IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v199y2020ics0951832017308244.html
   My bibliography  Save this article

Reliability analysis for a hybrid flow shop with due date consideration

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832017308244
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2017.07.008?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. 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.
    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. 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.

    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. Bai, Guanghan & Zuo, Ming J. & Tian, Zhigang, 2015. "Search for all d-MPs for all d levels in multistate two-terminal networks," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 300-309.
    2. Forghani-elahabad, Majid & Mahdavi-Amiri, Nezam, 2015. "An efficient algorithm for the multi-state two separate minimal paths reliability problem with budget constraint," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 472-481.
    3. Niu, Yi-Feng, 2021. "Performance measure of a multi-state flow network under reliability and maintenance cost considerations," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    4. Lin, Yi-Kuei & Huang, Cheng-Fu & Chang, Ping-Chen, 2013. "System reliability evaluation of a touch panel manufacturing system with defect rate and reworking," Reliability Engineering and System Safety, Elsevier, vol. 118(C), pages 51-60.
    5. Liu, Tao & Bai, Guanghan & Tao, Junyong & Zhang, Yun-An & Fang, Yining & Xu, Bei, 2022. "Modeling and evaluation method for resilience analysis of multi-state networks," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    6. 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.
    7. Niu, Yi-Feng & Gao, Zi-You & Lam, William H.K., 2017. "A new efficient algorithm for finding all d-minimal cuts in multi-state networks," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 151-163.
    8. Yeh, Wei-Chang & Tan, Shi-Yi & Zhu, Wenbo & Huang, Chia-Ling & Yang, Guang-yi, 2022. "Novel binary addition tree algorithm (BAT) for calculating the direct lower-bound of the highly reliable binary-state network reliability," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    9. Niu, Yi-Feng & Gao, Zi-You & Lam, William H.K., 2017. "Evaluating the reliability of a stochastic distribution network in terms of minimal cuts," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 100(C), pages 75-97.
    10. Paweł Marcin Kozyra, 2020. "Analysis of minimal path and cut vectors in multistate monotone systems and use it for detection of binary type multistate monotone systems," Journal of Risk and Reliability, , vol. 234(5), pages 686-695, October.
    11. Fan Yang & Roel Leus, 2021. "Scheduling hybrid flow shops with time windows," Journal of Heuristics, Springer, vol. 27(1), pages 133-158, April.
    12. Lin, Yi-Kuei & Fiondella, Lance & Chang, Ping-Chen, 2013. "Quantifying the impact of correlated failures on system reliability by a simulation approach," Reliability Engineering and System Safety, Elsevier, vol. 109(C), pages 32-40.
    13. Niu, Yi-Feng & Zhao, Xia & Xu, Xiu-Zhen & Zhang, Shi-Yun, 2023. "Reliability assessment of a stochastic-flow distribution network with carbon emission constraint," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    14. Yi-Kuei Lin & Hsien-Chang Chou & Ping-Chen Chang, 2017. "Reliability and sensitivity analysis for a banking company transmission system," Journal of Risk and Reliability, , vol. 231(2), pages 146-154, April.
    15. Yong Wang & Yuting Wang & Yuyan Han, 2023. "A Variant Iterated Greedy Algorithm Integrating Multiple Decoding Rules for Hybrid Blocking Flow Shop Scheduling Problem," Mathematics, MDPI, vol. 11(11), pages 1-25, May.
    16. Yeh, Wei-Chang, 2024. "A new hybrid inequality BAT for comprehensive all-level d-MP identification using minimal paths in Multistate Flow Network reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    17. Kozyra, Paweł Marcin, 2023. "The usefulness of (d,b)-MCs and (d,b)-MPs in network reliability evaluation under delivery or maintenance cost constraints," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    18. Zhi Li & Ray Y. Zhong & Ali Vatankhah Barenji & J. J. Liu & C. X. Yu & George Q. Huang, 2021. "Bi-objective hybrid flow shop scheduling with common due date," Operational Research, Springer, vol. 21(2), pages 1153-1178, June.
    19. Li, Daqing & Zhang, Qiong & Zio, Enrico & Havlin, Shlomo & Kang, Rui, 2015. "Network reliability analysis based on percolation theory," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 556-562.
    20. Forghani-elahabad, Majid & Kagan, Nelson & Mahdavi-Amiri, Nezam, 2019. "An MP-based approximation algorithm on reliability evaluation of multistate flow networks," Reliability Engineering and System Safety, Elsevier, vol. 191(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:199:y:2020:i:c:s0951832017308244. 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.