Six Sigma DMAIC Methodology

Six Sigma is a systematic approach towards defects minimization through five phases of DMAIC methodology namely Define, Measure, Analyse, Improve and Control [1]. The Six Sigma DMAIC methodology is a process improvement methodology, which aims at reducing the number of possible defects in an organization, by letting the process operate at a 99% efficiency level [10].

After identifying the major defects, computer vision technology with artificial neural network have been applied on textured samples for developing automated defect detection and classification systems. Feature selection and image enhancement plays an important role in developing automated defect classification system. Image processing techniques deal with image acquisition,

Day by day it is becoming more difficult to trace all the defects at each level. There are many variable processes available at the spinning and fabric forming stages coupled with the complexities of the finishing and colouration processes to the production of a wide range of textile products [8]. In textile industry there have been an enlarge amount of losses due to the defects at each level of processing [9, 11] and these defects can harm the production cost

While identifying the defects in fabric during various stages it explores the use of DMAIC (define, measure, analyse, improve and control) methodology of six sigma in a garment factory to minimize the defect percentage. DMAIC methodology of six sigma is a problem solving method where six sigma tools are used to analyse the process data and finally the root causes behind the defects produce in the product are identified. Six Sigma is a quality improvement process of final product by reducing the defects, minimizing the variation and improving capability in the manufacturing process [2, 3]. The concept of implementing Six Sigma processes was pioneered at Motorola in the 1980s and the objective was to reduce the number of defects to as low as 3.4 parts per million opportunities [12]. Six Sigma, a statistically-based quality improvement program, helps to improve business processes by reducing the waste and costs related to poor quality, and by improving the efficiency and effectiveness of processes [13]. Ultimately these measures should lead to improved customer satisfaction and increased profitability