Abstract
Artificial intelligence (AI) is a crucial technology of industrial digitalization. Especially in the production industry, a great potential is present in optimizing existing processes, e.g., concerning resource consumption, emission reduction, process and product quality improvements, predictive maintenance, and so on. Some of this potential is addressed by methods of industrial analytics beyond specific production technology. Furthermore, particular technological aspects in production systems address another part of this potential, e.g., mechatronics, robotics and motion control, automation systems, and so on. The problem is that the field of AI includes many research areas and methods, and many companies are losing the overview of the necessary and appropriate methods for solving the company problems. The reasons for this are, on the one hand, a lack of expertise in AI and, on the other hand, high complexity and risks of use for the companies (especially for SMEs). As a result, many potentials cannot yet be exploited. The KI-NET project aims to fill this gap, whereby a project overview is presented in this contribution.
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Acknowledgements
The research reported in this paper has been funded by the European Interreg Austria-Bavaria project "KI-Net (AB292)". It has also been partly funded by BMK, BMDW, and the State of Upper Austria in the frame of the COMET Program managed by FFG.
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Freudenthaler, B., Martinez-Gil, J., Fensel, A., Höfig, K., Huber, S., Jacob, D. (2022). KI-Net: AI-Based Optimization in Industrial Manufacturing—A Project Overview. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2022. EUROCAST 2022. Lecture Notes in Computer Science, vol 13789. Springer, Cham. https://doi.org/10.1007/978-3-031-25312-6_65
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