Remaining Useful Life Prediction for a Multi-Component System with Degradation Interactions

Kalaei, Mahdiyeh; Saniee Monfared, Mohammad Ali

doi:10.22034/IJRRS.2023.6.1.4

Remaining Useful Life Prediction for a Multi-Component System with Degradation Interactions

Document Type : Original Research Article

Authors

Mahdiyeh Kalaei

Mohammad Ali Saniee Monfared

Department of Industrial Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran

10.22034/IJRRS.2023.6.1.4

Abstract

Remaining useful life (RUL) prediction is crucial in prognostics and health management (PHM) systems. The primary objective is to forecast the time to failure (TTF) or anticipate the RUL of a system. In real industrial cases, systems typically consist of multiple components that can affect each other, and ignoring these dependencies when modeling PHM systems can lead to erroneous RUL predictions and ineffective maintenance planning. Recognizing this, the focus of this paper is on the prognostics of multi-component systems, where the degradation processes of the system are influenced by both internal factors specific to the components and external factors related to the environment.

Keywords

Multi-component system

Prognostic

Degradation modeling

Remaining useful life prediction

Subjects

Maintenance engineering

Dekker, RE. Wldeman and D. Schouten, “A review of multi-component maintenance models with economic dependence”. Mathematical Methods of Operations Research, vol. 45, pp. 411-435, 1997. doi: https://doi.org/10.1007/BF01194788
P. Nicolai and R. Dekker, “Optimal Maintenance of Multi-component Systems: A Review”. Complex System Maintenance Handbook. pp. 263–286, 2008,doi: https://doi.org/10.1007/978-1-84800-011-7_11
Cao, X. Jia, Q. Hu, J. Zhao and Y. Wu, “A literature review on selective maintenance for multi‐unit systems”. RESEARCH ARTICLE, vol. 34, pp. 824-845, 2018, doi: https://doi.org/10.1002/qre.2293
Zhang, M. Chen and D. Zhou, "Predicting remaining useful life for a multi-Component system with public noise," 2016 Prognostics and System Health Management Conference (PHM-Chengdu), Chengdu, China, 2016, pp. 1-6, doi: https://doi.org/10.1109/PHM.2016.7819819
Bian and N. Gebraeel “Stochastic Modeling and Real-Time Prognostics for Multi-Component Systems with Degradation-Rate-Interactions”. IIE Transactions, vol.46, pp. 470-482 2014. doi: https://doi.org/10.1080/0740817X.2013.812269
-H. Sheu, T. -H. Liu, Z. G. Zhang and Y. -H. Chien, "Extended Optimal Replacement Policy for a Two-Unit System with Shock Damage Interaction", IEEE Transactions on Reliability, vol. 64, no. 3, pp. 998-1014, Sept. 2015, doi: https://doi.org/10.1109/TR.2015.2427231
Zhang, M. Fouladirad and A. Barros “Optimal imperfect maintenance cost analysis of a two-component system with failure interactions”. Reliability Engineering and System Safety. Vol. 177, pp. 24-34, 2018, doi: https://doi.org/10.1016/j.ress.2018.04.019
Dinh, P. Do and B. Iung “Degradation modeling and reliability assessment for a multi-component system with structural dependence”. Computers & Industrial Engineering, vol. 144, p. 106443, 2020, doi: https://doi.org/10.1016/j.cie.2020.106443
Bakir, M. Yildirim and E. Ursavas, “An integrated optimization framework for multi-component predictive analytics in wind farm operations & maintenance”. Renewable and Sustainable Energy Reviews, vol. 138, p. 110639, 2021, doi: https://doi.org/10.1016/j.rser.2020.110639
Niu H, Zeng J, Shi H, Zhang X, Liang J. “Degradation Modeling and Remaining Useful Life Prediction for a Multicomponent System with Stochastic Dependence”. Computers & Industrial Engineering, vol. 175, p. 108889, 2022, doi: https://doi.org/10.1016/j.cie.2022.108889
Özgür-Ünlüakın and B. Turkali “Evaluation of proactive maintenance policies on a stochastically dependent hidden multi-component system using DBNs”. Reliability Engineering and System Safety, vol. 211, p. 107559, 2021, doi: https://doi.org/10.1016/j.ress.2021.107559
Zhang, K. Cai, J. Zhang and T. Wang, “A condition-based maintenance policy considering failure dependence and imperfect inspection for a two-component system”. Reliability Engineering and System Safety, vol. 217, p. 108069, 2022, doi: https://doi.org/10.1016/j.ress.2021.108069
Nguyen, K. Medjaher and C. Gogu, “Probabilistic deep learning methodology for uncertainty quantification of remaining useful lifetime of multi-component systems”, Reliability Engineering and System Safety, vol. 222, p. 108383, 2022, doi: https://doi.org/10.1016/j.ress.2022.108383
Li, W. Zhu, L. Dieulle and E. Deloux “Condition-based maintenance strategies for stochastically dependent systems using Nested Lévy copulas”, Reliability Engineering and System Safety, vol. 217, p. 108038, 2022, doi: https://doi.org/10.1016/j.ress.2021.108038
Shi and J. Zeng “Real-time prediction of remaining useful life and preventive opportunistic maintenance strategy for multi-component systems considering stochastic dependence”, Computers & Industrial Engineering, Vol. 93, pp. 192-204, 2016, doi: https://doi.org/10.1016/j.cie.2015.12.016
Zhang, and W. Si, “Deep Reinforcement Learning for Condition-Based Maintenance Planning of Multi-Component Systems Under Dependent Competing Risks”. Reliability Engineering and System Safety, vol. 203, p. 107094, 2020, doi: https://doi.org/10.1016/j.ress.2020.107094
Shen, A. Elwany and L. Cui, “Reliability analysis for multi-component systems with degradation interaction and categorized shocks” Applied Mathematical Modelling, Vol. 56, pp. 487-500, 2018, doi: https://doi.org/10.1016/j.apm.2017.12.001
Martinod, O. Bistorin, LF. Castaneda and N. Rezg, “Maintenance policy optimisation for multi-component systems considering degradation of components and imperfect maintenance actions”. Computers & Industrial Engineering, Vol. 124, pp. 100-112, 2018, doi: https://doi.org/10.1016/j.cie.2018.07.019
Xu, X. Jin, S. Kamarthi and Md. Noor-E-Alam “A failure-dependency modeling and state discretization approach for condition-based maintenance optimization of multi-component systems”. Journal of Manufacturing Systems, Vol. 47, pp. 141-152, 2018, doi: https://doi.org/10.1016/j.jmsy.2018.04.018
Nguyen, P. Do and A. Grall “Joint predictive maintenance and inventory strategy for multi-component systems using Birnbaum’s structural importance”. Reliability Engineering and System Safety, Vol. 168, pp. 249-261, 2017, doi: https://doi.org/10.1016/j.ress.2017.05.034
Do, R. Assef, P. Scarf and B. Lung “Modelling and application of condition-based maintenance for a two-component system with stochastic and economic dependencies”. Reliability Engineering and System Safety, vol. 189, pp.: 86-97, 2019. doi: https://doi.org/10.1016/j.ress.2018.10.007
Shafiee, A. Labib, J. Maiti and A. Starr, “Maintenance strategy selection for multi-component systems using a combined analytic network process and cost-risk criticality model”. Institution MECHANICAL ENGINEERS, Vol. 233, no. 2, pp. 89-104, 2019, doi: https://doi.org/10.1177/1748006X17712071
Liu, MD. Pandey, X. Wang and X. Zhao “A finite-horizon condition-based maintenance policy for a two-unit system with dependent degradation processes”. European Journal of Operational Research, Vol. 295, pp. 705-717, 2021, doi: https://doi.org/10.1016/j.ejor.2021.03.010
Wang, X. Li, J. Chen and Y. Liu “A condition-based maintenance policy for multi-component systems subject to stochastic and economic dependencies”. Reliability Engineering and System Safety, vol. 219, p. 108174, 2022, doi: https://doi.org/10.1016/j.ress.2021.108174
Oakley, KJ. Wilson and P. Philipson. “A condition-based maintenance policy for continuously monitored multi-component systems with economic and stochastic dependence”. Reliability Engineering and System Safety, vol. 222, p. 108321, 2022, doi: https://doi.org/10.1016/j.ress.2022.108321
Zhou, TR. Lin, Y. Sun and L. Ma, “Maintenance optimization of a parallel-series system with stochastic and economic dependence under limited maintenance capacity”. Reliability Engineering and System Safet, Vol. 155, pp. 137-146, 2016, doi: https://doi.org/10.1016/j.ress.2016.06.012