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.
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1 April 1995
Research Article|
April 01 1995
A methodology of pattern recognition schemes for two variables in SPC
Wen‐Hai Chih;
Wen‐Hai Chih
Dai‐yeh Institute of Technology, Taiwan, Republic of China
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Dwayne A. Rollier
Dwayne A. Rollier
Arizona State University, Tempe, Arizona, USA
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Publisher: Emerald Publishing
Online ISSN: 1758-6682
Print ISSN: 0265-671X
© MCB UP Limited
1995
International Journal of Quality & Reliability Management (1995) 12 (3): 86–107.
Citation
Chih W, Rollier DA (1995), "A methodology of pattern recognition schemes for two variables in SPC". International Journal of Quality & Reliability Management, Vol. 12 No. 3 pp. 86–107, doi: https://doi.org/10.1108/02656719510084808
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