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Source: www.stitchworld.net March 2004 issue 1

Statistical Process Control (SPC) in ApparelManufacturing

Dr. Rajesh Bheda is a Professor at theGMT Department, NIFT, New Delhi,one of the worlds leading fashiontechnology institutes. His teaching,

consultancy and research interestsfocus on productivity improvement,quality management, and the socialissues in apparel manufacturing. He isa thought provoking speaker, writerand author. He has been addressinginternational conferences and hasconducted several managementdevelopment programmes for leadingapparel firms. He holds a Doctorate inManagement from the Faculty ofManagement Studies, University of

Delhi.

In the past decade, quality management practices in

the apparel industry have undergone a significantchange in the majority of factories in India. There isalso no doubt that the quality of apparel produced inthe country has improved significantly over a period oftime. However, in the light of the intense competitionfor a share of the global apparel market, it is notenough to say that our product quality level hasimproved over the past. It is also important to evaluatehow our quality level fares, compared to the bestapparel producers in the world. When such acomparison is made, one clearly realises that there isa long way to go and there is great scope forimprovement. One tool of quality management that iswidely used in other industries but is seldom used inthe apparel industry is Statistical Process Control,SPC. This article is intended to introduce the conceptof SPC and its application in the apparel industry.

What is SPC? Statistical Process Control (SPC) lays emphasis oncontrolling various processes in the manufacturingcycle. It reduces heavy dependence on postmanufacturing product inspection and

consistency of processes to produce acceptable products. SPC uses various charts that visuallycommunicate whether a process is performing under control or is out of control. This is achieved bydrawing a small sample from the output of critical processes at a fixed time interval and evaluatingthe output against given specifications. Any variation from the target value is noted and the same isdrawn in form of a line graph. These graphs have control limits drawn on them. If any observationgoes out of the control limit it can be said that the process is getting out of control and will not be ableto meet specified quality requirements. In such cases, a corrective action is initiated. If the results ofthe inspection show that the process is under control but there is a trend indicating that it is likely toget out of control in the future, then also corrective action is warranted.

Why SPC? SPC, developed by Dr.Walter A Shewhart of Bell Technologies in the second half of the 1920s, usesControl Charts for monitoring each process. By careful analysis of these charts, workers can detectand prevent many defects thus eliminating the need for mass inspection. Each worker can monitorhis or her process and make changes as needed. This method gives workers better control over theirprocess so that time, energy, and money can be saved by eliminating scrap. Because the workersare given more responsibility and power, they are likely to take greater pride in their work.The first large scale implementation of SPC in the apparel industry was carried out by Liz Claiborne


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Inc. Any discussion on the SPC implementation in apparel industry is incomplete without thereference to and learning from the Liz experience. Liz Claiborne started SPC implementation on apilot basis in 1997 with Sara International, a Miami, Florida based supplier, with factories inColumbia. As a result of the SPC implementation, the garment reject rate at Sara International'sfactories plummeted from over 20% in mid 1990's to 3% in 1997, below 2% in 1998 and to 0.4% inthe first half of 1999. Liz used this factory as a global showcase for SPC implementation and invited

its important vendors from across the globe to witness SPC in action. As a result of subsequent rollout of SPC implementation in Liz supplier factories across the globe, Liz Claiborne's failed shipmentindex dropped by 33% between 1996 and 1999.

STEPS FOR SPC IMPLEMENTATION

Step 1 Management Commitment: As SPC is uncommon in the apparel industry, it'simplementation is likely to face a lot of resistance within the organisation. For thisreason, it is important that the top management is completely convinced of itsimplementation and will support and ensure its implementation.

Step 2 SPC Briefing and Training: The quality manager, supervisors and operators/ inspectors on the critical operations will need to be exposed to the basic principlesof SPC and the methodology of SPC implementation.

Step 3 Identification of production line for pilot implementation and PreparatoryMeeting: This shall involve a meeting between Production Manager, Pattern Master

/ Technical Supervisors and Quality Manager / Supervisor. The objective of thismeeting is to identify critical operations of a garment style to be produced. Theseoperations, if not controlled, are likely to contribute to high rate of defects. Themeeting also focuses on how to minimise/ eliminate defects by process modificationand what type of control chart can be installed on these critical operations.

Step 4 Installation of Control Charts at the critical operations: This involved training theoperators/ inspectors at the critical operation on how to construct control charts andhow to interpret them. Once this is done the data for SPC should be collected atfixed interval, generally every 30 or 60 minutes, and the control charts should beconstructed

Step 6 Interpretation and corrective action: Installation of the control chart is not enough atit only tells you the status of the process. It's important to have procedures in placefor initiating corrective action should the process go out of control. The tools likecause and effect diagrams are quite useful for analysing the root causes of defectsand initiating a corrective action.

Step 7 Monitor the progress and review the improvement: It is expected that with thecontrol charts in pace and focus of the QA on eliminating the major causes of thedefects, the process is likely to get stabilised and the defect rate is likely to drop. It'simportant to monitor the progress and ensure that the implementation efforts do nothit roadblocks.


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In the processes / operations where the output is evaluated quantitatively, for example length, weightetc. (variable data) variable charts X and R as illustrated in table are used. So communicate andtrack measurements of a critical operation for example sleeve length, X and R charts can be used. Xchart shows the average of the sleeve placket length measurement for each sub-sample collectedevery hour, where as R chart shows range between the sleeve length measurement of the sub-sample.

In case of the operations where the output is evaluated for presence or absence of defects (attributedata) attribute charts (p, np, c) are used. For example for pressing operation p chart can be used.This chart communicates the fraction of defective products out of the total lot inspected. The np chartis used for tracking the total number of defective products in lots of fixed size. Assuming 10 garmentsare checked every hour and the total number of defective garments out of them are tracked then npchart will be useful. On the contrary, if a company is interested in tracking number of defects in agarment, c chart can be used.

SPC Implementation in the Indian apparel Industry

Most readers would have realised by now that SPC implementation in the Indian apparel industry isbroadly limited to the vendors of Liz Claiborne. The manufacturers that have implemented SPC havebenefited immensely and there is no reason why others cant emulate them. Though SPC may soundas a difficult to implement technique, two small projects carried out by GMT student teams illustratethat even with limited but focussed efforts, pilot implementation of SPC can be achieved andsubstantial results can be obtained. These two projects carried out at one of the largest Indianapparel exporters factories in 2002 and 2003 under my guidance produced encouraging results. The2002 project resulted in decrease in the averege percent defective rate in the sewing lines by 51%and increase in machine productivity by 32.7%. In 2003, SPC was implemented in multiple lines ofanother factory belonging to the same group. In this case, during post SPC implementation period,the % defective at the end of the line in the sewing stage reduced by almost 45%. The machineproductivity per shift improved to the tune of 23% to 47 %. Rejection % ranged between 2.2 % to 3.9%, whereas the average rejection % in the factory for the previous styles was around 5%.

33-37 statistical process control

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