期刊
ANNALS OF APPLIED STATISTICS
卷 7, 期 4, 页码 2249-2271出版社
INST MATHEMATICAL STATISTICS-IMS
DOI: 10.1214/13-AOAS666
关键词
Accelerated life test data; frailty model; field failure data; heterogeneous operating conditions; optimal plan
资金
- Sate Key Laboratory of Industrial Control Technology [ICT1313]
- NSF [CMMI-1068933]
- DuPont Young Professor Grant
- Directorate For Engineering
- Div Of Civil, Mechanical, & Manufact Inn [1068933] Funding Source: National Science Foundation
The main objective of accelerated life tests (ALTs) is to predict fraction failings of products in the field. However, there are often discrepancies between the predicted fraction failing from the lab testing data and that from the field failure data, due to the yet unobserved heterogeneities in usage and operating conditions. Most previous research on ALT planning and data analysis ignores the discrepancies, resulting in inferior test plans and biased predictions. In this paper we model the heterogeneous environments together with their effects on the product failures as a frailty term to link the lab failure time distribution and field failure time distribution of a product. We show that in the presence of the heterogeneous operating conditions, the hazard rate function of the field failure time distribution exhibits a range of shapes. Statistical inference procedure for the frailty models is developed when both the ALT data and the field failure data are available. Based on the frailty models, optimal ALT plans aimed at predicting the field failure time distribution are obtained. The developed methods are demonstrated through a real life example.
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