OPTIMAL LOT-SIZING DECISIONS WITH INTEGRATED PURCHASING, MANUFACTURING AND ASSEMBLING FOR REMANUFACTURING SYSTEMS

This work applies fuzzy sets to the integration of purchasing, manufacturing and assembling of production planning decisions with multiple suppliers, multiple components and multiple machines in remanufacturing systems. The developed fuzzy multi-objective linear programming model (FMOLP) simultaneou...

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Vydané v:Iranian journal of fuzzy systems (Online) Ročník 15; číslo 3; s. 1
Hlavný autor: Su, Tai-Sheng
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Zahedan University of Sistan and Baluchestan, Iranian Journal of Fuzzy Systems 01.06.2018
Predmet:
Decision making
Fuzzy sets
Linear programming
Production planning
Remanufacturing
ISSN:1735-0654, 2676-4334
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Shrnutí:This work applies fuzzy sets to the integration of purchasing, manufacturing and assembling of production planning decisions with multiple suppliers, multiple components and multiple machines in remanufacturing systems. The developed fuzzy multi-objective linear programming model (FMOLP) simultaneously minimizes total costs, total $\text{CO}_2$ emissions and total lead time with reference to customer demand, due date, supplier/manufacturer capacity, lot-size release and machine yield. The proposed FMOLP model provides a recoverable remanufacturing framework that facilitates fuzzy decision-making, enabling the decision maker (DM) to adjust interactively the membership function or parameters during the solution procedure to obtain a preferred and satisfactory solution. To test the model, it was implemented in various scenarios with a remanufacturing production system. The analytical results in this work can help planner by enabling systematic analysis of the cost-effectiveness of remanufacturing systems and their potential for improving $\text{CO}_2$ emissions and lead time in terms of remanufacturing planning. Future investigations may apply the related patterns of non-linear membership functions to develop an actual remanufacturing planning decision.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:1735-0654
2676-4334
DOI:10.22111/ijfs.2018.3946