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 possible mounting solution for machining. It is shown on a typical aeronautic part that machining forces may 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.
Metal additive manufacturing is an active eld of innova-tion, but for Selective Laser Melting (SLM), supports removal is a major constraint. For this technology, supports are strongly welded to the part, to tightly maintain the part and avoid distortion and also to evacuate the thermal load. Supports are usually optimized for their manual removal but machining is often applied and need to be more often used in order to improve post-processing produc-tivity. This paper proposes a full methodological approach to optimize the selection of the cutting parameters, cutting tools and the type of supports itself. The aim is to help the additive manufacturer to nd among the numerous wide supports designs, the ones that would reduce the cost of machining, in terms of machining time and cutting tools degradation. This approach can also be used for the optimization of the design of lattice structures for their structures. Our results show that among the 11 designs tested, the honey-comb and squared pattern grid supports are the most e ciently machined, using the 8 teeth tangential milling among the 3 tools tested, with a good post machined surface roughness and tool's health. The method takes into account low magni cation optical analysis and an accelerometer sensor, easy to use even for SME. This paper also proposes and analyzes with this method a new kind of porous support.
Metal additive manufacturing is an active field of innova- tion, but for Selective Laser Melting (SLM), supports removal is a major constraint. For this technology, supports are strongly welded to the part, to tightly maintain the part and avoid distortion and also to evacuate the thermal load. Supports are usually optimized for their manual removal but machining is often applied and need to be more often used in order to improve post-processing produc- tivity. This paper proposes a full methodological approach to optimize the selection of the cutting parameters, cutting tools and the type of supports itself. The aim is to help the additive manufacturer to find among the numerous wide supports designs, the ones that would reduce the cost of machining, in terms of machining time and cutting tools degradation. This approach can also be used for the optimization of the design of lattice structures for their structures. Our results show that among the 11 designs tested, the honey- comb and squared pattern grid supports are the most efficiently machined, using the 8 teeth tangential milling among the 3 tools tested, with a good post machined surface roughness and tool’s health. The method takes into account low magnification optical analysis and an accelerometer sensor, easy to use even for SME. This paper also proposes and analyzes with this method a new kind of porous support.
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