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  4. Multi-objective optimization of transfer line balancing problem considering cycle time and energy expenditure
 
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Multi-objective optimization of transfer line balancing problem considering cycle time and energy expenditure

Citation Link: https://doi.org/10.15480/882.14071
Publikationstyp
Conference Paper
Date Issued
2024-05
Sprache
English
Author(s)
Petersen, Julian  
Produktionsmanagement und -technik M-18  
Nourmohammadi, Amir  
Fathi, Masood  
Burmeister, Carsten
TORE-DOI
10.15480/882.14071
TORE-URI
https://hdl.handle.net/11420/52658
Journal
Procedia CIRP  
Volume
130
Start Page
1378
End Page
1383
Citation
57th CIRP Conference on Manufacturing Systems 2024, CMS 2024
Contribution to Conference
57th CIRP Conference on Manufacturing Systems, CMS 2024  
Publisher DOI
2-s2.0-85213036004
Scopus ID
2-s2.0-85213036004
The transfer lines are among highly complex automated production systems that manufacture a large volume of identical or similar products with high demand. Recently, the design of environmentally friendly production systems has become the focus of more and more enterprises as one of the sustainable manufacturing strategies. In light of the recent energy-efficient manufacturing trends, this paper investigates the transfer line balancing problem (TLBP), considering both efficiency and energy aspects. The problem arises in the automated transfer lines equipped with dedicated machining centers and automated material handling systems, producing a large volume of specific products. The operations are performed at machines by realizing particular processing requirements, including machining features, inclusions, and exclusions considerations. The objectives to be minimized are the cycle time and the total energy consumption. The latter objective consists of machines’ operating and non-operating energy costs. The problem is first formulated as a mixed-integer linear programming model. Due to the problem’s complexity, an efficient multi-objective optimization algorithm based on the non-dominated sorting genetic algorithm (NSGA-II) is also proposed. The performance of the proposed algorithm is compared with the e-constraint method in terms of the Pareto-front metrics while solving various test problems and a case study. The computational results show the effectiveness of the proposed algorithm in dealing with the TLBP.
Subjects
transfer line balancing
energy expenditure
cycle time
mathematical model
multi-objective optimization
DDC Class
670: Manufacturing
Publication version
publishedVersion
Lizenz
https://creativecommons.org/licenses/by-nc-nd/4.0/
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