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Modelling of flexible manufacturing system: a review

Author

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  • Anupma Yadav
  • S.C. Jayswal

Abstract

A flexible manufacturing system (FMS) due to its ability of being flexible in nature is concerned with automatic production of different parts in medium range. In short, it can be regarded as an automated manufacturing system. In this paper, an insight on previous work in the area of FMS modelling has been provided with an overview of research and development for better understanding of FMS. It serves as a medium for investigation of work that are accomplished by using different modelling techniques in FMS like mathematical, artificial intelligence, hierarchical, multi criteria decision-making method, Petri Nets and simulation. This paper will help researchers who are keen to do research in the area of FMS modelling, by highlighting contribution of available techniques in the field of FMS. It will also help them in deciding which modelling techniques can be used for a given problem. At last, comparison of different parameters considered in the recent papers of modelling FMS has been provided in the form of Table, along with a clear vision related to those works that still need to be investigated.

Suggested Citation

  • Anupma Yadav & S.C. Jayswal, 2018. "Modelling of flexible manufacturing system: a review," International Journal of Production Research, Taylor & Francis Journals, vol. 56(7), pages 2464-2487, April.
    • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:7:p:2464-2487
    DOI: 10.1080/00207543.2017.1387302
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    Citations

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    Cited by:

    1. Santosh Kumar Srivastava & Surajit Bag, 2023. "Recent Developments on Flexible Manufacturing in the Digital Era: A Review and Future Research Directions," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(4), pages 483-516, December.
    2. Delorme, Xavier & Cerqueus, Audrey & Gianessi, Paolo & Lamy, Damien, 2023. "RMS balancing and planning under uncertain demand and energy cost considerations," International Journal of Production Economics, Elsevier, vol. 261(C).
    3. Kinkel, Steffen & Capestro, Mauro & Di Maria, Eleonora & Bettiol, Marco, 2023. "Artificial intelligence and relocation of production activities: An empirical cross-national study," International Journal of Production Economics, Elsevier, vol. 261(C).
    4. Chris Turner & John Oyekan, 2023. "Manufacturing in the Age of Human-Centric and Sustainable Industry 5.0: Application to Holonic, Flexible, Reconfigurable and Smart Manufacturing Systems," Sustainability, MDPI, vol. 15(13), pages 1-29, June.
    5. Guo, Daqiang & Li, Mingxing & Lyu, Zhongyuan & Kang, Kai & Wu, Wei & Zhong, Ray Y. & Huang, George Q., 2021. "Synchroperation in industry 4.0 manufacturing," International Journal of Production Economics, Elsevier, vol. 238(C).
    6. Mohd. Shaaban Hussain & Mohammed Ali, 2019. "A Multi-agent Based Dynamic Scheduling of Flexible Manufacturing Systems," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 20(3), pages 267-290, September.
    7. Simon Li & Bahareh Eshragh & Akposeiyifa Joseph Ebufegha, 2023. "Simulation-Based Study of the Resilience of Flexible Manufacturing Layouts Subject to Uncertain Demands of Product Variants," Sustainability, MDPI, vol. 15(20), pages 1-20, October.
    8. Sandhya Dixit & Suman Gothwal & Tilak Raj, 2022. "A LAPTOP methodology to evaluate the transition of CMS into FMS: a case study," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 516-534, February.
    9. Luo, Kaiping & Shen, Guangya & Li, Liheng & Sun, Jianfei, 2023. "0-1 mathematical programming models for flexible process planning," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1160-1175.

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