Abstract
A growing number of manufacturing companies organize their production in global production networks, which tend to show a high degree of complexity. Improving operational performance or managing risks like production breakdowns and delayed transportation between production plants is challenging in these complex systems. Literature proposes discrete event simulation as an adequate tool to support the management of network operations. Companies are currently not able to exploit the potential of the required large-scale simulations of production networks as the development process of these simulations is lengthy, challenging and cost-intensive. In this paper, we introduce a concept to use highly granular data originating from production and information systems to automate simulation model development and parametrization.
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Milde, M., Reinhart, G. (2022). Automated Model Development for the Simulation of Global Production Networks. In: Andersen, AL., et al. Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems. CARV MCPC 2021 2021. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-90700-6_53
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DOI: https://doi.org/10.1007/978-3-030-90700-6_53
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