Abstract
The research work aims at optimizing the energy costs in manufacturing industries. We pay particular attention to the use of energy in production processes and to the costs deriving from its consumption considering flexibility in machine selecting, job sequencing, idle machine and machine switching off-on operations. We formulate a flexible job shop scheduling model that minimizes costs due to energy consumption and considers a planning period where to schedule jobs. To test the optimization model, we consider a case study of a multinational corporate that operates in the manufacturing sector. The collected real data are related to process activities of heat exchangers products. The results show that the planning and scheduling of operations over a planning period is found in few seconds and that the costs due to the energy required for production is about 10% lower than the current production.
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Guido, R., Zangara, G., Ambrogio, G., Conforti, D. (2023). A Flexible Job Shop Scheduling Model for Sustainable Manufacturing. In: Cappanera, P., Lapucci, M., Schoen, F., Sciandrone, M., Tardella, F., Visintin, F. (eds) Optimization and Decision Science: Operations Research, Inclusion and Equity. ODS 2022. AIRO Springer Series, vol 9. Springer, Cham. https://doi.org/10.1007/978-3-031-28863-0_18
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DOI: https://doi.org/10.1007/978-3-031-28863-0_18
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