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Design of Rectifying Screening Inspections under a Bivariate Normal Distribution  

Hong, Sung-Hoon (Department of Industrial & Information Systems Engineering, Chonbuk National University)
Choi, Ik-Jun (Department of Industrial & Information Systems Engineering, Chonbuk National University)
Lee, Yoon-Dong (Applied Statistics, Konkuk University)
Lee, Min-Koo (Department of Information and Statistics, Chungnam National University)
Kwon, Hyuck-Moo (Department of Systems and Management Engineering, Pukyong National University)
Publication Information
Journal of Korean Society for Quality Management / v.35, no.4, 2007 , pp. 147-158 More about this Journal
Abstract
Owing to the rapid growth in automated manufacturing systems, screening inspection becomes an attractive practice for removing nonconforming items, and it has been suggested that inspection will essentially become an inherent part of modem manufacturing processes. In this paper, we propose rectifying screening inspections which allow quality practitioners to use performance and surrogate variables interchangeably in real-time applications. Two screening inspections are considered; a statistically-based screening inspection to reduce the current proportion of nonconforming items to a specified AOQ(average outgoing quality) after screening, and an economically-based screening inspection where the tolerance limit is determined so that the expected total cost is minimized. It is assumed that the performance variable and the surrogate variable are jointly normally distributed. For two screening inspections, methods of finding the optimal solutions are presented and numerical examples are also given.
Keywords
Quality Inspection; Performance Variable; Rectifying Screening Inspections; Surrogate Variable;
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