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Integrated degradation-based burn-in and maintenance model for heterogeneous and highly reliable items

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  • Safaei, Fatemeh
  • Taghipour, Sharareh

Abstract

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 lifetime-based 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.

Suggested Citation

  • Safaei, Fatemeh & Taghipour, Sharareh, 2024. "Integrated degradation-based burn-in and maintenance model for heterogeneous and highly reliable items," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
  • Handle: RePEc:eee:reensy:v:244:y:2024:i:c:s0951832024000176
    DOI: 10.1016/j.ress.2024.109942
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    References listed on IDEAS

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    1. Mullen, Katharine M. & Ardia, David & Gil, David L. & Windover, Donald & Cline, James, 2011. "DEoptim: An R Package for Global Optimization by Differential Evolution," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i06).
    2. Cheng, Yao & Wei, Yian & Liao, Haitao, 2022. "Optimal sampling-based sequential inspection and maintenance plans for a heterogeneous product with competing failure modes," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    3. Wallace R. Blischke & M. Rezaul Karim & D. N. Prabhakar Murthy, 2011. "Warranty Data Collection and Analysis," Springer Series in Reliability Engineering, Springer, number 978-0-85729-647-4, August.
    4. Aven, Terje & Castro, I.T., 2008. "A minimal repair replacement model with two types of failure and a safety constraint," European Journal of Operational Research, Elsevier, vol. 188(2), pages 506-515, July.
    5. Ji Hwan Cha, 2011. "A Survey of Burn-in and Maintenance Models for Repairable Systems," Springer Series in Reliability Engineering, in: Lotfi Tadj & M.-Salah Ouali & Soumaya Yacout & Daoud Ait-Kadi (ed.), Replacement Models with Minimal Repair, pages 179-203, Springer.
    6. Maxim Finkelstein & Ji Hwan Cha, 2013. "Stochastic Modeling for Reliability," Springer Series in Reliability Engineering, Springer, edition 127, number 978-1-4471-5028-2, August.
    7. Ji Hwan Cha & Maxim Finkelstein & Gregory Levitin, 2022. "Replacement Policy for Heterogeneous Items Subject to Gamma Degradation Processes," Methodology and Computing in Applied Probability, Springer, vol. 24(3), pages 1323-1340, September.
    8. Cha, Guesik & Park, Junseok & Moon, Ilkyeong, 2023. "Military aircraft flight and maintenance planning model considering heterogeneous maintenance tasks," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    9. Yue Shi & Yisha Xiang & Ying Liao & Zhicheng Zhu & Yili Hong, 2020. "Optimal burn-in policies for multiple dependent degradation processes," IISE Transactions, Taylor & Francis Journals, vol. 53(11), pages 1281-1293, November.
    10. Safaei, Fatemeh & Ahmadi, Jafar & Taghipour, Sharareh, 2022. "A maintenance policy for a k-out-of-n system under enhancing the system’s operating time and safety constraints, and selling the second-hand components," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    11. Fu, Yuqiang & Zhu, Xiaoyan, 2023. "A joint age-based system replacement and component reallocation maintenance policy: Optimization, analysis and resilience," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    12. E. Mosayebi Omshi & S. Shemehsavar, 2018. "An optimal burn‐in policy based on a degradation model," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 34(4), pages 486-498, July.
    13. Shen, Jingyuan & Cui, Lirong & Ma, Yizhong, 2019. "Availability and optimal maintenance policy for systems degrading in dynamic environments," European Journal of Operational Research, Elsevier, vol. 276(1), pages 133-143.
    14. Chen, Zhen & Pan, Ershun & Xia, Tangbin & Li, Yanting, 2020. "Optimal degradation-based burn-in policy using Tweedie exponential-dispersion process model with measurement errors," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    15. Finkelstein, Maxim & Cha, Ji Hwan & Langston, Amy, 2023. "Improving classical optimal age-replacement policies for degrading items," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    16. van Noortwijk, J.M., 2009. "A survey of the application of gamma processes in maintenance," Reliability Engineering and System Safety, Elsevier, vol. 94(1), pages 2-21.
    17. Safaei, Fatemeh & Taghipour, Sharareh, 2022. "Optimal preventive maintenance for repairable products with three types of failures sold under a renewable hybrid FRW/PRW policy," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    18. Ji Hwan Cha & Maxim Finkelstein, 2014. "Burn-in for Eliminating Weak Items in Heterogeneous Populations," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 43(24), pages 5115-5129, December.
    19. Tavangar, Mahdi & Hashemi, Marzieh, 2022. "Reliability and maintenance analysis of coherent systems subject to aging and environmental shocks," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    20. Veloso, Guilherme A. & Loschi, Rosangela H., 2021. "Dynamic linear degradation model: Dealing with heterogeneity in degradation paths," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    21. Xin Liu & Thomas A. Mazzuchi, 2008. "The Optimal Burn-in: State of the Art and New Advances for Cost Function Formulation," Springer Series in Reliability Engineering, in: Hoang Pham (ed.), Recent Advances in Reliability and Quality in Design, chapter 6, pages 137-182, Springer.
    22. Cha, Ji Hwan & Finkelstein, Maxim, 2011. "Burn-in and the performance quality measures in heterogeneous populations," European Journal of Operational Research, Elsevier, vol. 210(2), pages 273-280, April.
    23. Toshio Nakagawa, 2005. "Maintenance Theory of Reliability," Springer Series in Reliability Engineering, Springer, number 978-1-84628-221-8, August.
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