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research-article

Optimizing energy consumption in a decentralized manufacturing system

[+] Author and Article Information
Rebecca Ilsen

Institute for Manufacturing Technology and Production Systems University of Kaiserslautern Kaiserslautern, Germany
publications.fbk@mv.uni-kl.de

Hermann Meissner

Institute for Manufacturing Technology and Production Systems University of Kaiserslautern Kaiserslautern, Germany
hermann.meissner@mv.uni-kl.de

Jan C. Aurich

Institute for Manufacturing Technology and Production Systems University of Kaiserslautern Kaiserslautern, Germany
jan.aurich@mv.uni-kl.de

1Corresponding author.

ASME doi:10.1115/1.4034585 History: Received September 29, 2015; Revised August 10, 2016

Abstract

The deployment of modern information and communication technologies within manufacturing systems leads to the creation of so called cyber-physical production systems that consist of intelligent interconnected production facilities. One of the expected features of cyber-physical production systems is found to be the capability of self-organization and decentralized process planning in manufacturing. To determine the functionality as well as the benefit of different self-organization concepts a virtual test field for the simulation of manufacturing systems is implemented based on a multi-agent system modeling concept. Special focus is laid on the impact on energy consumption of the machine tools in the different scenarios. The presented simulation approach is applied to a manufacturing system for discrete part production in a job shop. Focus is centered on the process planning, especially the machine tool selection. The comparison of different strategies for machine tool selection of the product agents shows the potential of energy reduction in manufacturing by a product driven process planning concept that is based on communication between machine tools and product orders. Results of several simulations runs indicate that rather the flexible mixture of different selection criteria than the use of one single criterion leads to good performance of the overall system.

Copyright (c) 2016 by ASME
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