose of this study is to summarize some scientific researches about production delay caused by rework in a clothing and accessory industry. It provides a general overview of the current state of knowledge concerning the interdependence between reduced productivity and rework rate. The research process is based on the Functional Analysis System Technique. It facilitates a systematic examination of sequential and logical steps necessary to achieve objective and attain outcomes. Functional Analysis System Techniques not only provides a structured methodology but also aids in identifying the successive functions crucial for attaining desired outcomes. The initial phase involves conducting a comprehensive systematic literature review focused on productivity issues stemming from rework within the textile industry. The first phase, related to the Seiri of the 5S methodology, involves conducting a comprehensive systematic literature review focused on productivity issues stemming from rework within the textile industry. Subsequently, the filling of a literature review synthesis matrix using Excel is conducted which represents Seiton. Next, focusing specifically on the Lean tools employed utilized and the corresponding productivity improvements, data are extracted. This corresponds to Seiso step. Following this, a Network Meta-Analysis is applied, representing the Seiketsu. Finally, the identification of the most effective Lean tools combination to reduce rework is undertaken, corresponding to Shitsuke. As results, the Ishikawa Diagram appears to have obtained the best ranking position according to the rankogram. Ishikawa Diagram is often associated with other tools to multiply its performance. The study's findings highlight that the Ishikawa, Pareto, Single-Minute Exchange of Die and Work Study combination emerges as the most effective approach for minimizing rework and enhancing productivity, as indicated by the League Table. This network meta-analysis provides a comprehensive overview of the Lean tools synergy effectiveness in rework reduction and productivity improvement strategies in textile industries. While powerful, Network Meta-Analysis has limitations including reliance on indirect comparisons from studies that may not directly compare all treatments, inheriting biases and complexities, which can pose challenges in assessing result certainty.
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Impact of JIT Production Practices on Organizational Performance: Factor Analysis Just In Time Production Practices in Garments and Textile Industries in Bangladesh: Factor Analysis of Some Selected Variables
Article
Full-text available
  • Nov 2019
Bangladesh has been endeavoring to industrialization. It faces manifold major problems, one of, those is how to control cost of production. Most of these costs as we know incur in the form of what is known as 'system losses' or non-value added activities. The industrial managers have been trying to implement modern tools and techniques that result in reduction of opportunities for errors, waste reduction and ultimately contribute in cost minimization and provide competitive advantages. Success of JIT system in the manufacturing environment has been documented by a large number of researchers. Much has been written regarding the positive strategic influence of JIT especially on the Japanese manufacturing sector and other developed countries like USA, UK, and Australia. However the implementation of quality management practices like JIT is yet to be explored in a developing country like Bangladesh. This paper emphasizes on the output of the factor analysis as a data reduction statistical tool and examines the interdependent relationships among variables with their underlying factors. The respondents' ratings of 78 statements were factor analyzed to determine the underlying factors for JIT supporting/facilitating variables. From factor analysis, 17 factors emerged from the present study. The study revealed that JIT supporting factors exist in the RMG and Textile industries in Bangladesh. Moreover, this smaller set of 17 factors can be used for further study in the same field.
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Lean or agile a solution for supply chain management in the textiles and clothing industry? International Journal of Operations and Production Management, 24(2), 151-170
Article
Full-text available
  • Feb 2004
  • INT J OPER PROD MAN
The textiles and apparel industry has been neglected in terms of supply chain management research. Recently, the industry has undergone a great deal of change, particularly with global sourcing and high levels of price competition. In addition, textiles and clothing has market characteristics, such as short product lifecycle, high volatility, low predictability, and a high level of impulse purchase, making such issues as quick response of paramount importance. This article discusses characteristics of the textiles and apparel industry and identifies the perspectives of lean, agile and leagility (a combination of these) within existing supply chain literature, which have been proffered as solutions to achieving quick response and reduced lead times. Through case studies of textile and apparel companies, different approaches to supply chain management are illustrated.
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Management Practices and Performance Reporting in the Sri Lankan Apparel Sector
Article
Full-text available
  • Mar 2007
  • Manag Audit J
Purpose An increasing number of organisations in developing countries are implementing management accounting innovations in order to generate improvements in accounting practices, which should ultimately impact on financial performance. This study aims to focus on the implementation of one such innovation, total quality management (TQM), among apparel companies in Sri Lanka, to determine the impact on business strategy, management practices and performance reporting. Design/methodology/approach A survey is conducted of Sri Lankan companies to identify differences in their management practices depending on whether or not they have implemented TQM. Findings The results demonstrate a significant difference in the business strategy implemented by the two groups, with those companies adopting TQM regarding quality as more important than cost efficiencies. Significant differences in both quality management practices and performance reporting systems were observed, except in the area of employee empowerment. Research limitations/implications The research is subject to the normal limitations of survey research, and its scope means that the findings may not be generalisable to industries other than garment manufacturing, or outside Sri Lanka. The findings should motivate comparative studies to determine the influence of both industry setting and national culture on the results. Practical implications The absence of employee empowerment is an important finding, with long‐term implications for the competitiveness of the Sri Lankan apparel industry, suggesting that corrective action is necessary. Originality/value The study is one of the few to examine improvements in organisational performance in developing countries.
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The Role of Quality Tools in Improving Satisfaction with Government
Article
  • Jan 2002
This article presents the results of a study in a city in the western United States. The authors found that city employees believed that quality knowledge was necessary for improving quality. Results show that departmental leadership was positively associated with teamwork, process improvement and employee satisfaction. Quality knowledge, if followed up with application, can he effective in improving processes. Leadership is necessary to the development of quality tools knowledge. Therefore, both leadership and teamwork are important contextual variables for quality improvement in the public sector.
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Management leadership and productivity improvement programs
Article
  • Dec 1999
  • Int J Appl Qual Manag
The intent of this empirical research is to identify the critical factors that are potentially fatal to productivity improvement programs and to analyze these factors relative to management leadership concepts. From this analysis we determine that these “fatal” factors can be prevented by the pre-existence of a leadership-based program that requires participative involvement of all members of an organization through good performance measurement and a sound reward system.
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Ask the Lean Manufacturing Experts Applying Lean in the Garment Industry
  • Jan 2008
  • G Mercado
Mercado, G. (2008). " Ask the Lean Manufacturing Experts Applying Lean in the Garment Industry", Thomas Publishing Company
Technology, Practices, and Competitiveness: The Primary Textiles Industry in Canada, China, and India
  • Jan 1998
  • P Chandra
Chandra, P., (1998),"Technology, Practices, and Competitiveness: The Primary Textiles Industry in Canada, China, and India", Himalaya Publishing House, Mumbai,.
Lean Six Sigma, Combining Six Sigma Quality with Lean speed
  • Jan 2002
  • M George
George, M., (2002) "Lean Six Sigma, Combining Six Sigma Quality with Lean speed", McGraw-Hill.