Process Capability Indices Based on the Highest Density Interval

被引:3
|
作者
Yang, Jun [1 ]
Gang, Tingting [1 ]
Cheng, Yuan [2 ]
Xie, Min [2 ]
机构
[1] Beihang Univ, Sch Reliabil & Syst Engn, Beijing 100191, Peoples R China
[2] City Univ Hong Kong, Dept Syst Engn & Engn Management, Hong Kong, Hong Kong, Peoples R China
关键词
process capability indices; non-normal processes; natural tolerance; highest density interval; asymmetric distribution; MULTIPLE CHARACTERISTICS; QUALITY CHARACTERISTICS; NONNORMAL PROCESSES; C-PK;
D O I
10.1002/qre.1665
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
For process capability indices (PCIs) of non-normal processes, the natural tolerance is defined as the difference between the 99.865 percentile and the 0.135 percentile of the process characteristic. However, some regions with relatively low probability density may still be included in this natural tolerance, while some regions with relatively high probability density may be excluded for asymmetric distributions. To take into account the asymmetry of process distributions and the asymmetry of tolerances from the viewpoint of probability density, the highest density interval is utilized to define the natural tolerance, and a family of new PCIs based on the highest density interval is proposed to ensure that regions with high probability density are included in the natural tolerance. Some properties of the proposed PCIs and two algorithms to compute the highest density interval are given. A real example is given to show the application of the proposed method. Copyright (C) 2014 John Wiley & Sons, Ltd.
引用
收藏
页码:1327 / 1335
页数:9
相关论文
共 50 条
  • [1] Interval estimation of process capability indices based on the quality data of supplied products
    Cui, Yanhe
    Yang, Jun
    Huang, Shuo
    [J]. 12TH INTERNATIONAL CONFERENCE ON RELIABILITY, MAINTAINABILITY, AND SAFETY (ICRMS 2018), 2018, : 400 - 404
  • [2] Large-sample interval estimators for process capability indices
    Nam, Kyung H.
    Kim, Dae Kyung
    Park, Dong Ho
    [J]. Quality Engineering, 2002, 14 (02) : 213 - 221
  • [3] Interval estimation of process capability indices based on the Weibull distributed quality data of supplier products
    Cui, Yanhe
    Yang, Jun
    [J]. 2018 5TH INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND THEIR APPLICATIONS (DSA), 2018, : 86 - 90
  • [4] Bootstrap Confidence Interval of the Difference Between Two Process Capability Indices
    L.I. Tong
    J.P. Chen
    [J]. The International Journal of Advanced Manufacturing Technology, 2003, 21 (4) : 249 - 256
  • [5] Bootstrap confidence interval of the difference between two process capability indices
    Chen, JP
    Tong, LI
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2003, 21 (04): : 249 - 256
  • [6] Probability-Based Process Capability Indices
    Khadse, K. G.
    Shinde, R. L.
    [J]. COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2009, 38 (04) : 884 - 904
  • [7] Multivariate Process Capability Indices of Sequence Process Based on Process Cost
    Liu Zhan-yu
    [J]. PROCEEDINGS OF 2009 INTERNATIONAL CONFERENCE OF MANAGEMENT SCIENCE AND INFORMATION SYSTEM, VOLS 1-4, 2009, : 652 - 655
  • [8] Generalized interval estimation of process capability indices for the Birnbaum-Saunders distribution
    Guo, Baocai
    He, Xixiang
    Xia, Qiming
    Sun, Yingying
    Xuan, Jie
    [J]. QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 2022, 38 (08) : 4015 - 4032
  • [9] Analyzing of process capability indices based on neutrosophic sets
    S Yalçın
    İ Kaya
    [J]. Computational and Applied Mathematics, 2022, 41
  • [10] Process Capability Indices Robust Based on Entropic Concepts
    Manzi, Joao
    Bispo, Heleno
    [J]. IFAC PAPERSONLINE, 2022, 55 (10): : 673 - 677