Abstract
The design of constant-stress accelerated life-test (CSALT) is important in reliability estimation. In reliability studies, practitioners usually rely on underlying distribution to design CSALTs. However, model misspecification analysis of optimal designs has not been examined extensively. This paper considers one-shot device testing data by assuming gamma, Weibull, lognormal and Birnbaum–Saunders (BS) lifetime distributions, which are popular lifetime distributions in reliability studies. We then investigate the effect of model misspecification between these lifetime distributions in the design of optimal CSALTs, in which the asymptotic variance of the estimate of reliability of the device at a specific mission time is minimized subject to a prefixed budget and a termination time of the life-test. The inspection frequency, number of inspections at each stress level, and allocation of the test devices are determined in optimal design for one-shot device testing. Finally, a numerical example involving a grease-based magnetorheological fluids (G-MRF) data set is used to illustrate the developed methods. Results suggest the assumption of lifetime distribution as Weibull or lognormal to be more robust to model misspecification, while the assumption of gamma lifetime distribution seems to be the most non-robust (or most sensitive) one. Copyright © 2021 The Authors. Quality and Reliability Engineering International published by John Wiley & Sons Ltd.
Original language | English |
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Pages (from-to) | 989-1012 |
Journal | Quality and Reliability Engineering International |
Volume | 38 |
Issue number | 2 |
Early online date | 03 Dec 2021 |
DOIs | |
Publication status | Published - Mar 2022 |
Citation
Balakrishnan, N., Castilla, E., & Ling, M. H. (2022). Optimal designs of constant-stress accelerated life-tests for one-shot devices with model misspecification analysis. Quality and Reliability Engineering International, 38(2), 989-1012. doi: 10.1002/qre.3031Keywords
- Accelerated life-test
- Asymptotic variance
- Best test plan
- BS distribution
- Gamma distribution
- Lognormal distribution
- Model misspecification
- One-shot device
- Reliability
- Weibull distribution