Six Sigma and Application of Six Sigma in Garment Industry

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SIX SIGMA AND APPLICATION OF SIXSIGMA IN GARMENT INDUSTRY TO IMPROVE THE ACCEPTANCE LEVEL

P.SENTHILKUMAAR

ABSTRACT

In this paper I am going to present you about the six sigma, its origination, basics, about six sigma, and the application of six sigma to improve the acceptance level in garment industry. And also various bottlenecks in the implementation of six sigma in garment industry will be discussed.

KEYWORDS
DMAIC, VOC, SPC, CTQ, TQM, DFSS, DPMO, BLACK BELTS, MASTER BLACK BELTS, GREENBELTS.

INTRODUCTION

SIX SIGMA: THE BASICS & ORIGINATION

Six Sigma is a revolutionary business process geared toward dramatically reducing organizational inefficiencies that translates into bottom-line profitability. It started in the 1980s at Motorola; then, organizations such as GE, Allied Signal, and Motorola; then, organizations such as GE, Allied Signal, and Seagate worked with the initiative during the 1990s and made it the most successful business initiative of the era. Motorola Allied Signal General Electric Philips Sony, Toshiba… 1987 1994 1996 2000

Key to the Six Sigma methodology of the 1990s is a five step process—Define, Measure, Analyze, Improve and Control.
SIX SIGMA DEFINED AND EXPLAINED

The basis of Six Sigma is measuring a process in terms of defects. The statistical concept of six sigma means processes are working nearly perfectly, delivering only 3.4 defects per million opportunities (DPMO). Sigma (the Greek letter ) is a statistical term that measures standard deviation. In the context of management, it’s used to measure defects in the outputs of a process and show how far the process deviates from perfection. A one-sigma process produces 691462.5 defects per million opportunities, which translates to a percentage of satisfactory outputs of only 30.854%. That’s obviously really poor performance.

If we have processes functioning at a three sigma level, this means we’re producing 66807.2 errors per million opportunities- .
STANDARD DEVIATION (SD)
A measure of the spread of data points in relation to the mean. It’s the most common measure of variation in a set of data. EXAMPLE FOR SD CALCULATION
Observations - 5, 23, 32, 10,130
Mean (Average) = 5+23+32+10+130/5 = 40
Variance
I) (5-40)2, (23-40)2, (32-40)2, (10-40) 2, (130-40)2

II) 1225, 289,64,900,8100

III) 1225+289+64+900+8100/5 = 2115.6
SD
(2115.6) 1/2 = 45.99
DEFECT A measurable characteristic of the process or its output that is not within the acceptable customer limits, i.e., not conforming to Specifications. The sigma level of a process is calculated in terms of defects per million opportunities (DPMO).

Most organizations are operating at three to four sigma quality levels. That means they could be losing up to25% of their total revenue due to processes that deliver too many...
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