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    题名: Model selection methods for reliability assessment based on interval-censored field failure samples
    作者: Tsai, Tzong-Ru;Wu, Sih-Hua;Shen, Yan
    关键词: Akaike information criterion;Bayesian information criterion;field failure data;location-scale family;maximum likelihood estimation
    日期: 2020-06-13
    上传时间: 2020-07-09 12:10:26 (UTC+8)
    出版者: World Scientific Publishing Co. Pte. Ltd.
    摘要: Incomplete field failure data from automated production are often applied for evaluating the system reliability. But the evaluation could be impacted by the uncertainty of the product’s lifetime distribution, which is usually predetermined but may be misspecified. In this paper, we assume that the system lifetime distribution follows a location-scale family with several candidates instead of a certain distribution. Two model selection procedures are proposed to assign the most likely candidate distribution from a pool of the location-scale distributions based on interval-censored field failure samples. The maximum likelihood estimates (MLE) of parameters of the candidate distribution are estimated by using the Newton–Raphson method and the MLE of a quartile is assigned as the reliability measure for assessing the reliability of systems. To illustrate the applications of the proposed model selection procedures, an example of high-speed motor with interval-censored field failure data is given. Monte Carlo simulations are carried out to evaluate the performance of the proposed model selection procedures. Simulation results show that the proposed methods are efficient for model identification and can provide reliable reliability assessment.
    關聯: International Journal of Reliability, Quality and Safety Engineering, 2050018 (19 pages)
    DOI: 10.1142/S0218539320500187
    显示于类别:[統計學系暨研究所] 期刊論文

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