Managing SPC, a Critical Quality System Element

Article

Shainin, Peter D.   (1992, ASQC)   Shainin Consultants, Inc., Mt. Vernon, WA 98273

Annual Quality Congress, Nashville TN    Vol. 46    No. 0
QICID: 9837    May 1992    pp. 251-257
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Article Abstract

Research shows that Statistical Process Control (using Shewhart, Moving Average and Range, CUSUM, or Multi-Vari charts) improves quality and productivity. To prepare and manage process control effectively, consider several factors.

Create thorough process control by using different charts to examine different process aspects. For example, Shewhart charts identify the changes in variation between specified control limits at a single station. Multi-Vari charts identify the causes of variation by examining the process across several stations. Identify the proper category of process (stable, drifting, uncontrollable) to control. Make decisions as close to the point of implementation as possible, and train the implementers to make those decisions correctly. For example, operators must have a clear goal, e.g. a parameter defined by a Tolerance Parallelogram. They must have or be taught a way to measure variance (e.g., Isoplot(TM)). They must have a way to adjust to correct for variance immediately, without contacting a superior. Be prepared to audit SPC directly, by performing periodic blind audits of the physical product -- on-paper tolerance reports are not enough.

Properly managed SPC results in true quality control, an informed and capable workforce, and an improved competitive position.

Keywords

Isoplot(TM),Multivariate control charts,Shewhart control chart,Statistical process control (SPC),Tolerances,Quality management (QM)


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