a bayesian approach for the recognition of control chart patterns

Authors

mehdi kabiri naeini yazd

mohammad saleh owlia yazd

mohammad saber fallahnezhad yazd

abstract

in this research, an iterative approach is employed to recognize and classify control chart patterns. to do this, by taking new observations on the quality characteristic under consideration, the maximum likelihood estimator of pattern parameters is first obtained and then the probability of each pattern is determined. then using bayes’ rule, probabilities are updated recursively. finally, when one of the updated derived statistics falls outside the calculated control interval a pattern recognition signal is issued. the advantage of this approach comparing with other existing ccp recognition methods is that it has no need for training. simulation results show the effectiveness and accuracy of the new method to detect the abnormal patterns as well as satisfactory results in the estimation of pattern parameters.

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Journal title:
international journal of industrial engineering and productional research-

جلد ۲۳، شماره ۳، صفحات ۲۲۳-۲۳۰

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