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Availability modeling and optimization of dynamic multi-state series–parallel systems with random reconfiguration

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  • Li, Y.F.
  • Peng, R.

Abstract

Most studies on multi-state series–parallel systems focus on the static type of system architecture. However, it is insufficient to model many complex industrial systems having several operation phases and each requires a subset of the subsystems combined together to perform certain tasks. To bridge this gap, this study takes into account this type of dynamic behavior in the multi-state series–parallel system and proposes an analytical approach to calculate the system availability and the operation cost. In this approach, Markov process is used to model the dynamics of system phase changing and component state changing, Markov reward model is used to calculate the operation cost associated with the dynamics, and universal generating function (UGF) is used to build system availability function from the system phase model and the component models. Based upon these models, an optimization problem is formulated to minimize the total system cost with the constraint that system availability is greater than a desired level. The genetic algorithm is then applied to solve the optimization problem. The proposed modeling and solution procedures are illustrated on a system design problem modified from a real-world maritime oil transportation system.

Suggested Citation

  • Li, Y.F. & Peng, R., 2014. "Availability modeling and optimization of dynamic multi-state series–parallel systems with random reconfiguration," Reliability Engineering and System Safety, Elsevier, vol. 127(C), pages 47-57.
    • Handle: RePEc:eee:reensy:v:127:y:2014:i:c:p:47-57
    DOI: 10.1016/j.ress.2014.03.005
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    3. Zhang, Yue & Feng, Qiang & Fan, Dongming & Ren, Yi & Sun, Bo & Yang, Dezhen & Wang, Zili, 2023. "Optimization of maritime support network with relays under uncertainty: A novel matheuristics method," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
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    7. Funda Iscioglu, 2017. "Dynamic performance evaluation of multi – state systems under non – homogeneous continuous time Markov process degradation using lifetimes in terms of order statistics," Journal of Risk and Reliability, , vol. 231(3), pages 255-264, June.
    8. Xiao, Hui & Shi, Daimin & Ding, Yi & Peng, Rui, 2016. "Optimal loading and protection of multi-state systems considering performance sharing mechanism," Reliability Engineering and System Safety, Elsevier, vol. 149(C), pages 88-95.
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    10. Yu, Huan & Yang, Jun & Peng, Rui & Zhao, Yu, 2016. "Reliability evaluation of linear multi-state consecutively-connected systems constrained by m consecutive and n total gaps," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 35-43.
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    14. Fort, A. & Mugnaini, M. & Vignoli, V., 2015. "Hidden Markov Models approach used for life parameters estimations," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 85-91.

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