IDEAS home Printed from https://ideas.repec.org/a/gam/jlogis/v8y2024i2p62-d1416220.html
   My bibliography  Save this article

Optimal Strategy of Unreliable Flexible Production System Using Information System

Author

Listed:
  • Sadok Rezig

    (UFR Mathématiques, Informatique, Mécanique et Automatique, Département Science pour l’ingénieur, Université de Lorraine, F-57070 Metz, France)

  • Sadok Turki

    (UFR Mathématiques, Informatique, Mécanique et Automatique, Département Science pour l’ingénieur, Université de Lorraine, F-57070 Metz, France)

  • Ayoub Chakroun

    (UFR Mathématiques, Informatique, Mécanique et Automatique, Département Science pour l’ingénieur, Université de Lorraine, F-57070 Metz, France)

  • Nidhal Rezg

    (UFR Mathématiques, Informatique, Mécanique et Automatique, Département Science pour l’ingénieur, Université de Lorraine, F-57070 Metz, France)

Abstract

Background : Optimization approaches and a models can be applied for critical production systems that experience equipment failure, repair delays and product quality control in order to maximize the total profit. We can cite, as an example, flexible manufacturing systems. Methods : Our methodology involves developing a decision model integrated with an information system to coordinate various system operations, ensuring timely response to customer requests. The module of the information system is provided to optimally manage the production flow and parts ordering according to machine availability. The objective is to determine the optimal order thresholds of part batches that maximize the total profit. Results : Numerical results are provided to analyze the influence of system reliability and uncertainty on decision variables, offering insights into the system’s performance and robustness. By using our method, the advancement of the flexible production systems is carried out by addressing key operational challenges and optimizing production processes for enhanced efficiency and profitability. Conclusions : To achieve this, an optimization algorithm is employed to identify optimal solutions that enhance profitability.

Suggested Citation

  • Sadok Rezig & Sadok Turki & Ayoub Chakroun & Nidhal Rezg, 2024. "Optimal Strategy of Unreliable Flexible Production System Using Information System," Logistics, MDPI, vol. 8(2), pages 1-18, June.
    • Handle: RePEc:gam:jlogis:v:8:y:2024:i:2:p:62-:d:1416220
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2305-6290/8/2/62/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2305-6290/8/2/62/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, P. Patrick & Wilson, George R., 1994. "Approximations for the mean and variance of the throughput of flexible manufacturing cells," International Journal of Production Economics, Elsevier, vol. 37(2-3), pages 275-284, December.
    2. Wahab, M.I.M. & Wu, Desheng & Lee, Chi-Guhn, 2008. "A generic approach to measuring the machine flexibility of manufacturing systems," European Journal of Operational Research, Elsevier, vol. 186(1), pages 137-149, April.
    3. Savsar, Mehmet & Aldaihani, Majid, 2008. "Modeling of machine failures in a flexible manufacturing cell with two machines served by a robot," Reliability Engineering and System Safety, Elsevier, vol. 93(10), pages 1551-1562.
    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. Mohamed Dia & Amirmohsen Golmohammadi & Pawoumodom M. Takouda, 2020. "Relative Efficiency of Canadian Banks: A Three-Stage Network Bootstrap DEA," JRFM, MDPI, vol. 13(4), pages 1-25, April.
    2. Wahab, M.I.M. & Stoyan, S.J., 2008. "A dynamic approach to measure machine and routing flexibilities of manufacturing systems," International Journal of Production Economics, Elsevier, vol. 113(2), pages 895-913, June.
    3. E. Borgonovo & L. Peccati, 2011. "Managerial insights from service industry models: a new scenario decomposition method," Annals of Operations Research, Springer, vol. 185(1), pages 161-179, May.
    4. Cenk Sahin & Melek Demirtas & Rizvan Erol & Adil Baykasoğlu & Vahit Kaplanoğlu, 2017. "A multi-agent based approach to dynamic scheduling with flexible processing capabilities," Journal of Intelligent Manufacturing, Springer, vol. 28(8), pages 1827-1845, December.
    5. Behzad Karimi & Seyed Taghi Akhavan Niaki & Amir Hossein Niknamfar & Mahsa Gareh Hassanlu, 2021. "Multi-objective optimization of job shops with automated guided vehicles: A non-dominated sorting cuckoo search algorithm," Journal of Risk and Reliability, , vol. 235(2), pages 306-328, April.
    6. Seebacher, Gottfried & Winkler, Herwig, 2014. "Evaluating flexibility in discrete manufacturing based on performance and efficiency," International Journal of Production Economics, Elsevier, vol. 153(C), pages 340-351.
    7. Tamayo-Torres, Javier & Gutierrez-Gutierrez, Leopoldo & Ruiz-Moreno, Antonia, 2014. "The relationship between exploration and exploitation strategies, manufacturing flexibility and organizational learning: An empirical comparison between Non-ISO and ISO certified firms," European Journal of Operational Research, Elsevier, vol. 232(1), pages 72-86.
    8. Olivella, Jordi & Corominas, Albert & Pastor, Rafael, 2010. "An entropy-based measurement of working time flexibility," European Journal of Operational Research, Elsevier, vol. 200(1), pages 253-260, January.
    9. Fawaz Abdulmalek & Mehmet Savsar & Majid M. Aldaihani, 2012. "Design of experiments for the analysis of the effects of pallet arrival patterns and maintenance policies on FMC productivity," International Journal of Applied Management Science, Inderscience Enterprises Ltd, vol. 4(1), pages 91-106.
    10. Chang, An-Yuan, 2009. "An attribute approach to the measurement of machine-group flexibility," European Journal of Operational Research, Elsevier, vol. 194(3), pages 774-786, May.
    11. Liang, Zhenglin & Liu, Bin & Xie, Min & Parlikad, Ajith Kumar, 2020. "Condition-based maintenance for long-life assets with exposure to operational and environmental risks," International Journal of Production Economics, Elsevier, vol. 221(C).
    12. Sabri-Laghaie, Kamyar & Karimi-Nasab, Mehdi, 2019. "Random search algorithms for redundancy allocation problem of a queuing system with maintenance considerations," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 144-162.
    13. Chou, Mabel C. & Chua, Geoffrey A. & Teo, Chung-Piaw, 2010. "On range and response: Dimensions of process flexibility," European Journal of Operational Research, Elsevier, vol. 207(2), pages 711-724, December.
    14. Akber Aman Shah & Desheng Wu & Vladmir Korotkov, 2019. "Are Sustainable Banks Efficient and Productive? A Data Envelopment Analysis and the Malmquist Productivity Index Analysis," Sustainability, MDPI, vol. 11(8), pages 1-19, April.

    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:gam:jlogis:v:8:y:2024:i:2:p:62-:d:1416220. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.