Sobottka, T., Kamhuber, F., Rössler, M., & Sihn, W. (2017). Hybrid simulation-based optimization of discrete parts manufacturing to increase energy efficiency and productivity. In Proceedings of 15th Global Conference on Sustainable Manufacturing (pp. 413–420). Elsevier. https://doi.org/10.1016/j.promfg.2018.02.139
E330-02 - Forschungsbereich Betriebstechnik, Systemplanung und Facility Management
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Erschienen in:
Proceedings of 15th Global Conference on Sustainable Manufacturing
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Band:
21
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Datum (veröffentlicht):
2017
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Veranstaltungsname:
15th Global Conference on Sustainable Manufacturing
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Veranstaltungszeitraum:
25-Sep-2017 - 27-Sep-2017
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Veranstaltungsort:
Haifa, Israel
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Umfang:
8
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Verlag:
Elsevier
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Peer Reviewed:
Ja
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Keywords:
Artificial Intelligence; optimization; Industrial and Manufacturing Engineering; case study; energy efficiency; metaheuristics; production planning; hybrid simulation; sustainable manufacturing
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Abstract:
This presented research comprises the development of an optimization module for use in a novel production optimization tool - similar in function but not mode of operation to an Advanced Planning System -, with energy efficiency incorporated into its goal system. The optimization features a hybrid-simulation of production systems as an evaluation function. A hybrid simulation has been developed and presented in preceding publications, in order to enable a sufficient consideration of interactions between material flow and the thermal-physical behavior of the production system. The size of the search space for the complex optimization problem necessitates a customized two-phase-optimization method, which is based on a Genetic Algorithm, with the consideration of linear constraints and extended customizations. The results, obtained in a case study featuring a food production facility, show energy savings of around 20 percent together with significant productivity gains.
