82
Views
0
CrossRef citations to date
0
Altmetric
Article

Designing optimal proactive replacement strategies for degraded systems subject to two types of external shocks

, , , &
Pages 4450-4468 | Received 18 Apr 2022, Accepted 11 Feb 2023, Published online: 27 Feb 2023

References

  • Brown, M., and F. Proschan. 1983. Imperfect repair. Journal of Applied Probability 20 (4):851–9. doi: 10.2307/3213596.
  • Cao, Y., S., Liu, Z., Fang, and W. Dong. 2020. Modeling ageing effects for multi-state systems with multiple components subject to competing and dependent failure processes. Reliability Engineering and System Safety 199: 106890. doi: 10.1016/j.ress.2020.106890.
  • Celen, M., and D. Djurdjanovic. 2020. Integrated maintenance and operations decision making with imperfect degradation state observations. Journal of Manufacturing Systems 55: 302–16. doi: 10.1016/j.jmsy.2020.03.010.
  • Cha, J. H., and M. Finkelstein. 2018. Point processes for reliability analysis. In Shocks and repairable systems. London: Springer.
  • Chang, C. C. 2021a. Optimal preventive replacement last policy for a successive random works system with random lead time. Communications in Statistics-Theory and Methods. Available: doi: 10.1080/03610926.2021.1926506.
  • Chang, C. C. 2021b. Optimal preventive replacement policy for operating products with renewing free-replacement warranty. Communications in Statistics-Theory and Methods 50 (18):4255–70. doi: 10.1080/03610926.2020.1713371.
  • Che, H., S., Zeng, J., Guo, and Y. Wang. 2018. Reliability modeling for dependent competing failure processes with mutually dependent degradation process and shock process. Reliability Engineering and System Safety 180:168–78. doi: 10.1016/j.ress.2018.07.018.
  • Cherkaoui, H., K. T., Huynh, and A. Grall. 2018. Quantitative assessments of performance and robustness of maintenance policies for stochastically deteriorating production systems. International Journal of Production Research 56 (3):1089–108. doi: 10.1080/00207543.2017.1370563.
  • Dong, W., J., Du, M., Yang, and S. Liu. 2022. Implementing a bivariate ordering and replacement policy for deteriorating systems with two failure types. International Transactions in Operational Research. Available: doi: 10.1111/itor.13205.
  • Dong, W., S., Liu, S. J., Bae, and Y. Liu. 2020. A multi-stage imperfect maintenance strategy for multi-state systems with variable user demands. Computers and Industrial Engineering 145: 106508. doi: 10.1016/j.cie.2020.106508.
  • Dong, W., S., Liu, Y., Cao, and S. J. Bae. 2020. Time-based replacement policies for a fault tolerant system subject to degradation and two types of shocks. Quality and Reliability Engineering International 36 (7):2338–50. doi: 10.1002/qre.2700.
  • Dong, W., S., Liu, Y., Cao, and S. A. Javed. 2021. Scheduling optimal replacement policies for a stochastically deteriorating system subject to two types of shocks. ISA Transactions 112: 292–301. doi: 10.1016/j.isatra.2020.12.017.
  • Dong, W., S., Liu, Y., Cao, S. A., Javed, and Y. Du. 2020. Reliability modeling and optimal random preventive maintenance policy for parallel systems with damage self-healing. Computers and Industrial Engineering 142: 106359. doi: 10.1016/j.cie.2020.106359.
  • Dong, W., S., Liu, L., Tao, Y., Cao, and Z. Fang. 2019. Reliability variation of multi-state components with inertial effect of deteriorating output performances. Reliability Engineering and System Safety 186: 176–85. doi: 10.1016/j.ress.2019.02.018.
  • Elwany, A. H., N. Z., Gebraeel, and L. M. Maillart. 2011. Structured replacement policies for components with complex degradation processes and dedicated sensors. Operations Research 59 (3):684–95. doi: 10.1287/opre.1110.0912.
  • Fan, M., Z., Zeng, E., Zio, and R. Kang. 2017. Modeling dependent competing failure processes with degradation-shock dependence. Reliability Engineering and System Safety 165: 422–30. doi: 10.1016/j.ress.2017.05.004.
  • Grall, A., L., Dieulle, C., Bérenguer, and M. Roussignol. 2002. Continuous-time predictive-maintenance scheduling for a deteriorating system. IEEE Transactions on Reliability 51 (2):141–50. doi: 10.1109/TR.2002.1011518.
  • Huynh, K. T. 2020. Modeling past-dependent partial repairs for condition-based maintenance of continuously deteriorating systems. European Journal of Operational Research 280 (1):152–63. doi: 10.1016/j.ejor.2019.07.007.
  • Huynh, K. T., I. T., Castro, A., Barros, and C. Bérenguer. 2012. Modeling age-based maintenance strategies with minimal repairs for systems subject to competing failure modes due to degradation and shocks. European Journal of Operational Research 218 (1):140–51. doi: 10.1016/j.ejor.2011.10.025.
  • Khatab, A., C., Diallo, E. H., Aghezzaf, and U. Venkatadri. 2019. Integrated production quality and condition-based maintenance optimisation for a stochastically deteriorating manufacturing system. International Journal of Production Research 57 (8):2480–97. doi: 10.1080/00207543.2018.1521021.
  • Kim, M. J. 2016. Robust control of partially observable failing systems. Operations Research 64 (4):999–1014. doi: 10.1287/opre.2016.1495.
  • Kim, M. J., and V. Makis. 2013. Joint optimization of sampling and control of partially observable failing systems. Operations Research 61 (3):777–90. doi: 10.1287/opre.2013.1171.
  • Lee, D., and R. Pan. 2017. Predictive maintenance of complex system with multi-level reliability structure. International Journal of Production Research 55 (16):4785–801. doi: 10.1080/00207543.2017.1299947.
  • Li, Q., W., Dong, S., Liu, and Z. Fang. 2022. Generalized periodic replacement policies for repairable systems subject to two types of failures. RAIRO-Operations Research 56 (2):703–20. doi: 10.1051/ro/2022040.
  • Liu, B., S., Wu, M., Xie, and W. Kuo. 2017. A condition-based maintenance policy for degrading systems with age- and state-dependent operating cost. European Journal of Operational Research 263 (3):879–87. doi: 10.1016/j.ejor.2017.05.006.
  • Lu, L., B. X., Wang, Y. L., Hong, and Z. S. Ye. 2020. General path models for degradation data with multiple characteristics and covariates. Technometrics 63 (3):354–69. doi: 10.1080/00401706.2020.1796814.
  • Ouyang, L., J., Chen, Y., Ma, C., Park, and J. Jin. 2020. Bayesian closed-loop robust process design considering model uncertainty and data quality. IISE Transactions 52 (3):288–300. doi: 10.1080/24725854.2019.1636428.
  • Panagiotidou, S., and G. Tagaras. 2010. Statistical process control and conditionbased maintenance: A meaningful relationship through data sharing. Production and Operations Management 19 (2):156–71. doi: 10.1111/j.1937-5956.2009.01073.x.
  • Peng, H., and Q. Feng. 2013. Reliability modeling for ultrathin gate oxides subject to logistic degradation processes with random onset time. Quality and Reliability Engineering International 29 (5):709–18. doi: 10.1002/qre.1421.
  • Peng, H., Q., Feng, and D. W. Coit. 2010. Reliability and maintenance modeling for systems subject to multiple dependent competing failure processes. IIE Transactions 43 (1):12–22. doi: 10.1080/0740817X.2010.491502.
  • Sheu, S. H., Y. H., Chien, C. C., Chang, and C. H. Chiu. 2014. Optimal trivariate replacement policies for a deteriorating system. Quality Technology and Quantitative Management 11 (3):307–20. doi: 10.1080/16843703.2014.11673347.
  • Sheu, S. H., T. H., Liu, Z. G., Zhang, and J. C. Ke. 2015. Extended preventive replacement policy for a two-unit system subject to damage shocks. International Journal of Production Research 53 (15):4614–28. doi: 10.1080/00207543.2015.1005250.
  • Sheu, S. H., T. H., Liu, Z. G., Zhang, H. N., Tsai, and J. C. Chen. 2016. Optimal two-threshold replacement policy in a cumulative damage model. Annals of Operations Research 244 (1):23–47. doi: 10.1007/s10479-016-2142-3.
  • Wang, J., G., Bai, Z., Li, and M. J. Zuo. 2020. A general discrete degradation model with fatal shocks and age- and state-dependent nonfatal shocks. Reliability Engineering and System Safety 193: 106648. doi: 10.1016/j.ress.2019.106648.
  • Wang, J., G., Bai, and L. Zhang. 2020. Modeling the interdependency between natural degradation process and random shocks. Computers and Industrial Engineering 145: 106551. doi: 10.1016/j.cie.2020.106551.
  • Wang, J., Z., Li, G., Bai, and M. J. Zuo. 2020. An improved model for dependent competing risks considering continuous degradation and random shocks. Reliability Engineering and System Safety 193: 106641. doi: 10.1016/j.ress.2019.106641.
  • Wang, J., and J. Ye. 2020. A new repair model and its optimization for cold standby system. Operational Research. Available: doi: 10.1007/s12351-020-00545-x.
  • Wang, Y., and H. Pham. 2012. Modeling the dependent competing risks with multiple degradation processes and random shock using time-varying copulas. IEEE Transactions on Reliability 61 (1):13–22. doi: 10.1109/TR.2011.2170253.
  • Ye, Z. S., and M. Xie. 2015. Stochastic modelling and analysis of degradation for highly reliable products. Applied Stochastic Models in Business and Industry 31 (1):16–32. doi: 10.1002/asmb.2063.
  • Yousefi, N., D. W., Coit, and X. Zhu. 2020. Dynamic maintenance policy for systems with repairable components subject to mutually dependent competing failure processes. Computers and Industrial Engineering 143: 106398 doi: 10.1016/j.cie.2020.106398.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.