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Reliability analysis for a hybrid flow shop with due date consideration

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  • Lin, Yi-Kuei
  • Huang, Ding-Hsiang

Abstract

For a hybrid flow-shop (HFS), the number of machines in a stage presents multiple levels because of maintenance, partial failures, unexpected failures, etc. In other words, it is suitable that the capacity of each stage is regarded as a stochastic component. Reliability reveals the performance of an HFS under the stochastic capacity, while certain demand and due date are required. In this paper, the reliability is defined as the probability that an HFS with stochastic capacity can satisfy the makespan for the demand within the due date. We first transform the HFS with stochastic capacity into a multistate hybrid flow-shop network. An efficient algorithm is then proposed to derive an estimated interval for the reliability based on a pair of capacity vectors, which are generated from two estimated demand levels. Two practical cases, including a tile production system and a footwear production system, are presented to demonstrate how the estimated interval is obtained and to investigate efficiency and accuracy of the proposed algorithm. The reliability can be regarded as a quality indicator to understand the capability of the real-world HFS and to guarantee whether the demand can be completed within the desire due date.

Suggested Citation

  • Lin, Yi-Kuei & Huang, Ding-Hsiang, 2020. "Reliability analysis for a hybrid flow shop with due date consideration," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
  • Handle: RePEc:eee:reensy:v:199:y:2020:i:c:s0951832017308244
    DOI: 10.1016/j.ress.2017.07.008
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    References listed on IDEAS

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    1. Lin, Yi-Kuei & Yeh, Cheng-Ta, 2011. "Maximal network reliability for a stochastic power transmission network," Reliability Engineering and System Safety, Elsevier, vol. 96(10), pages 1332-1339.
    2. Huseby, Arne B. & Natvig, Bent, 2013. "Discrete event simulation methods applied to advanced importance measures of repairable components in multistate network flow systems," Reliability Engineering and System Safety, Elsevier, vol. 119(C), pages 186-198.
    3. Shijin Wang & Ming Liu & Chengbin Chu, 2015. "A branch-and-bound algorithm for two-stage no-wait hybrid flow-shop scheduling," International Journal of Production Research, Taylor & Francis Journals, vol. 53(4), pages 1143-1167, February.
    4. Ruiz, Rubén & Vázquez-Rodríguez, José Antonio, 2010. "The hybrid flow shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 205(1), pages 1-18, August.
    5. José Ramirez-Marquez & Claudio Rocco, 2010. "Evolutionary optimization technique for multi-state two-terminal reliability allocation in multi-objective problems," IISE Transactions, Taylor & Francis Journals, vol. 42(8), pages 539-552.
    6. Figielska, Ewa, 2014. "A heuristic for scheduling in a two-stage hybrid flowshop with renewable resources shared among the stages," European Journal of Operational Research, Elsevier, vol. 236(2), pages 433-444.
    7. Azadeh, A. & Maleki Shoja, B. & Ghanei, S. & Sheikhalishahi, M., 2015. "A multi-objective optimization problem for multi-state series-parallel systems: A two-stage flow-shop manufacturing system," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 62-74.
    8. Joseph C. Hudson & Kailash C. Kapur, 1985. "Reliability Bounds for Multistate Systems with Multistate Components," Operations Research, INFORMS, vol. 33(1), pages 153-160, February.
    9. Yan, Zhou & Qian, Meng, 2007. "Improving efficiency of solving d-MC problem in stochastic-flow network," Reliability Engineering and System Safety, Elsevier, vol. 92(1), pages 30-39.
    10. Yeh, Wei-Chang & Bae, Changseok & Huang, Chia-Ling, 2015. "A new cut-based algorithm for the multi-state flow network reliability problem," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 1-7.
    11. 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.
    12. Schneider, Kellie & Rainwater, Chase & Pohl, Ed & Hernandez, Ivan & Ramirez-Marquez, Jose Emmanuel, 2013. "Social network analysis via multi-state reliability and conditional influence models," Reliability Engineering and System Safety, Elsevier, vol. 109(C), pages 99-109.
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    Cited by:

    1. Huang, Cheng-Hao & Lin, Yi-Kuei, 2024. "Rescue and safety system development and performance evaluation by network reliability," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    2. 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).
    3. Mei Li & Gai-Ge Wang & Helong Yu, 2021. "Sorting-Based Discrete Artificial Bee Colony Algorithm for Solving Fuzzy Hybrid Flow Shop Green Scheduling Problem," Mathematics, MDPI, vol. 9(18), pages 1-30, September.

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