Abstract
AbstractIntroducing distributed computing paradigms to the manufacturing domain increases the difficulty of designing and planning an appropriate IT infrastructure. This paper proposes a model and solution approach addressing the conjoint application and IT resource placement problem in a factory context. Instead of aiming to create an exact model, resource requirements and capabilities are simplified, focusing on usability in the planning and design phase for industrial use cases. Three objective functions are implemented: minimizing overall cost, environmental impact, and the number of devices. The implications of edge and fog computing are considered in a multi-layer model by introducing five resource placement levels ranging from on-device, within the production system, within the production section, within the factory (on-premise), to the cloud (off-premise). The model is implemented using the open-source modeling language Pyomo. The solver SCIP is used to solve the NP-hard integer programming problem. For the evaluation of the optimization implementation a benchmark is created using a sample set of scenarios varying the number of possible placement locations, applications, and the distribution of assigned edge recommendations. The resulting execution times demonstrate the viability of the proposed approach for small (100 applications; 100 locations) and large (1000 applications, 1000 scenarios) instances. A case study for a section of a factory producing electronic components demonstrates the practical application of the proposed approach.
Funder
Technische Universität Braunschweig
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Industrial and Manufacturing Engineering,Software
Reference35 articles.
1. Aazam, M., Zeadally, S., & Harras, K. A. (2018). Deploying Fog computing in industrial internet of things and industry 4.0. IEEE Transactions on Industrial Informatics, 14(10), 4674–4682. https://doi.org/10.1109/TII.2018.2855198
2. Basir, R., Qaisar, S., Ali, M., Aldwairi, M., Ashraf, M. I., Mahmood, A., & Gidlund, M. (2019). Fog computing enabling industrial Internet of Things: State-of-the-art and research challenges. Sensors, 19(21), 4807. https://doi.org/10.3390/s19214807
3. Beitinger, G. (2021). Digitalization and automation are the game-changers. https://ingenuity.siemens.com/2021/03/digitalization-and-automation-are-the-game-changers/
4. Brettel, M., Klein, M., & Friederichsen, N. (2016). The relevance of manufacturing flexibility in the context of Industrie 4.0. Procedia CIRP, 41, 105–110. https://doi.org/10.1016/j.procir.2015.12.047
5. Chen, B., Wan, J., Celesti, A., Li, D., Abbas, H., & Zhang, Q. (2018). Edge computing in IoT-based manufacturing. IEEE Communications Magazine, 56(9), 103–109. https://doi.org/10.1109/MCOM.2018.1701231
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