Sequential degradation-based burn-in test with multiple periodic inspections  

作　　者：Jiawen HU Qiuzhuang SUN Zhi-Sheng YE Xiaoliang LING 

机构地区：[1]Department of Industrial Systems Engineering and Management,National University of Singapore,Singapore 119077,Singapore [2]School of Aeronautics and Astronautics,University of Electronic Science and Technology of China,Chengdu 611731,China [3]National University of Singapore Suzhou Research Institute,Suzhou 215000,China [4]College of Sciences,Hebei University of Science and Technology,Shijiazhuang 050018,China

出　　处：《Frontiers of Engineering Management》2021年第4期519-530,共12页工程管理前沿（英文版）

基　　金：The research is supported by the National Natural Science Foundation of China(Grant Nos.7180116&72071138 and 72071071);the Young Talent Support Plan of Hebei Province.

摘　　要：Bum-in has been proven effective in identifying and removing defective products before they are delivered to customers.Most existing bum-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 bum-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 bum-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.

关 键 词：bum-in DEGRADATION multiple inspections Wiener process partially observed Markov decision process 

分 类 号：N94[自然科学总论—系统科学]