Abstract
Implementing a virtual production system is challenging. Production systems are constrained by different dynamical market changes and characterised by complex general and machine specific interactions, uncertainties and unknowns. These complications make predicting the behaviour by any deterministic computer model not only inaccurate but sometimes misleading, e.g. if the range of a model’s applicability is not sufficiently well identified. Thus it is crucial to implement a virtual production system that supports learning from data and existing knowledge in the iterative design of models and their range of applicability—such a systematic design approach integrates real versus virtual data with digital versus human creativity and intelligence. The theory of design oriented thinking adapted for manufacturing favours fast iteration in digitised design cycles instead of optimisation in one step, offers knowledge exploration using intuitively operating intelligent tools, enhances interactive communication and learning capabilities, finally leading to a concept called Virtual Production Intelligence. Making data accessible to creativity by Meta-Modelling and visualisation techniques are the fundamental and functional parts of such a concept respectively.
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Acknowledgements
The authors would like to thank the German Research Association DFG for the kind support within the Cluster of Excellence “Integrative Production Technology for High-Wage Countries” of RWTH Aachen University.
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Schulz, W. (2017). Meta-Modelling and Visualisation of Multi-dimensional Data for Virtual Production Intelligence. In: Dowden, J., Schulz, W. (eds) The Theory of Laser Materials Processing. Springer Series in Materials Science, vol 119. Springer, Cham. https://doi.org/10.1007/978-3-319-56711-2_12
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