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System reliability of stochastic networks with multiple reworks

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  • Tina Song, Wheyming
  • Lin, Peisyuan

Abstract

An important performance measure for stochastic networks is so-called “network-system reliability†, defined as the probability that the production output meets a pre-determined demand for stochastic networks consisting of many workstations. Specifically, the random factors of stochastic networks include the capacity of each workstation and numbers of the conforming parts produced in each workstation. Previous work has studied analytical methods to determine network-system reliability, however a great deal of archive publications incorrectly analyzed network-system reliability. The error is caused by assuming continuous network flow, despite the model’s flow being discrete and indivisible.

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  • Tina Song, Wheyming & Lin, Peisyuan, 2018. "System reliability of stochastic networks with multiple reworks," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 258-268.
    • Handle: RePEc:eee:reensy:v:169:y:2018:i:c:p:258-268
    DOI: 10.1016/j.ress.2017.08.008
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    References listed on IDEAS

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    1. Wu, Wei-wei & Ning, Angelika & Ning, Xuan-xi, 2008. "Evaluation of the reliability of transport networks based on the stochastic flow of moving objects," Reliability Engineering and System Safety, Elsevier, vol. 93(6), pages 838-844.
    2. Wheyming Song & Bruce Schmeiser, 2011. "Displaying statistical point estimates using the leading-digit rule," IISE Transactions, Taylor & Francis Journals, vol. 43(12), pages 851-862.
    3. Yeh, Wei-Chang, 2008. "A simple minimal path method for estimating the weighted multi-commodity multistate unreliable networks reliability," Reliability Engineering and System Safety, Elsevier, vol. 93(1), pages 125-136.
    4. Wheyming T. Song & Bruce W. Schmeiser, 2009. "Omitting Meaningless Digits in Point Estimates: The Probability Guarantee of Leading-Digit Rules," Operations Research, INFORMS, vol. 57(1), pages 109-117, February.
    5. Rui Peng & Qingqinq Zhai & Liudong Xing & Jun Yang, 2016. "Reliability analysis and optimal structure of series-parallel phased-mission systems subject to fault-level coverage," IISE Transactions, Taylor & Francis Journals, vol. 48(8), pages 736-746, August.
    6. Dharmaraja, S. & Vinayak, Resham & Trivedi, Kishor S., 2016. "Reliability and survivability of vehicular ad hoc networks: An analytical approach," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 28-38.
    7. Lin, Yi-Kuei & Chang, Ping-Chen, 2012. "Evaluate the system reliability for a manufacturing network with reworking actions," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 127-137.
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    Cited by:

    1. Delia Montoro-Cazorla & Rafael Pérez-Ocón, 2022. "Analysis of k-Out-of-N-Systems with Different Units under Simultaneous Failures: A Matrix-Analytic Approach," Mathematics, MDPI, vol. 10(11), pages 1-13, June.
    2. Montoro-Cazorla, Delia & Pérez-Ocón, Rafael, 2018. "Constructing a Markov process for modelling a reliability system under multiple failures and replacements," Reliability Engineering and System Safety, Elsevier, vol. 173(C), pages 34-47.
    3. 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).
    4. Hao, Zhifeng & Yeh, Wei-Chang & Liu, Zhenyao & Forghani-elahabad, Majid, 2020. "General multi-state rework network and reliability algorithm," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    5. Yeh, Cheng-Ta & Lin, Yi-Kuei & Yeng, Louis Cheng-Lu & Huang, Pei-Tzu, 2021. "Reliability evaluation of a multistate railway transportation network from the perspective of a travel agent," Reliability Engineering and System Safety, Elsevier, vol. 214(C).

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