Model selection methods for reliability assessment based on interval-censored field failure samples
學年 108
學期 2
出版（發表）日期 2020-06-13
作品名稱 Model selection methods for reliability assessment based on interval-censored field failure samples
作品名稱（其他語言）
著者 Tzong-Ru Tsai; Sih-Hua Wu; Yan Shen
單位
出版者
著錄名稱、卷期、頁數 International Journal of Reliability, Quality and Safety Engineering v.27(6), 2050018
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.
關鍵字 Akaike information criterion;Bayesian information criterion;field failure data;location-scale family;maximum likelihood estimation
語言 en
ISSN 1793-6446
期刊性質 國外
收錄於 ESCI Scopus
產學合作
通訊作者
審稿制度 是
國別 SGP
公開徵稿
出版型式 ,電子版
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