标题: A Bayesian approach for assessing process precision based on multiple samples
作者: Pearn, WL
Wu, CW
工業工程與管理學系
Department of Industrial Engineering and Management
关键字: process capability indices;Bayesian approach;credible interval;posterior probability;decision making;quality control
公开日期: 16-九月-2005
摘要: Using process capability indices to quantify manufacturing process precision (consistency) and performance, is an essential part of implementing any quality improvement program. Most research works for testing the capability indices have focused on using the traditional distribution frequency approaches. Cheng and Spiring [IIE Trans. 21 (1) 97) proposed a Bayesian procedure for assessing process capability index C-P based on one single sample. In practice, manufacturing information regarding product quality characteristic is often derived from multiple samples, particularly, when a routine-based quality control plan is implemented for monitoring process stability. In this paper, we consider estimating and testing C-P with multiple samples using Bayesian approach, and propose accordingly a Bayesian procedure for capability testing. The posterior probability, p, for which the process under investigation is capable, is derived. The credible interval, a Bayesian analogue of the classical lower confidence interval, is obtained. The results obtained in this paper, are generalizations of those obtained in Cheng and Spiring [IIE Trans. 21 (1), 97]. Practitioners can use the proposed procedure to Cheng and Spiring determine whether their manufacturing processes are capable of reproducing products satisfying the preset precision requirement. (c) 2004 Elsevier B.V. All rights reserved.
URI: http://dx.doi.org/10.1016/j.ejor.2004.02.009
http://hdl.handle.net/11536/13263
ISSN: 0377-2217
DOI: 10.1016/j.ejor.2004.02.009
期刊: EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volume: 165
Issue: 3
起始页: 685
结束页: 695
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