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A new method of design for additive manufacturing including machining constraints

Abstract : Metal additive manufacturing is a major field of study and innovation. In almost every industry, a lot of effort goes into modelizing and optimizing designs in order to minimize global mass. In this context, despite all efforts, metal additive manufacturing, especially SLM, still produces parts generally considered as raw parts with some surfaces still needing to be machined in order to obtain the required geometrical quality. Despite sometimes, great complexity and cost, the machining stage is never taken into account in the design process, especially during the topological optimization approach. This paper proposes a new design for the additive manufacturing method in order to optimize the design stage and takes into account topological optimization machining as well as geometrical and mechanical constraints. The machining constraints are initially integrated as forces and functional surfaces, but also as the result of a topological optimization loop, in order to find the best possiblemounting solution for machining. It is shown on a typical aeronautic part that machining forcesmay be indeed the greatest forces during the part’s lifetime. Using two different topological optimization software, i.e. Inspire and Abaqus Tosca, the paper illustrates that it is possible to take into account most of the machining constraints to only slightly modify the initial design and thus simplify the machining stage and reduce cost and possible failure during machining.
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Submitted on : Thursday, October 15, 2020 - 1:02:21 PM
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Vincent Benoist, Lionel Arnaud, Maher Baili. A new method of design for additive manufacturing including machining constraints. International Journal of Advanced Manufacturing Technology, Springer Verlag, 2020, 111 (1-2), pp.25-36. ⟨10.1007/s00170-020-06059-2⟩. ⟨hal-02968044⟩



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