Generative Engineering and Design – A Comparison of Different Approaches to Utilize Artificial Intelligence in CAD Software Tools

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Abstract

There are new CAD software tools emerging that will likely pave the way to next generation engineering design. They are labelled Generative Engineering, Generative Design, Algorithm Based Design, Simulation Based Design or similar. Those new tools have in common that they make intensive use of Artificial Intelligence methods and extensive computing power. The focus of these algorithm-driven approaches to developing products and finding solutions is not the explicit creation of geometry but rather the definition of constraints, boundary conditions, rules and procedures that allow the computation of feasible solutions including the implicit generation of geometric models. One major idea is to initially open up wide solution spaces that are goal-oriented based on given requirements and provide engineers with all relevant information to perform trade-off studies and create new and innovative solutions instead of perpetuating existing solutions. The new tools are often associated with topology optimization and generative manufacturing, but the concepts go far beyond and lead to a complete workflow in the creation of products. The paper systematically analyses different software tools and shows that Generative Design and Engineering is interpreted and implemented differently by various software vendors, all pursuing different goals. In addition to the potentials, the paper mainly shows the current limitations of the implemented approaches in the different CAD tools. The focus is not only on the design phase, but also on how the tools take into account different aspects such as the automation of the entire development process, cost evaluation and manufacturing processes.

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Gerhard, D., Köring, T., & Neges, M. (2023). Generative Engineering and Design – A Comparison of Different Approaches to Utilize Artificial Intelligence in CAD Software Tools. In IFIP Advances in Information and Communication Technology (Vol. 667 IFIP, pp. 206–215). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-25182-5_21

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