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Enabling Mass Customization and Manufacturing Sustainability in Industry 4.0 Context: A Novel Heuristic Algorithm for in-Plant Material Supply Optimization

Author

Listed:
  • Masood Fathi

    (Department of Production and Automation Engineering, University of Skövde, SE-541 28 Skövde, Sweden)

  • Morteza Ghobakhloo

    (Department of Industrial Engineering, Minab Higher Education Center, University of Hormozgan, Bandar Abbas 79177, Iran)

Abstract

The fourth industrial revolution and the digital transformation of consumer markets require contemporary manufacturers to rethink and reshape their business models to deal with the ever-changing customer demands and market turbulence. Manufacturers nowadays are inclined toward product differentiation strategies and more customer-focused approaches to stay competitive in the Industry 4.0 environment, and mass customization and product diversification are among the most commonly implemented business models. Under such circumstances, an economical material supply to assembly lines has become a significant concern for manufacturers. Consequently, the present study deals with optimizing the material supply to mixed-model assembly lines that contribute to the overall production cost efficiency, mainly via the reduction of both the material transportation and material holding costs across production lines, while satisfying certain constraints. Given the complexity of the problem, a novel two-stage heuristic algorithm is developed in this study to enable a cost-efficient delivery. To assess the efficiency and effectiveness of the proposed heuristic algorithm, a set of test problems are solved and compared against the best solution found by a commercial solver. The results of the comparison reveal that the suggested heuristic provides reasonable solutions, thus offering immense opportunities for production cost efficiency and manufacturing sustainability under the mass customization philosophy.

Suggested Citation

  • Masood Fathi & Morteza Ghobakhloo, 2020. "Enabling Mass Customization and Manufacturing Sustainability in Industry 4.0 Context: A Novel Heuristic Algorithm for in-Plant Material Supply Optimization," Sustainability, MDPI, vol. 12(16), pages 1-15, August.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:16:p:6669-:d:400469
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    References listed on IDEAS

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    Cited by:

    1. Basile, Vincenzo & Tregua, Marco & Giacalone, Massimiliano, 2024. "A three-level view of readiness models: Statistical and managerial insights on industry 4.0," Technology in Society, Elsevier, vol. 77(C).
    2. Caiming Zhang & Yong Chen & Hong Chen & Dazhi Chong, 2024. "Industry 4.0 and its Implementation: a Review," Information Systems Frontiers, Springer, vol. 26(5), pages 1773-1783, October.
    3. Fawaz M. Abdullah & Abdulrahman M. Al-Ahmari & Saqib Anwar, 2023. "Analyzing Interdependencies among Influencing Factors in Smart Manufacturing," Sustainability, MDPI, vol. 15(4), pages 1-19, February.
    4. Yuli Liang & Snigdha Rangineni & Chuanlan Liu, 2022. "Fashion or Function: Examining Consumers' Perceived Values of Mass-Customized Menswear via a Content Mining Approach," International Journal of Business Analytics (IJBAN), IGI Global, vol. 9(6), pages 1-18, October.
    5. Sam Solaimani & Alireza Parandian & Nabi Nabiollahi, 2021. "A Holistic View on Sustainability in Additive and Subtractive Manufacturing: A Comparative Empirical Study of Eyewear Production Systems," Sustainability, MDPI, vol. 13(19), pages 1-17, September.

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