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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
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. (Produktion och automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0001-5530-3517
Department of Industrial Engineering, Minab Higher Education Center, University of Hormozgan, Bandar Abbas, Iran.
2020 (English)In: Sustainability, E-ISSN 2071-1050, Vol. 12, no 16, p. 1-15, article id 6669Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
MDPI, 2020. Vol. 12, no 16, p. 1-15, article id 6669
Keywords [fo]
mass customization, Industry 4.0, heuristic algorithm, mixed-model assembly line, inplant material supply
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-18929DOI: 10.3390/su12166669ISI: 000578968300001Scopus ID: 2-s2.0-85089803784OAI: oai:DiVA.org:his-18929DiVA, id: diva2:1458971
Projects
This research was funded by the KK-stiftelsen (Knowledge Foundation, Stockholm, Sweden) for the ProSpekt 2018 project OPTION.
Funder
Knowledge Foundation
Note

CC BY 4.0

Available from: 2020-08-18 Created: 2020-08-18 Last updated: 2022-02-10Bibliographically approved

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Fathi, Masood

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