Multi-objective optimization of cycle time and energy consumption in parallel robotic assembly lines using a discrete firefly algorithm

PurposeAssembly lines are one of the places where energy consumption is intensive in manufacturing enterprises. The use of robots in assembly lines not only increases productivity but also increases energy consumption and carbon emissions. The purpose of this paper is to minimize the cycle time and...

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Bibliographic Details
Published inEngineering computations Vol. 39; no. 6; pp. 2424 - 2448
Main Authors Soysal-Kurt, Halenur, İşleyen, Selçuk Kürşat
Format Journal Article
LanguageEnglish
Published Bradford Emerald Publishing Limited 07.06.2022
Emerald Group Publishing Limited
Subjects
Algorithms
Alliances
Assembly lines
Comparative studies
Costs
Cycle time
Energy consumption
Energy efficiency
Heuristic methods
Integer programming
Linear programming
Literature reviews
Manufacturers
Manufacturing
Mathematical models
Mathematical programming
Multiple objective analysis
Mutation
Optimization
Pareto optimization
Productivity
Robotics
Robots
Simulated annealing
Taguchi methods
Energy consumption
Multi-objective optimization
Parallel
Discrete firefly algorithm
Robotic assembly line balancing
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ISSN0264-4401
1758-7077
DOI10.1108/EC-12-2020-0747

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Summary:PurposeAssembly lines are one of the places where energy consumption is intensive in manufacturing enterprises. The use of robots in assembly lines not only increases productivity but also increases energy consumption and carbon emissions. The purpose of this paper is to minimize the cycle time and total energy consumption simultaneously in parallel robotic assembly lines (PRAL).Design/methodology/approachDue to the NP-hardness of the problem, A Pareto hybrid discrete firefly algorithm based on probability attraction (PHDFA-PA) is developed. The algorithm parameters are optimized using the Taguchi method. To evaluate the results of the algorithm, a multi-objective programming model and a restarted simulated annealing (RSA) algorithm are used.FindingsAccording to the comparative study, the PHDFA-PA has a competitive performance with the RSA. Thus, it is possible to achieve a sustainable PRAL through the proposed method by addressing the cycle time and total energy consumption simultaneously.Originality/valueTo the best knowledge of the authors, this is the first study addressing energy consumption in PRAL. The proposed method for PRAL is efficient in solving the multi-objective balancing problem.
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ISSN:0264-4401
1758-7077
DOI:10.1108/EC-12-2020-0747