Optimizing Mixed-Model Synchronous Assembly Lines with Bipartite Sequence-Dependent Setup Times in Advanced Manufacturing
Author:
Varyani Asieh1ORCID, Salehi Mohsen2ORCID, Heydari Gharahcheshmeh Meysam3
Affiliation:
1. Department of Mechanical, Industrial, and Manufacturing Engineering, Oregon State University, SW Monroe Avenue, Corvallis, OR 97331, USA 2. Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan 6517838623, Iran 3. Department of Mechanical Engineering, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182, USA
Abstract
In advanced manufacturing, optimizing mixed-model synchronous assembly lines (MMALs) is crucial for enhancing productivity and adhering to sustainability principles, particularly in terms of energy consumption and energy-efficient sequencing. This paper introduces a novel approach by categorizing sequence-dependent setup times into bipartite categories: workpiece-independent and workpiece-dependent. This strategic division streamlines assembly processes, reduces idle times, and decreases energy consumption through more efficient machine usage. A new mathematical model is proposed to minimize the intervals at which workpieces are launched on an MMAL, aiming to reduce operational downtime that typically leads to excessive energy use. Given the Non-deterministic Polynomial-time hard (NP-hard) nature of this problem, a genetic algorithm (GA) is developed to efficiently find solutions, with performance compared against the traditional branch and bound technique (B&B). This method enhances the responsiveness of MMALs to variable production demands and contributes to energy conservation by optimizing the sequence of operations to align with energy-saving objectives. Computational experiments conducted on small and large-sized problems demonstrate that the proposed GA outperforms the conventional B&B method regarding solution quality, diversity level, and computational time, leading to energy reductions and enhanced cost-effectiveness in manufacturing settings.
Reference81 articles.
1. Renna, P., and Materi, S. (2021). A literature review of energy efficiency and sustainability in manufacturing systems. Appl. Sci., 11. 2. Gielen, D., Gorini, R., Wagner, N., Leme, R., Gutierrez, L., Prakash, G., Asmelash, E., Janeiro, L., Gallina, G., and Vale, G. (2019). Global Energy Transformation: A Roadmap to 2050, International Renewable Energy Agency. 3. Effectiveness of carbon dioxide emission target is linked to country ambition and education level;Zheng;Commun. Earth Environ.,2024 4. Engaging with energy reduction: Does a climate change frame have the potential for achieving broader sustainable behaviour?;Spence;J. Environ. Psychol.,2014 5. Akerman, P., Cazzola, P., Christiansen, E.S., Van Heusden, R., Kolomanska-van Iperen, J., Christensen, J., Crone, K., Dawe, K., De Smedt, G., and Keynes, A. (2020). Reaching Zero with Renewables, International Renewable Energy Agency.
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