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Towards decision-support for reconfigurable manufacturing systems based on Computational Design Synthesis

The efficiency of production systems has great impact on the profitability in the automotive industry. Recent trends such as increasing part variety and lower part volumes challenge traditional manufacturing concepts and promote the adoption of more flexible approaches. Reconfigurable manufacturing systems have key characteristics that make them a potential solution for the prevalent issues. Decision makers can change the configuration of the manufacturing system to respond to changing requirements, however they have a lot of possibilities to configure the system. Therefore, they are confronted with a new challenge, which is to make the right decisions on the configuration of the system. Help can be provided by building a knowledge model of the system design processes and their variables. After this, an algorithm can be used to synthesize system configurations and analyze their performances. This is called Computational Design Synthesis (CDS) and can help to generate an overview of the solution space (configurations and performances). This way, CDS supports the decision maker in exploring the generated range of design solutions by making trade-offs for many key performance indicators concurrently by generating sets of feasible solutions that can later be narrowed down by design constraints. In this paper an investigation is proposed that explores the role of Computational Design Synthesis tools to support decision-making in the design of reconfigurable manufacturing systems and to show potential benefits of applying this design support approach.

Authors: J. Unglert, S. Hoekstra, J. Jauregui-Becker, F.J.A.M. van Houten
University of Twente
Conference: CIRP Conference on Manufacturing Systems
Audience: Academic + Industrial
Size: 200+ participants
Worldwide

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