IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v236y2023ics0951832023001886.html
   My bibliography  Save this article

Mission reliability-driven risk-based predictive maintenance approach of multistate manufacturing system

Author

Listed:
  • Liao, Ruoyu
  • He, Yihai
  • Feng, Tianyu
  • Yang, Xiuzhen
  • Dai, Wei
  • Zhang, Weifang

Abstract

With the coupling effect of equipment state, product quality, and task requirements of manufacturing system, physical condition-based maintenance of the manufacturing system has gradually failed to satisfy the corresponding requirements, leading to operational risk improvement continuously. However, few existing maintenance studies consider operational risk, such as product quality decline and production task delay. Therefore, a novel operational risk-based predictive maintenance approach is proposed using mission reliability and adopting the principle of risk-based maintenance. First, according to the operation principle of manufacturing system, the definition of mission reliability-oriented operational risk is expounded, and the mechanism of risk-based maintenance is put forward. Second, the source and types of operational risk are explained: the fundamental risk is obtained from the manufacturing equipment degradation and failures, the explicit risk is characterized by the qualification rate of key quality characteristics of process and products, and the implicit risk is quantified by the realization rate of production tasks. Third, to decrease the three risk types, an operational risk-based predictive maintenance strategy is proposed to minimize the comprehensive production cost. Finally, a case study of subway current receiver manufacturing system is conducted to illustrate the effectiveness and advantages of the proposed approach.

Suggested Citation

  • Liao, Ruoyu & He, Yihai & Feng, Tianyu & Yang, Xiuzhen & Dai, Wei & Zhang, Weifang, 2023. "Mission reliability-driven risk-based predictive maintenance approach of multistate manufacturing system," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    • Handle: RePEc:eee:reensy:v:236:y:2023:i:c:s0951832023001886
    DOI: 10.1016/j.ress.2023.109273
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832023001886
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2023.109273?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hao, Zhifeng & Yeh, Wei-Chang & Tan, Shi-Yi, 2021. "One-batch preempt deterioration-effect multi-state multi-rework network reliability problem and algorithms," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    2. Evrencan Özcan & Rabia Yumuşak & Tamer Eren, 2019. "Risk Based Maintenance in the Hydroelectric Power Plants," Energies, MDPI, vol. 12(8), pages 1-22, April.
    3. Alaswad, Suzan & Xiang, Yisha, 2017. "A review on condition-based maintenance optimization models for stochastically deteriorating system," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 54-63.
    4. Hesabi, Hadis & Nourelfath, Mustapha & Hajji, Adnène, 2022. "A deep learning predictive model for selective maintenance optimization," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    5. Li, Yaping & Xia, Tangbin & Chen, Zhen & Pan, Ershun, 2023. "Multiple degradation-driven preventive maintenance policy for serial-parallel multi-station manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    6. Dui, Hongyan & Zhang, Chi & Tian, Tianzi & Wu, Shaomin, 2022. "Different costs-informed component preventive maintenance with system lifetime changes," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    7. Li, Yao & He, Yihai & Liao, Ruoyu & Zheng, Xin & Dai, Wei, 2022. "Integrated predictive maintenance approach for multistate manufacturing system considering geometric and non-geometric defects of products," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    8. Nguyen, Van-Thai & Do, Phuc & Vosin, Alexandre & Iung, Benoit, 2022. "Artificial-intelligence-based maintenance decision-making and optimization for multi-state component systems," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    9. Mahmood Shafiee & Ashraf Labib & Jhareswar Maiti & Andrew Starr, 2019. "Maintenance strategy selection for multi-component systems using a combined analytic network process and cost-risk criticality model," Journal of Risk and Reliability, , vol. 233(2), pages 89-104, April.
    10. GAO, Guibing & ZHOU, Dengming & TANG, Hao & HU, Xin, 2021. "An Intelligent Health diagnosis and Maintenance Decision-making approach in Smart Manufacturing," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    11. Han, Xiao & Wang, Zili & Xie, Min & He, Yihai & Li, Yao & Wang, Wenzhuo, 2021. "Remaining useful life prediction and predictive maintenance strategies for multi-state manufacturing systems considering functional dependence," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    12. Yihai He & Changchao Gu & Zhaoxiang Chen & Xiao Han, 2017. "Integrated predictive maintenance strategy for manufacturing systems by combining quality control and mission reliability analysis," International Journal of Production Research, Taylor & Francis Journals, vol. 55(19), pages 5841-5862, October.
    13. Pedersen, Tom Ivar & Vatn, Jørn, 2022. "Optimizing a condition-based maintenance policy by taking the preferences of a risk-averse decision maker into account," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    14. Yang, Xiuzhen & He, Yihai & Liao, Ruoyu & Cai, Yuqi & Ai, Jun, 2022. "Integrated mission reliability modeling based on extended quality state task network for intelligent multistate manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yao, Jinyong & Gao, Zhanfei & He, Yihai & Peng, Chong, 2024. "Integrated mission reliability modeling for multistate manufacturing systems considering heterogeneous feedstocks based on extended stochastic flow manufacturing network," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    2. Deng, Wanyi & Ma, Xiaoxue & Qiao, Weiliang, 2024. "A novel methodology to quantify the impact of safety barriers on maritime operational risk based on a probabilistic network," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    3. Yang, Xiuzhen & He, Yihai & Liao, Ruoyu & Cai, Yuqi & Dai, Wei, 2024. "Mission reliability-centered opportunistic maintenance approach for multistate manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 241(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ye, Zhenggeng & Cai, Zhiqiang & Yang, Hui & Si, Shubin & Zhou, Fuli, 2023. "Joint optimization of maintenance and quality inspection for manufacturing networks based on deep reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    2. Yang, Xiuzhen & He, Yihai & Liao, Ruoyu & Cai, Yuqi & Dai, Wei, 2024. "Mission reliability-centered opportunistic maintenance approach for multistate manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    3. Yang, Xiuzhen & He, Yihai & Liao, Ruoyu & Cai, Yuqi & Ai, Jun, 2022. "Integrated mission reliability modeling based on extended quality state task network for intelligent multistate manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    4. 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).
    5. Wang, Yu & Xia, Tangbin & Xu, Yuhui & Si, Guojin & Wang, Dong & Pan, Ershun & Xi, Lifeng, 2024. "Quality-centered production and maintenance scheduling for multi-machine manufacturing systems under variable operating conditions," Reliability Engineering and System Safety, Elsevier, vol. 250(C).
    6. Finkelstein, Maxim & Cha, Ji Hwan & Bedford, Tim, 2023. "Optimal preventive maintenance strategy for populations of systems that generate outputs," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    7. Yao, Jinyong & Gao, Zhanfei & He, Yihai & Peng, Chong, 2024. "Integrated mission reliability modeling for multistate manufacturing systems considering heterogeneous feedstocks based on extended stochastic flow manufacturing network," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    8. Li, Yao & He, Yihai & Liao, Ruoyu & Zheng, Xin & Dai, Wei, 2022. "Integrated predictive maintenance approach for multistate manufacturing system considering geometric and non-geometric defects of products," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    9. Wang, Wenzhuo & He, Yihai & Liao, Ruoyu & Cai, Yuqi & Zheng, Xin & Zhao, Yu, 2022. "Mission reliability driven functional healthy state modeling approach considering production rhythm and workpiece quality for manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    10. Giorgio, Massimiliano & Pulcini, Gianpaolo, 2024. "The effect of model misspecification of the bounded transformed gamma process on maintenance optimization," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    11. Cheng, Guo Qing & Zhou, Bing Hai & Li, Ling, 2018. "Integrated production, quality control and condition-based maintenance for imperfect production systems," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 251-264.
    12. Pedersen, Tom Ivar & Vatn, Jørn, 2022. "Optimizing a condition-based maintenance policy by taking the preferences of a risk-averse decision maker into account," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    13. Dinh, Duc-Hanh & Do, Phuc & Iung, Benoit, 2022. "Multi-level opportunistic predictive maintenance for multi-component systems with economic dependence and assembly/disassembly impacts," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    14. Chen, Zhaoxiang & Chen, Zhen & Zhou, Di & Pan, Ershun, 2023. "Energy-oriented opportunistic maintenance optimization of continuous process manufacturing systems with two types of stochastic durations," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    15. Shi, Haohao & Zhang, Ji & Zio, Enrico & Zhao, Xufeng, 2023. "Opportunistic maintenance policies for multi-machine production systems with quality and availability improvement," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    16. Li, Yaohan & Dong, You & Guo, Hongyuan, 2023. "Copula-based multivariate renewal model for life-cycle analysis of civil infrastructure considering multiple dependent deterioration processes," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    17. Sánchez, Luciano & Costa, Nahuel & Couso, Inés, 2023. "Simplified models of remaining useful life based on stochastic orderings," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    18. Ma, Weining & Zhang, Qin & Xiahou, Tangfan & Liu, Yu & Jia, Xisheng, 2023. "Integrated selective maintenance and task assignment optimization for multi-state systems executing multiple missions," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    19. Yin, Mingang & Liu, Yu & Liu, Shuntao & Chen, Yiming & Yan, Yutao, 2023. "Scheduling heterogeneous repair channels in selective maintenance of multi-state systems with maintenance duration uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    20. GAO, Guibing & ZHOU, Dengming & TANG, Hao & HU, Xin, 2021. "An Intelligent Health diagnosis and Maintenance Decision-making approach in Smart Manufacturing," Reliability Engineering and System Safety, Elsevier, vol. 216(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:236:y:2023:i:c:s0951832023001886. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.