In modern industries, manufacturers employ burn -in procedures to detect and remove faulty units before they are put into use. However, with the increasing prevalence of highly reliable items, traditional lifetimebased burn -in approaches may not be effective. So, the degradation -based approach screening units based on their degradation levels becomes more prevalent. Ensuring the safety and reliability of a system requires maintenance, making it crucial to find optimal burn -in settings and maintenance time simultaneously. This paper presents an integrated degradation -based burn -in and maintenance model, assuming a population comprising several heterogeneous subpopulations. The model has four decision parameters, three for the burn -in settings, and one for maintenance. To determine the parameters optimally, two optimization problems are presented. The first problem minimizes expected cost function by considering availability and safety as constraints. The second problem maximizes a joint function of cost and availability given a safety constraint. A comprehensive numerical analysis is conducted to offer valuable insights for practitioners. The proposed approach is compared to a stand-alone planned maintenance model, as well as models that neglect availability and safety constraints. The results of the comparative studies show the integrated model outperforms. The proposed model is illustrated using a case study on high -power semiconductor lasers.
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Sun Yat Sen Univ, Sun Yat Sen Business Sch, Dept Management Sci, Guangzhou 510275, Guangdong, Peoples R ChinaSun Yat Sen Univ, Sun Yat Sen Business Sch, Dept Management Sci, Guangzhou 510275, Guangdong, Peoples R China
Xiang, Yisha
Coit, David W.
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Rutgers State Univ, Ind & Syst Engn Dept, Piscataway, NJ 08854 USASun Yat Sen Univ, Sun Yat Sen Business Sch, Dept Management Sci, Guangzhou 510275, Guangdong, Peoples R China
Coit, David W.
Feng, Qianmei
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Univ Houston, Dept Ind Engn, Houston, TX 77204 USASun Yat Sen Univ, Sun Yat Sen Business Sch, Dept Management Sci, Guangzhou 510275, Guangdong, Peoples R China
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King Saud Univ, Dept Stat & Operat Res, Coll Sci, Riyadh 11362, Saudi Arabia
Suez Univ, Dept Math & Comp Sci, Fac Sci, Suez 43511, EgyptKing Saud Univ, Dept Stat & Operat Res, Coll Sci, Riyadh 11362, Saudi Arabia
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City Univ Hong Kong, Dept Syst Engn & Engn Management, Hong Kong, Peoples R ChinaCity Univ Hong Kong, Dept Syst Engn & Engn Management, Hong Kong, Peoples R China
Zhang, Mimi
Gaudoin, Olivier
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Grenoble Univ, Lab Jean Kuntzmann, Grenoble, FranceCity Univ Hong Kong, Dept Syst Engn & Engn Management, Hong Kong, Peoples R China
Gaudoin, Olivier
Xie, Min
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City Univ Hong Kong, Dept Syst Engn & Engn Management, Hong Kong, Peoples R ChinaCity Univ Hong Kong, Dept Syst Engn & Engn Management, Hong Kong, Peoples R China
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Western New England Univ, Dept Ind Engn & Engn Management, Springfield, MA 01119 USAWestern New England Univ, Dept Ind Engn & Engn Management, Springfield, MA 01119 USA
Li, Zhaojun
Deng, Yiming
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Univ Colorado, Dept Elect Engn, Denver, CO 80217 USAWestern New England Univ, Dept Ind Engn & Engn Management, Springfield, MA 01119 USA
Deng, Yiming
Mastrangelo, Christina
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Univ Washington, Dept Ind & Syst Engn, Seattle, WA 98195 USAWestern New England Univ, Dept Ind Engn & Engn Management, Springfield, MA 01119 USA