Abstract
Burn-in has been proven effective in identifying and removing defective products before they are delivered to customers. Most existing burn-in models adopt a one-shot scheme, which may not be sufficient enough for identification. Borrowing the idea from sequential inspections for remaining useful life prediction and accelerated lifetime test, this study proposes a sequential degradation-based burn-in model with multiple periodic inspections. At each inspection epoch, the posterior probability that a product belongs to a normal one is updated with the inspected degradation level. Based on the degradation level and the updated posterior probability, a product can be disposed, put into field use, or kept in the test till the next inspection epoch. We cast the problem into a partially observed Markov decision process to minimize the expected total burn-in cost of a product, and derive some interesting structures of the optimal policy. Then, algorithms are provided to find the joint optimal inspection period and number of inspections in steps. A numerical study is also provided to illustrate the effectiveness of our proposed model.
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The research is supported by the National Natural Science Foundation of China (Grant Nos. 71801168, 72071138 and 72071071), and the Young Talent Support Plan of Hebei Province.
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Hu, J., Sun, Q., Ye, ZS. et al. Sequential degradation-based burn-in test with multiple periodic inspections. Front. Eng. Manag. 8, 519–530 (2021). https://doi.org/10.1007/s42524-021-0166-0
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DOI: https://doi.org/10.1007/s42524-021-0166-0