A methodology of pattern recognition schemes for two variables in SPC

Abstract

Prototype patterns and pattern diagnostic characteristics have been proposed in a previous article. Simulation results based on the prototypes and the diagnostic characteristics have also been presented as a justification for the study. Outlines a methodology, with three major components, which designates eight processors to identify the unnatural pattern. The working memory (blackboard) characterizes the symbolic structure of the transformed data and stores the intermediate results from each processor. Eight processors are the kernel of the knowledge base used to classify the pattern of the observations. The comparison of intermediate results is executed in the inference engine, which makes the preliminary decision. The implementation of the processors is coded in Turbo C and runs on an IBM PC/XT/AT or compatible PC. The results of the implementation and validation demonstrate that the methodology does a good job for two‐variable pattern recognition.