A conjugate bayesian approach for calculating process capability indices

被引:22
|
作者
Miao, Rui [1 ]
Zhang, Xinyi [1 ]
Yang, Dong [1 ]
Zhao, Yanzheng [1 ]
Jiang, Zhibin [1 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Mech Engn, Shanghai 200240, Peoples R China
关键词
Process capability indices; Bayesian estimation; Conjugate prior; Multi-batch and low volume production; DISTRIBUTIONAL PROPERTIES; MULTIPLE SAMPLES; SUBSAMPLES;
D O I
10.1016/j.eswa.2010.12.151
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:8099 / 8104
页数:6
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