Control chart for monitoring the Weibull shape parameter under two competing risks

被引:8
作者
Haghighi, Firoozeh [1 ,2 ]
Castagliola, Philippe [3 ]
机构
[1] Univ Tehran, Coll Sci, Sch Math Stat & Comp Sci, Tehran, Iran
[2] IRCCyN UMR CNRS, Nantes, France
[3] Univ Nantes, UMR 6004, LS2N, Nantes, France
关键词
Censoring; Competing risks; Complete-data likelihood; Conditional expected values; Control chart; EM algorithm; Masked data; Missing; Weibull distribution;
D O I
10.1080/03610918.2018.1433845
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In this paper, we propose a control chart to monitor the Weibull shape parameter where the observations are censored due to competing risks. We assume that the failure occurs due to two competing risks that are independent and follow Weibull distribution with different shape and scale parameters. The control charts are proposed to monitor one or both of the shape parameters of competing risk distributions and established based on the conditional expected values. The proposed control chart for both shape parameters is used in certain situations and allows to monitor both shape parameters in only one chart. The control limits depend on the sample size, number of failures due to each risk and the desired stable average run length (ARL). We also consider the estimation problem of the target parameters when the Phase I sample is incomplete. We assumed that some of the products that fail during the life testing have a cause of failure that is only known to belong to a certain subset of all possible failures. This case is known as masking. In the presence of masking, the expectation-maximization (EM) algorithm is proposed to estimate the parameters. For both cases, with and without masking, the behaviour of ARLs of charts is studied through the numerical methods. The influence of masking on the performance of proposed charts is also studied through a simulation study. An example illustrates the applicability of the proposed charts.
引用
收藏
页码:2125 / 2137
页数:13
相关论文
共 50 条
  • [41] Bayesian censored sequential reliability demonstration testing for two-parameter Weibull distribution with known shape
    Zhou, TG
    Hao, Q
    Sha, DG
    PROCEEDINGS OF THE SECOND INTERNATIONAL SYMPOSIUM ON INSTRUMENTATION SCIENCE AND TECHNOLOGY, VOL 3, 2002, : 134 - 138
  • [42] Exact Inference for an Exponential Parameter under Generalized Adaptive Progressive Hybrid Censored Competing Risks Data
    Cho, Youngseuk
    Lee, Kyeongjun
    SYMMETRY-BASEL, 2020, 12 (12): : 1 - 17
  • [43] Asymmetric Control Limits for Weighted-Variance Mean Control Chart with Different Scale Estimators under Weibull Distributed Process
    Zhou, Jing Jia
    Ng, Kok Haur
    Ng, Kooi Huat
    Peiris, Shelton
    Koh, You Beng
    MATHEMATICS, 2022, 10 (22)
  • [44] Private health investments under competing risks: Evidence from malaria control in Senegal
    Rossi, Pauline
    Villar, Paola
    JOURNAL OF HEALTH ECONOMICS, 2020, 73
  • [45] A mixed control chart for monitoring failure times under accelerated hybrid censoring
    Aslam, Muhammad
    Raza, Muhammad Ali
    Sherwani, Rehan Ahmad Khan
    Farooq, Muhammad
    Jeong, Jun Yong
    Jun, Chi-Hyuck
    JOURNAL OF APPLIED STATISTICS, 2021, 48 (01) : 138 - 153
  • [46] A median loss control chart for monitoring quality loss under skewed distributions
    Yang, Su-Fen
    Zhou, Ruoyu
    Lu, Shan-Wen
    JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2017, 87 (17) : 3241 - 3260
  • [47] Consistency of the MLE under a two-parameter Gamma mixture model with a structural shape parameter
    He, Mingxing
    Chen, Jiahua
    METRIKA, 2022, 85 (08) : 951 - 975
  • [48] Consistency of the MLE under a two-parameter Gamma mixture model with a structural shape parameter
    Mingxing He
    Jiahua Chen
    Metrika, 2022, 85 : 951 - 975
  • [49] E-Bayesian Estimation for the Weibull Distribution under Adaptive Type-I Progressive Hybrid Censored Competing Risks Data
    Okasha, Hassan
    Mustafa, Abdelfattah
    ENTROPY, 2020, 22 (08)
  • [50] Improved adaptive CUSUM control chart for industrial process monitoring under measurement error
    Abdullah Ali H. Ahmadini
    Imad Khan
    Shokrya Saleh A. Alshqaq
    Hadeel AlQadi
    Refka Ghodhbani
    Bakhtiyar Ahmad
    Scientific Reports, 15 (1)