Abstract
Between the recent advances in manufacturing engineering stands Tailored Forming, a process chain that produces massive hybrid material components through the use of different forming techniques. The motivation behind such a process is the achievement of higher performance parts, such as lightweight or local integrated functions. Thereby, new restrictions take place in the design of these parts, requiring the implementation of a suitable multi-material design methodology to attend user requirements. One of these new challenges is the design of the joining zone between the two metals, which presents limited controllability during the manufacturing process. With this objective, here is proposed the use of a Case Based Reasoning (CBR) system as design method. For that, a parametric model is created and, through an interface between CAD and finite element systems, a solution space is generated and analyzed, forming the first case-base. A comparison analysis of these results is executed, bringing valuable information for the current research. At the end, a similarity method is implemented in order to propose the most suitable solution among all variations based on specified requirements. With that, this tool will support the user on the creation of new cases and the machine learning process on storing the knowledge.
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Acknowledgment
The results presented in this paper were obtained under the umbrella of Collaborative Research Centre 1153 “Process Chain for Manufacturing Hybrid High Performance Components by Tailored Forming”, preliminary inspection project C2. The authors would like to thank the German Research Foundation (DFG) and the CRC 1153 for its financial and organizational support.
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Siqueira, R., Bibani, M., Mozgova, I., Lachmayer, R. (2019). Case-Based Parametric Analysis: A Method for Design of Tailored Forming Hybrid Material Component. In: Świątek, J., Borzemski, L., Wilimowska, Z. (eds) Information Systems Architecture and Technology: Proceedings of 39th International Conference on Information Systems Architecture and Technology – ISAT 2018. ISAT 2018. Advances in Intelligent Systems and Computing, vol 853. Springer, Cham. https://doi.org/10.1007/978-3-319-99996-8_2
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