Abstract
Purpose
– This paper aims to propose a new approach to setting the control limits to promote the control performance of the cumulative count of conforming chart (CCC-r chart), in terms of the average number of items inspected (ANI).
Design/methodology/approach
– In contemporary high-yield manufacturing processes, the CCC-r chart is often an alternative of p charts or np charts for monitoring the fraction nonconforming (p). When a CCC-r chart is used, the traditional approach based on the equal-tail probabilities to setting control limits demonstrates a poor performance in terms of ANI as p deviates upward from its nominal value p
0. To improve the performance of CCC-r charts, this research uses a search method based on some analytical results to find the control limits such that the in-control ANI (ANI
0) is near-maximal and near-unbiased.
Findings
– Analytical validation confirms that the proposed approach outperforms the traditional one in terms of the maximum and the unbiasedness of ANI
0. When p
0 is not given, simulation results show that the minimum-variance unbiased estimator tends to perform better than the maximum likelihood estimator.
Originality/value
– This study numerically shows that the use of the proposed approach achieves the goal of the near-maximal and near-unbiased ANI
0, and hence improves the performance of CCC-r charts. In addition, because the proposed approach is computational intensive, this study also develops a Visual Basic project to help practitioners obtain the control limits using the proposed approach.
Subject
Strategy and Management,General Business, Management and Accounting
Cited by
12 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献