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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

1
Department of Production and Automation Engineering, University of Skövde, SE-541 28 Skövde, Sweden
2
Department of Industrial Engineering, Minab Higher Education Center, University of Hormozgan, Bandar Abbas 79177, Iran
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(16), 6669; https://doi.org/10.3390/su12166669
Received: 30 June 2020 / Revised: 3 August 2020 / Accepted: 13 August 2020 / Published: 18 August 2020
(This article belongs to the Section Energy Sustainability)
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. View Full-Text
Keywords: mass customization; Industry 4.0; heuristic algorithm; mixed-model assembly line; in-plant material supply mass customization; Industry 4.0; heuristic algorithm; mixed-model assembly line; in-plant material supply
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Fathi, M.; Ghobakhloo, M. Enabling Mass Customization and Manufacturing Sustainability in Industry 4.0 Context: A Novel Heuristic Algorithm for in-Plant Material Supply Optimization. Sustainability 2020, 12, 6669.

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