Asst. Professor, NIFT, New Delhi

ABSTRACT

Sigma is a highly disciplined process that helps us focus on developing and delivering near-perfect products and services. The word is a statistical term that measures how far a given process deviates from perfection. The central idea behind Six Sigma is that it Six Sigma is a disciplined, data-driven approach and methodology for eliminating defects (driving towards six standard deviations between the mean and the nearest specification limit) in any process from manufacturing to transactional and from product to service. To achieve Six Sigma Quality, a process must produce no more than 3.4 defects per million opportunities. An 'opportunity' is defined as a chance for nonconformance, or not meeting the required specifications. This means we need to be nearly flawless in executing our key processes."

The paper tries to introduce the concept of Six Sigma for the Apparel Industry. Various tools can be applied under Six Sigma concept for measuring and analysis of variations in a process. DMAIC is practiced in the garment manufacturing industry and problem is identified on car seat manufacturing It is observed that the factor was working at 2.58 sigma level. After implementation of six sigma process, it is found that, the process improved to 3.16 sigma level. It clearly shows the way and scope for the further improvement of the same process indicating the flaw in the process. For pointing out the priority of the problems, FMEA tool was used.
Keywords: DMAIC, Process Improvement, Six Sigma, FMEA

Introduction:

Six Sigma is a proven method for improving profits by pursuing perfection. Six Sigma, or 6s, is a disciplined use of applied science that improves profits by creating and systematically replicating breakthrough improvements.

A 6s Expert, called a Black Belt, can be expected to lead three to four projects per year. Their success, and your businesses success with 6s, depends on the commitment of top-level executive leaders for achieving perfect, 6s quality.

So, Six Sigma is a business improvement methodology that focuses an organization on:

• Understanding and managing customer requirements
• Aligning key business processes to achieve those requirements
• Utilizing rigorous data analysis to minimize variation in those processes
• Driving rapid and sustainable improvement to business processes.

For non-Six Sigma companies, these costs are often extremely high. Companies operating at three or four sigma typically spend between 25 and 40 percent of their revenues fixing problems. This is known as the cost of quality, or more accurately the cost of poor quality. Companies operating at Six Sigma typically spend less than 5 percent of their revenues fixing problems.


Literature Review: History of Six sigma

Motorola® Allied Signal® General Electric® Philips® Sony, Toshiba…
1987 1994 1996 1996 2000
(Strength In Mfg) (Linked to Financial Results) (Linked to Design & Service) (Linked to Sales & Product commercialisation)  

Since 2001, large number of Organisations globally have taken up the initiave and got benefit out of it.

Six Sigma:

Six Sigma is a disciplined, data driven approach and methodology for eliminating defects (driving towards six standard deviations between the mean and the nearest specification limit) in any process -- from manufacturing to transactional and from product to service.

The statistical representation of Six Sigma describes quantitatively how a process is performing. To achieve Six Sigma, a process must not produce more than 3.4 defects per million opportunities. A Six Sigma defect is defined as anything outside of customer specifications. Six Sigma is a statistical unit of measure which reflects process capability. The sigma scale measure is perfectly correlated to such characteristics as defects per unit, parts per million defective and the probability of a failure/error.

The lower case Greek letter, s, is pronounced sigma. In Six Sigma science, s is the symbol for a statistical measure called the standard deviation. This measure helps describe the shape of a bell curve like the one on this book’s cover. When one knows the average ( X ) and standard deviation (s) of a process, one can improve that process to near perfection.


Six Sigma quality reduces variation. A Six Sigma bell curve covers 99.999% of a given process’s outcomes. The graphic effect of a smaller standard deviation, s, is illustrated on the left. The bell curve shrinks so only 3-4 defects per million (DPM), can occur.

Research Methodology:

A garment production process faces numerous kinds of problems leading to quality defects and subsequent alterations and rejections of the product. The implementation or application of Six Sigma starts with the recognition of a problem, and the defining of a project to cure or alleviate that problem. DMAIC methods can be used for the improvement of Structured and Repeated process, Focus on defects reduction and Existing product and process improvement.

DMAIC, which stands for Define, Measure, Analyze, Improve and Control. These are defined further as:

DEFINE: This phase involves the definition of the project/assignment, using process map, application area, desired improvement, likely benefits, etc. The importance lies in having the chance of any of the following factors such as

• Revenue Growth
• Cost Reduction’
• Capital Reduction
• Key Business Objectives
• On Time Delivery
• Lead Time
• Quality
• Customer Satisfaction


MEASURE: This phase involves the analysis of the process to determine its present state and the future, as obtained. Data collection is the main emphasis of this phase and Evaluating the measurement system to ensure the reliability of data.

Measurement is a means of communication. Six Sigma is largely the applied science of measurement. Knowing how to measure, when to measure, what to measure, and how to record measurements for maximum value are essential 6s skills. Measurement skills depend on measurement knowledge.

COPQ : Cost of Poor Quality (Prevention Cost, Failure Cost etc)
RTY : Roplled Throughput Yield
DPU : Defects per Unit
DPMO : Defects per million Opportunities
Process capability Index
Sigma Level


Data needs to be recorded sequentially. Accounting and finance people call this technique a time series. Whenever one collects data, either by counting or measuring, record 100% of the data in sequential order. The process flow diagram describes an efficient, economical, and thorough path towards six sigma improvements. This process has repeatedly demonstrated its capacity for productivity, quality, information and breakthrough improvements.

ANALYSE: This phase involves the data analysis for identification of parts of process which affect the quality of the problem. There are a number of statistical tools available such as Hypothesis Testing, Regression Analysis and historical Design of PFMEA, Box Plot,t test, ANOVA, Correlation, Regression.

IMPROVE: This phase adds to the process to find a permanent solution to the problem. This may involve better forecasting, better scheduling, better procedures or equipment.

CONTROL: This phase involves the process of establish ongoing process controls to avoid the problem recurring by implementing Control Charts, assigning clear process ownership and documenting the improved workflow which used to solving the problem by putting in the right procedures and management statistics.

Case Study 1:

• Define : Annual customer complaints were well over 10%
• Measure: Major faults that occurred in Final product were analysed by using Histogram for prioritization.

Defects per unit (DPU) = total defects/total units
Defects per million opportunities = DPU X 1,000,000
Or, DPMO = (total defects/total opportunities) X 1,000,000
Defects% =(total defects/total opportunities) X 100
Yield% = 100 – (defects%)
Process Sigma =NORMSINV[1–total defects /total opportunities )] +1.5

• Analyse : PFMEA tool was used to find out the RPN value and action taken accordingly.It is a systematic analysis of potential failure modes aimed at preventing failures or errors.

An PFMEA is a two-phase process

- First the potential failure modes and corrective actions are identified.
- Then after the corrective actions are implemented, process is re-
evaluated to determine if the result is acceptable.

Improve:

Various suggestions for improvements were given. Some of the major ones were:

1. Proper Training was imparted to the Quality Inspector
2. Quality Awareness Program was conducted for Operators and Checkers
3. A suitable Quality Manual was prepared for the unit
4. Work Instructions were developed and issued to each of the departments
5. “Quality Defects Identifiable Boards” were put up across the departments

  • Introduction of Quality Checking Systems or Formats and constant monitoring by a trained Quality Inspector has brought about drastic reduction in quality defects level.

  • There is a significant decrease in Defects Per Million Opportunities (DPMO) in both Jacquard (65.5% reduction) seat covers before and after quality system implementation.

  • The Process Sigma level has also improved for both the product types. In percentage terms, there is a jump in Process Sigma level by 22.48% in Jacquard product.

  • Estimated increased sale in Jacquard is Rs. 5,31,028/- per month.

  • It can be aptly stated that this kind of a change is evident only after establishing foolproof measures to check quality and by creating its awareness among the middle management, workers and checkers.

• Control : Create control Chart and control plan


Case Study 2 Related to HR:

Define : Rate of attrition had increased substantially in the last two quarters in
the four levels of their employees.
Measure : Collection of Data and finding the sigma level. Map the process and
create C&E diagram.
Analyse : Conduct the Hypothesis Testing and List the Vital x
Improve : Execute and Standardize the process (get approvals, impart training)

• HR decided to reduce the promotion period of level 1 to level 2 from an average of 2 years to 1.5 years as maximum resignations occurred during the initial years of service. Policy was made and approved from the management.
• HR started conducting awareness programs on the growth prospects an employee could expect in the organization and comparison with the competitors.
• HR created policies for the employees in consultation with the management to
• Identify new growth opportunities,
• Give additional responsibilities and rewards henceforth,
• Encourage inter- departmental transfers through internal job postings,
• And Promote up-gradation of skills through training.
• HR restructured the compensation for the next Performance review in Sept, 04 which rationalized the % compensation for all levels as per the benchmark industry.
• First, each individual was made to list down his job responsibilities. Then, HR interviewed the middle/ upper management to gauge non-uniformity in work load. Next, the managers were asked to uniformly distribute the work load amongst the employees.
• A new communication system was installed using which employees could attend conference calls from home to avoid night stays.
• HR was made responsible to solve each of the raised issues from the interactions and monitor the proposals regularly.

Control : Create control Chart and control plan

Conclusion:

Six Sigma, however, has its strengths in more complex situations where the relationship between causes and the problem may be unknown and where more profound data analysis is required to identify the true causes of variation. Six Sigma is able to identify and validate root causes from a huge amount of data and deliver the right information to make better business decisions based on facts rather than gut feel.
It has to incorporate all the resources and services in the most effective manner and be sustained until the continuous improvement is inculcated in the workforce.

The cases discussed in this paper not only clearly show the massive improvement potential available to the industry, but also resulted in substantial gains for the specific apparel manufacturers. Industry can take inspiration to implement the strategy for the better working environment of the industry.

References:

1. Executive Six Sigma, Slogan Consulting on Health Systems of America,Inc 2002.
2. Six Sigma or Lean, Dirk Roettges, venturehaus Consulting Limited, London.
3. U. Dinesh Kumar, David Nowicki, Jose´ Emmanuel Ramı´ rez-Marquez, Dinesh Verma, “On the optimal selection of process alternatives in a Six Sigma implementation”, from http://www.elsevier.com/locate/ijpe.htm
4. Thomas Pyzdek, The Six Sigma Revolution, from http://www.qualityamerica.Com/QPProducts/6Sigma.html
5. David L Stymiest, Analyse This – Applying Six Sigma to Facilities Maintenance, from http://www.hfmmagazine.com
6. Quality Network – Failure Mode & Effect Analysis, retrieved on 06/04/07 from http://www.national.com/quality/fmea.html
7. http://www.isixsigma.com
8. www.sixsigmatutorial.com
9. www.sixsigmamk.com
10. www.softwaresixsigma.com


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