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Robust Interval-Based Minimax-Regret Analysis Method For Filter Management Of Fluid Power System

Author

Listed:
  • SONGLIN NIE

    (College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing 100124, P. R. China)

  • HUI JI

    (College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing 100124, P. R. China)

  • YEQING HUANG

    (College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing 100124, P. R. China)

  • ZHEN HU

    (Department of Mechanical and Aerospace Engineering, Missouri University of Science and Technology, Rolla, Missouri 65401, USA)

  • YONGPING LI

    (S-C Energy and Environmental Research Academy, North China Electric Power University, Beijing 102206, P. R. China)

Abstract

Fluid contamination is one of the main reasons for the wear failure and the related downtime in a hydraulic power system. Filters play an important role in controlling the contamination effectively, increasing the reliability of the system, and maintaining the system economically. Due to the uncertainties of system parameters, the complicated relationship among components, as well as the lack of effective approach, managing filters is becoming one of the biggest challenges for engineers and decision makers. In this study, a robust interval-based minimax-regret analysis (RIMA) method is developed for the filter management in a fluid power system (FPS) under uncertainty. The RIMA method can handle the uncertainties existed in contaminant ingressions of the system and contaminant holding capacity of filters without making assumption on probabilistic distributions for random variables. Through analyzing the system cost of all possible filter management alternatives, an interval element regret matrix can be obtained, which enables decision makers to identify the optimal filter management strategy under uncertainty. The results of a case study indicate that the reasonable solutions generated can help decision makers understand the consequence of short-term and long-term decisions, identify optimal strategies for filter allocation and selection with minimized system-maintenance cost and system-failure risk.

Suggested Citation

  • Songlin Nie & Hui Ji & Yeqing Huang & Zhen Hu & Yongping Li, 2013. "Robust Interval-Based Minimax-Regret Analysis Method For Filter Management Of Fluid Power System," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 30(06), pages 1-40.
    • Handle: RePEc:wsi:apjorx:v:30:y:2013:i:06:n:s0217595913500218
    DOI: 10.1142/S0217595913500218
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    References listed on IDEAS

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    1. Unknown, 2001. "2001 Front Materials: Fourth Quarter," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, vol. 16(4), pages 1-5.
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    Cited by:

    1. Jungho Park & Hadi El-Amine & Nevin Mutlu, 2021. "An Exact Algorithm for Large-Scale Continuous Nonlinear Resource Allocation Problems with Minimax Regret Objectives," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1213-1228, July.

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