Special cause management: A knowledge-based approach to statistical process control

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 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.