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A Multi‐objective Joint Burn‐in and Imperfect Condition‐based Maintenance Model for Degradation‐based Heterogeneous Populations
Author(s) -
Xiang Yisha,
Coit David W.,
Zhu Zhicheng
Publication year - 2016
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.2076
Subject(s) - imperfect , computer science , degradation (telecommunications) , unit (ring theory) , joint (building) , process (computing) , burn in , variable (mathematics) , reliability engineering , operations research , industrial engineering , engineering , mathematics , architectural engineering , telecommunications , linguistics , mathematics education , mathematical analysis , philosophy , operating system
For some engineering design and manufacturing applications, particularly for evolving and new technologies, there can exist substantial heterogeneity in populations of manufactured components. The co‐existence of n subpopulations and unit‐to‐unit heterogeneity can be common in devices when the manufacturing process is still maturing or highly variable. In this research, we not only model the heterogeneity at the subpopulation‐level but also at the unit‐level. A mixture degradation framework is developed to model this multi‐level heterogeneity. Based on the proposed mixture degradation model, we develop a multi‐objective optimization model to jointly determine burn‐in and condition‐based maintenance policies for populations composed of distinct subpopulations with random effects. We allow the condition‐based maintenance to be imperfect, which is more realistic. Our joint models are entirely appropriate for companies that are the providers of both products and services, and can also produce optimal collective results and decisions that can quantify potential savings or benefits through cooperative efforts between producer and user. Numerical examples are provided to illustrate the proposed procedure. Copyright © 2016 John Wiley & Sons, Ltd.