IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v231y2023ics0951832022006500.html
   My bibliography  Save this article

Models for reliability assessment of reconfigurable manufacturing system regarding configuration orders

Author

Listed:
  • Zhang, Tian
  • Homri, Lazhar
  • Dantan, Jean-Yves
  • Siadat, Ali

Abstract

Reliability performance is a crucial indicator in manufacturing systems. Different configurations of a manufacturing system can have profound impacts on its reliability performance. However, there has not been many in-depth studies showing how the two factors interact. This paper proposes a novel framework that can apply to scenarios with different failure distributions to explore how configuration orders impact reliability performance. Reliability assessment models are built for configuration orders of Reconfigurable Manufacturing Tools (RMTs) in a Reconfigurable Manufacturing System (RMS), where the reconfiguration process is defined by Markov states and piecewise-defined failure rate. First a model of component failure mode following Poisson process is presented which concluded that reconfiguration order does not impact the reliability performance in terms of failure rate, reliability function and unreliability function. Further, two case studies are presented: a Monte Carlo simulation for further verification, and a demonstration of model application. Then a model of component failure following Weibull distribution is proposed with failure rate continuity assumption, relationship between Weibull parameters and processing parameters is mathematically calculated. The relationship contributes to modeling of causalities among configurations. A case study demonstrates that configuration order has a significant impact on the reliability performance when failure mode follows Weibull distribution.

Suggested Citation

  • Zhang, Tian & Homri, Lazhar & Dantan, Jean-Yves & Siadat, Ali, 2023. "Models for reliability assessment of reconfigurable manufacturing system regarding configuration orders," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
  • Handle: RePEc:eee:reensy:v:231:y:2023:i:c:s0951832022006500
    DOI: 10.1016/j.ress.2022.109035
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832022006500
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2022.109035?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. Xia, Tangbin & Xi, Lifeng & Pan, Ershun & Ni, Jun, 2017. "Reconfiguration-oriented opportunistic maintenance policy for reconfigurable manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 87-98.
    2. Liu, Yu & Zhang, Qin & Ouyang, Zhiyuan & Huang, Hong-Zhong, 2021. "Integrated production planning and preventive maintenance scheduling for synchronized parallel machines," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    3. Gao, Guibing & Wang, Junshen & Yue, Wenhui & Ou, Wenchu, 2020. "Structural-vulnerability assessment of reconfigurable manufacturing system based on universal generating function," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    4. 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.
    5. Qin, Jinlei & Coolen, Frank P.A., 2022. "Survival signature for reliability evaluation of a multi-state system with multi-state components," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    6. Lu, Biao & Zhou, Xiaojun, 2017. "Opportunistic preventive maintenance scheduling for serial-parallel multistage manufacturing systems with multiple streams of deterioration," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 116-127.
    7. Chang, Ping-Chen & Lin, Yi-Kuei & Chiang, Yu-Min, 2019. "System reliability estimation and sensitivity analysis for multi-state manufacturing network with joint buffers––A simulation approach," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 103-109.
    8. Rachel Campos Sabioni & Joanna Daaboul & Julien Le Duigou, 2022. "Concurrent optimisation of modular product and Reconfigurable Manufacturing System configuration: a customer-oriented offer for mass customisation," International Journal of Production Research, Taylor & Francis Journals, vol. 60(7), pages 2275-2291, April.
    9. Eslami Baladeh, Aliakbar & Taghipour, Sharareh, 2022. "Reliability optimization of dynamic k-out-of-n systems with competing failure modes," Reliability Engineering and System Safety, Elsevier, vol. 227(C).
    10. Jones, B. & Jenkinson, I. & Yang, Z. & Wang, J., 2010. "The use of Bayesian network modelling for maintenance planning in a manufacturing industry," Reliability Engineering and System Safety, Elsevier, vol. 95(3), pages 267-277.
    11. Wang, Dan & Si, Shubin & Cai, Zhiqiang & Zhao, Jiangbin, 2021. "Reliability optimization of linear consecutive-k-out-of-n: F systems driven by reconfigurable importance," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    12. Prince Pal Singh & Jatinder Madan & Harwinder Singh, 2021. "Composite performance metric for product flow configuration selection of reconfigurable manufacturing system (RMS)," International Journal of Production Research, Taylor & Francis Journals, vol. 59(13), pages 3996-4016, July.
    13. Zhang, Yongjin & Zhao, Ming & Zhang, Yanjun & Pan, Ruilin & Cai, Jing, 2020. "Dynamic and steady-state performance analysis for multi-state repairable reconfigurable manufacturing systems with buffers," European Journal of Operational Research, Elsevier, vol. 283(2), pages 491-510.
    14. Zhao, Jiangbin & Si, Shubin & Cai, Zhiqiang, 2019. "A multi-objective reliability optimization for reconfigurable systems considering components degradation," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 104-115.
    15. Xia, Tangbin & Dong, Yifan & Xiao, Lei & Du, Shichang & Pan, Ershun & Xi, Lifeng, 2018. "Recent advances in prognostics and health management for advanced manufacturing paradigms," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 255-268.
    16. Sürücü, Barış & Sazak, Hakan S., 2009. "Monitoring reliability for a three-parameter Weibull distribution," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 503-508.
    17. Jeon, Jeasu & Sohn, So Young, 2015. "Product failure pattern analysis from warranty data using association rule and Weibull regression analysis: A case study," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 176-183.
    18. Jiang, R. & Murthy, D.N.P., 2009. "Impact of quality variations on product reliability," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 490-496.
    Full references (including those not matched with items on IDEAS)

    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. Sinisterra, Wilfrido Quiñones & Lima, Victor Hugo Resende & Cavalcante, Cristiano Alexandre Virginio & Aribisala, Adetoye Ayokunle, 2023. "A delay-time model to integrate the sequence of resumable jobs, inspection policy, and quality for a single-component system," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    2. Li, Yao & He, Yihai & Ai, Jun & Wang, Chengcheng & Han, Xiao & Liao, Ruoyu & Yang, Xiuzhen, 2022. "Functional health prognosis approach of multi-station manufacturing system considering coupling operational factors," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    3. Jiang, Junwei & An, Youjun & Dong, Yuanfa & Hu, Jiawen & Li, Yinghe & Zhao, Ziye, 2023. "Integrated optimization of non-permutation flow shop scheduling and maintenance planning with variable processing speed," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    4. Cheng, Guoqing & Li, Ling, 2020. "Joint optimization of production, quality control and maintenance for serial-parallel multistage production systems," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    5. Sabri-Laghaie, Kamyar & Fathi, Mahdi & Zio, Enrico & Mazhar, Maryam, 2022. "A novel reliability monitoring scheme based on the monitoring of manufacturing quality error rates," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    6. Liu, Mingli & Wang, Dan & Si, Shubin, 2023. "Mixed reliability importance-based solving algorithm design for the cost-constrained reliability optimization model," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    7. 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).
    8. Zhou, Xiaojun & Shi, Kailong, 2019. "Capacity failure rate based opportunistic maintenance modeling for series-parallel multi-station manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 46-53.
    9. 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.
    10. Zhao, Xian & Li, Rong & Cao, Shuai & Qiu, Qingan, 2023. "Joint modeling of loading and mission abort policies for systems operating in dynamic environments," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    11. Wang, Lin & Lu, Zhiqiang & Ren, Yifei, 2020. "Joint production control and maintenance policy for a serial system with quality deterioration and stochastic demand," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    12. 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).
    13. Dui, Hongyan & Tian, Tianzi & Zhao, Jiangbin & Wu, Shaomin, 2022. "Comparing with the joint importance under consideration of consecutive-k-out-of-n system structure changes," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    14. Chuan Wang & Yupeng Liu & Wen Hou & Chao Yu & Guorong Wang & Yuyan Zheng, 2021. "Reliability and availability modeling of Subsea Autonomous High Integrity Pressure Protection System with partial stroke test by Dynamic Bayesian," Journal of Risk and Reliability, , vol. 235(2), pages 268-281, April.
    15. Murthy, D.N.P. & Hagmark, P.-E. & Virtanen, S., 2009. "Product variety and reliability," Reliability Engineering and System Safety, Elsevier, vol. 94(10), pages 1601-1608.
    16. Yang, Zhisen & Yang, Zaili & Yin, Jingbo, 2018. "Realising advanced risk-based port state control inspection using data-driven Bayesian networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 38-56.
    17. Di Zhang & Xinping Yan & Zaili Yang & Jin Wang, 2014. "An accident data–based approach for congestion risk assessment of inland waterways: A Yangtze River case," Journal of Risk and Reliability, , vol. 228(2), pages 176-188, April.
    18. Azizi, Fariba & Salari, Nooshin, 2023. "A novel condition-based maintenance framework for parallel manufacturing systems based on bivariate birth/birth–death processes," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    19. Zaretalab, Arash & Sharifi, Mani & Guilani, Pedram Pourkarim & Taghipour, Sharareh & Niaki, Seyed Taghi Akhavan, 2022. "A multi-objective model for optimizing the redundancy allocation, component supplier selection, and reliable activities for multi-state systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    20. Ta, Yuntian & Li, Yanfeng & Cai, Wenan & Zhang, Qianqian & Wang, Zhijian & Dong, Lei & Du, Wenhua, 2023. "Adaptive staged remaining useful life prediction method based on multi-sensor and multi-feature fusion," Reliability Engineering and System Safety, Elsevier, vol. 231(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:231:y:2023:i:c:s0951832022006500. 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.