Knowledge-Based Statistical Process Control

Kenneth R. Anderson, David E. Coleman, C. Ray Hill, Andrew P. Jaworski, Patrick L. Love, Douglas A. Spindler, and Marwan Simaan

In this paper we discuss a set of software tools developed to support the tasks associated with managing special causes of variation in a manufacturing process. These tasks include the I detection of significant changes in process variables, a diagnosis of the causes of those changes, the discovery of new causes, the management of performance data, and the reporting of results. The software tools include automatic recognition of "out-of-control" features in critical process variables, rule-based diagnosis of special causes, a model-based search for symptoms where a diagnosis is not possible, and automated reporting aids. It is hoped that these tools will enhance the efficiency of special cause management.

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