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Knitwear Product Quality Analysis and Development of Spc Plan

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Knitwear Product Quality Analysis and Development of Spc Plan
KNITWEAR PRODUCT QUALITY ANALYSIS AND DEVELOPMENT OF SPC IMPLEMENTATION PLAN
Tajammal Hussain
Institute of Quality and Technology Management
University of the Punjab, Lahore
Phone:042-9230344
E-mail: mtqm32@yahoo.com
And
Muhammad Mohsin
Department of Mathematical Sciences
COMSATS Institute of Information Technology Defence Road, Off-Raiwind Road, Lahore.
Phone: 042-5321090-ext-233
E-mail: mohsinshahid@yahoo.com Abstract Statistical process control (SPC) is a powerful technique which knitwear industry can use in its pursuit of continuous effort to achieve sustainable and compatible garments quality at optimum cost reducing the magnitude of nonconforming garments in continuous mode of production.
In this paper scientific investigation highlights the need for implementation of SPC to knitwear industry by exploring the nature of defects, which cause cost of quality to raise an intolerable level taking away the competitive edge of industry from its competitors in international market. It is scientifically observed that these defects occurring in garments manufacturing, in some extent, are overlapping and these overlapping are highlighted in three major factors. Further, it illustrates some prerequisites to successful implementation of SPC and a comprehensive framework for the introduction and application of SPC program in knitwear industry, to control the over all process.

Key words. Statistical process control, quality, Factor Analysis, inspection and prevention models

1. Introduction
Pakistan Knitwear industry is renowned and poised for victory and rapid progress in the ever-hot competition international market, which is conceived and appreciated by the statistical facts and figures. Although, Being one of the largest cotton producer and very economical and easily available workforce, Pakistan has competitive advantage over rest of its rivals in international market that can lead it to excel the opportunities which are exposed by the



References: (i) Antony, J. (2000), "Ten key ingredients for making SPC successful in organizations", Measuring Business Excellence, Vol. 4 No. 4, pp. 7-11. (ii) Antony, J. and Kaye, M. (1999), Experimental Quality: A Strategic Approach to Achieve and Improve Quality, (iii) Bird, R (iv) Does, R.J.M.M. et al., (1997), "A framework for implementation of statistical process control International Journal of Quality Science, Vol. 2 No. 3, pp. 181-98. (v) Does, R.J.M.M. et al. (1999), Statistical Process Control in Industry, Kluwer Academic Publishers, Norwall, MA. (vi) Gaafar, L.K. and Keats, J.B. (1992), "Statistical process control: a guide for implementation", International Journal of Quality & Reliability Management, Vol. 9 No. 4, pp. 9-20. (vii) Goh, T.N. and Xie, M. (1998), "Prioritizing processes in initial implementation of SPC", IEEE Transactions on Engineering Management, Vol. 45 No. 1, pp. 66-71. (viii) Little, T.A. (2001), "10 requirements for effective process control: a case study", Quality Progressive. 34 No. 2, pp. 46-52. (ix) Mason, B. and Antony, J. (2000), "Statistical process control: an essential ingredient for improving service and manufacturing quality", Managing Service Quality, Vol. 10 No. 4,pp. 233-8. (x) Montgomery, D.C. (1991), Introduction to Statistical Quality Control, John Wiley & Sons, NewYork, NY. (xi) Oakland, J. (1999), Statistical Process Control, Butterworth-Heinemann, Oxford... (xii) Xie, M. and Goh, T.N. (1999), "Statistical techniques for quality", The TQM Magazine, Vol. 11 No. 4, pp. 238-41 Comparison of Originations Defect Categories

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