Volume 23, Issue 3 (IJIEPR 2012)                   IJIEPR 2012, 23(3): 223-230 | Back to browse issues page

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Kabiri Naeini M, Owlia M S, Fallahnezhad M S. A Bayesian Approach for the Recognition of Control Chart Patterns. IJIEPR 2012; 23 (3) :223-230
URL: http://ijiepr.iust.ac.ir/article-1-301-en.html
A Bayesian Approach for the Recognition of Control Chart Patterns
Mehdi Kabiri Naeini1 , Mohammad Saleh Owlia 2, Mohammad Saber Fallahnezhad1
1- Yazd University
2- Yazd University , owliams@yazduni.ac.ir
Abstract:   (7072 Views)
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.
Keywords: Control Chart, Pattern Recognition, Bayes\' Rule, Maximum Likelihood Estimation
Full-Text [PDF 1255 kb]   (3718 Downloads)    
Type of Study: Research | Subject: Statistical Process Control Statistical Process Control or Quality Control
Received: 2011/09/5 | Accepted: 2014/07/21 | Published: 2014/07/21
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