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

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 differentiatio...

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Bibliographic Details
Published inSustainability Vol. 12; no. 16; p. 6669
Main Authors Fathi, Masood, Ghobakhloo, Morteza
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.08.2020
Subjects
Algorithms
Assembly lines
Business competition
Customers
Customization
Efficiency
Heuristic
heuristic algorithm
Industry 4.0
inplant material supply
Logistics
Manufacturers
Manufacturing
mass customization
Mathematical models
mixed-model assembly line
Optimization
Product differentiation
Production and Automation Engineering
Production lines
Produktion och automatiseringsteknik
Scheduling
Supermarkets
Sustainability
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Summary: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.
ISSN:2071-1050
2071-1050
DOI:10.3390/su12166669