A conjugate bayesian approach for calculating process capability indices |
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| Authors: | Rui Miao Xinyi Zhang Dong Yang Yanzheng Zhao Zhibin Jiang |
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| Affiliation: | 1. School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, PR China;2. Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL 60607, USA;1. School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan, China;2. Pattern Recognition and Intelligent System Laboratory, Beijing University of Posts and Telecommunications, Beijing, China;3. School of Physical and Electronic Science, Shandong Normal University, Jinan, China;1. Faculty of Computer, Guangdong University of Technology, Guangzhou 510006, China;2. School of Engineering, University of Lincoln, Lincoln, Lincolnshire LN6 7TS, United Kingdom;3. Faculty of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China |
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| Abstract: | Process capability indices measure the ability of a production process to produce items within specification limits. The calculation of process capability indices has been focusing on using traditional frequency approach, which requires a large sample size for an accurate estimation. In order to eliminate this defect of traditional frequency approach on multi-batch and low volume production, Bayesian approach was used. The conjugate Bayesian approach is chosen to estimate the process distribution parameters. The algorithm with these conjugate Bayes estimators is proposed for measuring the process capability for multi-batch and low volume production. A case study is presented to demonstrate how the approach can be applied to actual data collected in practice. |
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