Properties of Textile Fibers

Application of Six Sigma in Garments units

Even if using Total Quality Management as the main quality program represents. Prevalent facts in nowadays industry, many companies are extending this kind of initiatives to incorporate strategic and financial issue. Among these initiatives, one such methodology is known as Six Sigma, which originated from the Motorola Corporation. The Six Sigma strategy involves extensive use of statistical techniques such as control charts, design of experiments, response surface methodology etc. in order to minimize process variations and product / service defects. These techniques need to be applied in a structured manner. While reporting the process improvement, Six Sigma teams use certain numeric values, known as Six Sigma Metrics. The most common metrics are 'Defects per Million Opportunities (DPMO)', 'Sigma Quality Level', and 'Yield'.

INTRODUCTION OF SIX SIGMA:

            Total Quality Management has become a buzzword in the business management field all over the world. Its philosophy and approach seem to have caught the imagination of organizational managers to find themselves in the midst of intense competition and are thus concerned with their survival. The concept however has not appeared overnight but has evolved over a period of time.

            Six sigma can be defined as “a Business process that allows organization to drastically improve the bottom line by designing and monitoring everyday business activities in ways that minimize waste and resources while increasing customers stratifications”. Sigma is a Greek letter used to represent standard deviation in statistics and six sigma stands for six standard deviations from mean. It provides the techniques and tools to improve the capability and reduce the defects in any process.

THE ORGIN OF SIX SIGMA:

            Six sigma was born in the 1980’s at Motorola. Bill smith, an engineer at Motorola’s communication sector, was quietly working began the scenes as studying the correlation between a product field life or reliability and how often that product had been repair to the manufacturing process, finally as a result of, Motorola began to improve the quality and simultaneously reduce th manufacturing cost and save the profit of $ 2.2 billion dollars within a 4 years.

SIX SIGMA PROCESS MODELS:

            Six sigma facilitated pro active approach through rigorous measurement. Although PDCA could be used for process improvement, to give a new thrust six sigma was introduced with modified models for process improvement. Some six sigma models are given bellow. For DMAIC is used to improving existing process and DMADV is used to employed the new products,

1.      DMAIC (Define, Measure, Analyze, Improve, Control)

2.      DMADV (Define, Measure, Analyze. Design, Verify)

1.   DMAIC:

                            I.            Define

            This is the first phase of the process improvement effort. It is similar to the plan phase of PDCA cycle. During this phase, the six sigma project is defined. During this phase plan for the garment production and collect the information pertaining to the customer requirements.

                         II.            Measure

            The team identifies the key internal processes that influence critical to quality (CTQ) and measure the garment defects.

                      III.            Analyze

            The team discovers the causes for defects, they identify the key variables which cause the defect or which are most likely to cost are create a process variations. For this purpose, cause and effect diagram can be used, that is shown in fig: 1,

           

                      IV.            Improve

            The team identifies maximum permissible ranges of the key variables and proposes a system for measuring deviations of the variables. The team modifies the process to stay within the maximum permissible range of the performance of the key variables. The process performance has to be monitored and measured. If it is satisfactory, then it can be institutionalized. The solution has to be   implemented on a pilot basis before large scale application in the plant.

                         V.            Control

            In this phase, tools are put in place to ensure that the key variables remain within the maximum permissible ranges continuously.

2. DMADV:

                                      I.            Define

            This phase is similar to DMAIC. Six sigma team gets a charter of new designs of garments.

                                   II.            Measure

            During this step, the organization may need to use Quality Function Deployment (QFD). It will enable the organization to convert the voice of customer prioritized technical requirements. Six sigma identifies measures for each of the technical requirements identify through Quality Function Deployment (QFD). They should also define the performance standards, i.e. the expected performance of the new process or products.

                                III.            Analyze

            In this phase the team has to be design the concepts or top level design for the new projects. They should generate various designs options. They should evaluate and finally select the right option.

                                IV.            Design

            This stage, the detailed design of the garments or process is carried out. Detailed design involved identifying the final details and identifying all the required steps. The six sigma team will evaluate available option before finalize the most suitable process methods. Finally it is the system integration that takes place.

                                   V.            Verify

            This is last steps in DMADV is verification. At this stage, the functionality of garments or process of the garment will be verified. The full scale verification of the design of the garment is verified.

IMPLEMENTING SIX SIGMA IN GARMENT MANUFACTURING:

            The prevailing motto for Six Sigma is “Perfection is Possible”. The subtitle would be “Even when things go wrong, the product is still good”. There are two major qualifiers to the concept of perfection. The major concept is that perfection specifically means that the product meets the customer's accurately determined specification. Therefore perfect production of a size “large” shirt, which has a specification of 42 inches ± ¾ inch, does not mean that all shirts produced measure 42” but rather that all shirts measure between 41 ¼ inches and 42 ¾ inches. The second major concept of Six Sigma is that the variation of the output is very slight. Thus, when size “large” shirts are produced the measurements of multiple shirts will be so closely gathered around 42 inches that when something goes wrong, such as bad cutting or a gauge being miss adjusted, the end result is that shirts still measure within the tolerance.

            The rest of the Six Sigma process understands the statistics behind the charts and controls, learning the methods to determine what is working properly, and how to identify and fix problems that do occur. The concept as a statistical term has been frequently used since the 1930's and gained popularity in Japan and the USA beginning in the 1950's with Crosby, Deming, and Juran. However, Motorola is credited, by most, for bringing the term to the general public in the 1980's. Oh yes, the statistical term. Six Sigma manufacturing says that the variation in the product is so slight that 99.73 % of the output falls within the tolerances. Actually, the quality is so good, and multiple measurements so closely centered on the specified number, that even when the measurement is off by three times the standard deviation, in either direction, it is still within tolerance. Thus the measurements fall within Six Sigma or six standard deviations of the mean and the quality yield is 99.73%.

            Controlling the change is often a matter of “What gets measured and posted is What Improves”. While computer programs can calculate the control limits required to know when a process is out of control, the limits have less value in an environment utilizing human operators. Manual calculations and charting will allow quick recognition of changes in the average apparel plant.

MESUREMENT OF ANALYTICAL PROCESSES IN SIX SIGMA:

            The measurement and analytical processes use tools and charts that are already available in many plants. These include some capabilities within basic spreadsheet computer programs such as Check Sheets, Histograms, Pareto Charts, and Scatter Diagrams. Flowcharts and Fishbone diagrams are easily drawn by hand.

            The actual analysis and improvements come through human interpretation of the information and a logical thought process. There are two areas within this section that can be greatly assisted by the newer computer programs available. The first item is the determination of whether changes observed are statistically relevant, thus avoiding unnecessary adjustments to an existing process. The second area, with less use in the apparel industry, is the Design of Experiments capability to see what combination of changes will give the best end result. Experienced and motivated people given the time for thought and experimentation are the critical resource for analysis and improvement. Controlling the change is often a matter of “What gets measured and posted is What Improves”. While computer programs can calculate the control limits required to know when a process is out of control, the limits have less value in an environment utilizing human operators. Manual calculations and charting will allow quick recognition of changes in the average apparel plant.

            Should a company have people certified as Green Belts or Black Belts? The answer is “YES, IF”. If the company needs the computer program, needs a show of management support for Quality Improvement, or lacks personnel with Engineering or Quality Management training.

            However, any company can reap significant financial benefits from a focused quality program utilizing the statistical tools that have been available for years. The requirement is to provide a motivated team of people with a structured process, an agreed upon set of standards, an expectation.

STATISTICAL PROCESS CONTROL:

       The first reports on statistical quality control of yarn manufacturing products appeared during the late 1940’s and 1950’s. These documents emphasized product quality and defect detection rather than defect prevention. At that time, quality assurance was very much a departmentalized function. Unfortunately for many companies in the textile industry, this condition still exists.

        In spun-yarn manufacturing, testing focused on three areas: end-product testing of characteristics such as linear density, twist, strength and elongation, short-term evenness, and count variation; inspection of defects such as thick and thin places, slubs and neps, and repeating faults like mechanical errors or drafting waves; and frequency checks for end breaks during spinning. In recent years, companies have begun to focus on electronic monitoring of processing weights, faults and running performance.

      However, one of the problems many companies using electronic monitoring and controls face is that the adjustments are made on predetermined target values rather than through statistical control limits. This often leads to far more variation when over control is added to the process.

CONCLUSION

            During implementation of six sigma is in garment manufacturing, we can reduce the garment cost, wastage in the garment and get higher production and good quality of the garment. Six Sigma initiatives aim at reduction of process variations and defects. Statistical process control (SPC) and Engineering process control (EPC) are two important techniques for achieving these goals.