A new multiple dependent state sampling plan based on one-sided process capability indices
被引:0
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作者:
Ching-Ho Yen
论文数: 0引用数: 0
h-index: 0
机构:Huafan University,Department of Technology for Smart Living
Ching-Ho Yen
Chia-Hao Chang
论文数: 0引用数: 0
h-index: 0
机构:Huafan University,Department of Technology for Smart Living
Chia-Hao Chang
Chun-Chia Lee
论文数: 0引用数: 0
h-index: 0
机构:Huafan University,Department of Technology for Smart Living
Chun-Chia Lee
机构:
[1] Huafan University,Department of Technology for Smart Living
[2] Chang Gung Institute of Technology,Department of Nursing
[3] Minnan Normal University,School of Business
来源:
The International Journal of Advanced Manufacturing Technology
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2023年
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126卷
关键词:
Process capability indices;
Repetitive sampling;
Multiple dependent state;
Average sample number;
Operating characteristic curve;
D O I:
暂无
中图分类号:
学科分类号:
摘要:
Process capability indices (PCIs) are effective quality tools for evaluating process performance in the manufacturing industry. Over a period of more than 15 years, sampling plans based on PCIs have been developed for lot sentencing. Sampling plans that involve repetitive sampling or multiple dependent (deferred) state sampling achieve significant sample size reductions relative to sampling plans that involve single sampling. In this study, we combine the concepts of repetitive and multiple dependent state sampling to propose a new variable sampling plan based on one-sided PCIs. The proposed sampling plan minimizes the average sample number while satisfying the principle of two points on the operating characteristic curve. To demonstrate the performance of the proposed sampling plan, a comparison with existing homogeneous sampling plans is performed.
机构:
Laboratory of Applied Mathematics, CNRS UMR 5142 IUT de Bayonne, Université de Pau et des Pays de l'Adour, 17 place Paul Bert, 64100 Bayonne, FranceLaboratory of Applied Mathematics, CNRS UMR 5142 IUT de Bayonne, Université de Pau et des Pays de l'Adour, 17 place Paul Bert, 64100 Bayonne, France