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Mathematical model for robotic two-sided assembly line balancing problem with zoning constraints

Author

Listed:
  • Ashish Yadav

    (PDPM Indian Institute of Information Technology Design and Manufacturing Jabalpur)

  • Sunil Agrawal

    (PDPM Indian Institute of Information Technology Design and Manufacturing Jabalpur)

Abstract

In, the recent scenario, the utilization of robots in different areas such as packaging, loading/unloading, transportation, and especially assembly lines enhance the productivity of production systems. The increasing interest of customers in customized products and full fill customer demand within time is a challenge for the companies to balance and configure their robotic assembly line more efficient and effective than ever before. Robotic two-sided assembly line balancing problem (RTALBP) generally occurs in plants producing high volume, large-sized products, where there is a process of installing more than one robot on every single station of the assembly line for manufacturing the product. The main aim of this paper is to develop a new mathematical model with the objective of workload maximization on each workstation that directly minimizes the number of workstations when cycle time is fixed. Robotic two-sided assembly line balancing problem is well known NP-hard problem that’s why an exact solution approach is proposed to solve the problem. In this paper, real-life assembly line balancing based production case study data is collected, and a proposed mathematical model is applied to get a feasible solution. Benchmark problem and production case study problem is solved using a branch and bound algorithm on Lingo 16 solver. Computational results indicated proper allocation of robots and reduce the number of robots which indirectly increased efficiency and save cost and space for assembling the products.

Suggested Citation

  • Ashish Yadav & Sunil Agrawal, 2022. "Mathematical model for robotic two-sided assembly line balancing problem with zoning constraints," 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 395-408, February.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:1:d:10.1007_s13198-021-01284-8
    DOI: 10.1007/s13198-021-01284-8
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    References listed on IDEAS

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    1. Borba, Leonardo & Ritt, Marcus & Miralles, Cristóbal, 2018. "Exact and heuristic methods for solving the Robotic Assembly Line Balancing Problem," European Journal of Operational Research, Elsevier, vol. 270(1), pages 146-156.
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    3. Boysen, Nils & Fliedner, Malte & Scholl, Armin, 2008. "Assembly line balancing: Which model to use when," International Journal of Production Economics, Elsevier, vol. 111(2), pages 509-528, February.
    4. Becker, Christian & Scholl, Armin, 2006. "A survey on problems and methods in generalized assembly line balancing," European Journal of Operational Research, Elsevier, vol. 168(3), pages 694-715, February.
    5. Levitin, Gregory & Rubinovitz, Jacob & Shnits, Boris, 2006. "A genetic algorithm for robotic assembly line balancing," European Journal of Operational Research, Elsevier, vol. 168(3), pages 811-825, February.
    6. .Ilker Baybars, 1986. "A Survey of Exact Algorithms for the Simple Assembly Line Balancing Problem," Management Science, INFORMS, vol. 32(8), pages 909-932, August.
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    Cited by:

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    3. Hemant Sharma & Nagendra Sohani & Ashish Yadav, 2023. "A fuzzy SWARA-WASPAS based approach for determining the role of lean practices in enabling the supply chain agility," 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. 14(1), pages 492-511, March.

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