IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i22p2919-d680635.html
   My bibliography  Save this article

A Comprehensive Fuzzy Decision-Making Method for Minimizing Completion Time in Manufacturing Process in Supply Chains

Author

Listed:
  • Fahad Kh. A.O.H. Alazemi

    (Department of Mechanical and Manufacturing Engineering, Universiti Putra Malaysia, Serdang 43400, Malaysia)

  • Mohd Khairol Anuar Bin Mohd Ariffin

    (Department of Mechanical and Manufacturing Engineering, Universiti Putra Malaysia, Serdang 43400, Malaysia)

  • Faizal Bin Mustapha

    (Department of Mechanical and Manufacturing Engineering, Universiti Putra Malaysia, Serdang 43400, Malaysia)

  • Eris Elianddy bin Supeni

    (Department of Mechanical and Manufacturing Engineering, Universiti Putra Malaysia, Serdang 43400, Malaysia)

Abstract

In manufacturing firms, there are many factors that can affect product completion time in production lines. However, in a real production environment, such factors are uncertain and increase the adverse effects on product completion time. This research focuses on the role of internal factors in small- and medium-scale supply chains in developing countries, enhancing product completion time during the manufacturing process in fuzzy conditions. In the first step of this research, a list of factors was found clustered into six main groups: technology, human resources, machinery, material, facility design, and social factors. In the next step, fuzzy weights of each group factor were determined by a fuzzy inference system to reflect the uncertainty of the factors in utilizing product completion time. Then, a hybrid fuzzy–TOPSIS-based heuristic is proposed to generate and select the best production alternative. The outcomes showed that the proposed method could generate and select the alternative with a 10.13% lower product completion time. The findings also indicated that using the proposed fuzzy method will cause less minimum variance compared to the crisp mode.

Suggested Citation

  • Fahad Kh. A.O.H. Alazemi & Mohd Khairol Anuar Bin Mohd Ariffin & Faizal Bin Mustapha & Eris Elianddy bin Supeni, 2021. "A Comprehensive Fuzzy Decision-Making Method for Minimizing Completion Time in Manufacturing Process in Supply Chains," Mathematics, MDPI, vol. 9(22), pages 1-39, November.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:22:p:2919-:d:680635
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/22/2919/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/22/2919/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tommaso Rossi & Rossella Pozzi & Margherita Pero & Roberto Cigolini, 2017. "Improving production planning through finite-capacity MRP," International Journal of Production Research, Taylor & Francis Journals, vol. 55(2), pages 377-391, January.
    2. Hadi Mokhtari & Ali Salmasnia, 2015. "An Evolutionary Clustering-Based Optimization to Minimize Total Weighted Completion Time Variance in a Multiple Machine Manufacturing System," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 14(05), pages 971-991.
    3. Aidin Delgoshaei & Mohd Khairol Anuar Ariffin & Ahad Ali, 2017. "A multi-period scheduling method for trading-off between skilled-workers allocation and outsource service usage in dynamic CMS," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 997-1039, February.
    4. Houssem Felfel & Omar Ayadi & Faouzi Masmoudi, 2017. "Pareto Optimal Solution Selection for a Multi-Site Supply Chain Planning Problem Using the VIKOR and TOPSIS Methods," International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), IGI Global, vol. 8(3), pages 21-39, July.
    5. Gansterer, Margaretha & Almeder, Christian & Hartl, Richard F., 2014. "Simulation-based optimization methods for setting production planning parameters," International Journal of Production Economics, Elsevier, vol. 151(C), pages 206-213.
    6. Stephen C. Graves, 2011. "Uncertainty and Production Planning," International Series in Operations Research & Management Science, in: Karl G. Kempf & Pınar Keskinocak & Reha Uzsoy (ed.), Planning Production and Inventories in the Extended Enterprise, chapter 0, pages 83-101, Springer.
    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. Aidin Delgoshaei & Mohd Khairol Anuar Bin Mohd Ariffin & Zulkiflle B. Leman, 2022. "An Effective 4–Phased Framework for Scheduling Job-Shop Manufacturing Systems Using Weighted NSGA-II," Mathematics, MDPI, vol. 10(23), pages 1-28, December.

    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. Haeussler, S. & Stampfer, C. & Missbauer, H., 2020. "Comparison of two optimization based order release models with fixed and variable lead times," International Journal of Production Economics, Elsevier, vol. 227(C).
    2. Laurent Lim, Lâm & Alpan, Gülgün & Penz, Bernard, 2014. "Reconciling sales and operations management with distant suppliers in the automotive industry: A simulation approach," International Journal of Production Economics, Elsevier, vol. 151(C), pages 20-36.
    3. Romauch, Martin & Hartl, Richard F., 2017. "Capacity planning for cluster tools in the semiconductor industry," International Journal of Production Economics, Elsevier, vol. 194(C), pages 167-180.
    4. Sabet, Ehsan & Yazdani, Baback & Kian, Ramez & Galanakis, Kostas, 2020. "A strategic and global manufacturing capacity management optimisation model: A Scenario-based multi-stage stochastic programming approach," Omega, Elsevier, vol. 93(C).
    5. Alireza Pooya & Morteza Pakdaman, 2019. "Optimal control model for finite capacity continuous MRP with deteriorating items," Journal of Intelligent Manufacturing, Springer, vol. 30(5), pages 2203-2215, June.
    6. Milne, R. John & Mahapatra, Santosh & Wang, Chi-Tai, 2015. "Optimizing planned lead times for enhancing performance of MRP systems," International Journal of Production Economics, Elsevier, vol. 167(C), pages 220-231.
    7. Feng, Yanling & Li, Guo & Sethi, Suresh P., 2018. "A three-layer chromosome genetic algorithm for multi-cell scheduling with flexible routes and machine sharing," International Journal of Production Economics, Elsevier, vol. 196(C), pages 269-283.
    8. Houda Ghamlouch & Mitra Fouladirad & Antoine Grall, 2019. "The use of real option in condition-based maintenance scheduling for wind turbines with production and deterioration uncertainties," Post-Print hal-02365402, HAL.
    9. Dávid Gyulai & András Pfeiffer & László Monostori, 2017. "Robust production planning and control for multi-stage systems with flexible final assembly lines," International Journal of Production Research, Taylor & Francis Journals, vol. 55(13), pages 3657-3673, July.
    10. Fangzhou Yan & Huaxin Qiu & Dongya Han, 2023. "Lagrangian Heuristic for Multi-Depot Technician Planning of Product Distribution and Installation with a Lunch Break," Mathematics, MDPI, vol. 11(3), pages 1-22, January.
    11. Diaz, Juan Esteban & Handl, Julia & Xu, Dong-Ling, 2018. "Integrating meta-heuristics, simulation and exact techniques for production planning of a failure-prone manufacturing system," European Journal of Operational Research, Elsevier, vol. 266(3), pages 976-989.
    12. Aidin Delgoshaei & Mohd Khairol Anuar Bin Mohd Ariffin & Zulkiflle B. Leman, 2022. "An Effective 4–Phased Framework for Scheduling Job-Shop Manufacturing Systems Using Weighted NSGA-II," Mathematics, MDPI, vol. 10(23), pages 1-28, December.
    13. Xide Zhu & Peijun Guo, 2020. "Bilevel programming approaches to production planning for multiple products with short life cycles," 4OR, Springer, vol. 18(2), pages 151-175, June.
    14. Mohtashami, Zahra & Bozorgi-Amiri, Ali & Tavakkoli-Moghaddam, Reza, 2021. "A two-stage multi-objective second generation biodiesel supply chain design considering social sustainability: A case study," Energy, Elsevier, vol. 233(C).
    15. Gonçalves, João N.C. & Sameiro Carvalho, M. & Cortez, Paulo, 2020. "Operations research models and methods for safety stock determination: A review," Operations Research Perspectives, Elsevier, vol. 7(C).
    16. Cannas, Violetta G. & Gosling, Jonathan & Pero, Margherita & Rossi, Tommaso, 2019. "Engineering and production decoupling configurations: An empirical study in the machinery industry," International Journal of Production Economics, Elsevier, vol. 216(C), pages 173-189.
    17. Antoine Trad, 2021. "The Business Transformation Framework and Enterprise Architecture Framework for Managers in Business Innovation: An Applied Holistic Mathematical Model," International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), IGI Global, vol. 12(1), pages 142-181, January.
    18. Dmitry Ivanov & Richard Hartl & Alexandre Dolgui & Alexander Pavlov & Boris Sokolov, 2015. "Integration of aggregate distribution and dynamic transportation planning in a supply chain with capacity disruptions and the ripple effect consideration," International Journal of Production Research, Taylor & Francis Journals, vol. 53(23), pages 6963-6979, December.
    19. Shishvan, Masoud Soleymani & Benndorf, Jörg, 2019. "Simulation-based optimization approach for material dispatching in continuous mining systems," European Journal of Operational Research, Elsevier, vol. 275(3), pages 1108-1125.
    20. Barros, Júlio & Cortez, Paulo & Carvalho, M. Sameiro, 2021. "A systematic literature review about dimensioning safety stock under uncertainties and risks in the procurement process," Operations Research Perspectives, Elsevier, vol. 8(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:gam:jmathe:v:9:y:2021:i:22:p:2919-:d:680635. 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.