Abstract

Both the number of additive manufacturing processes as well as the materials available have developed rapidly in recent years. The additive manufacturing offers new possibilities in comparison to conventional methods, which have to be taken into account already during the design process. This includes especially the design freedom, which allows the manufacturing of very complex shapes. In addition, the integration of functions and components simplifies the assembly and thus also reduces costs. Furthermore, particularly light structures can be developed using lightweight materials. In order to use these numerous requirements and freedoms in the design process, topology optimization is an appropriate option. Therefore, in this contribution, a method is developed that optimizes topology optimization for additive manufacturing. Using the case study of an assembly of a humanoid robot, which has until now been conventionally manufactured and assembled, it can be shown how the process steps of the topology optimization can be implemented taking into account the special requirements from the additive manufacturing process. The goal in this example is to reduce the number of components and the necessary bolted joints. In addition, the weight of the entire assembly is to be reduced to facilitate the movement of the humanoid robot. It can be shown how the integration of components and functions makes it possible to optimize the geometries and to replace unfavorable bolted joints. Moreover, the influence of different materials and their anisotropy on the result of the topology optimization are also demonstrated. To this end, both conventional and lightweight construction materials, which were specially developed for additive manufacturing, were examined. By comparison with a conventional design, the advantages of topology optimization can be demonstrated clearly. These include, in particular, the successful reduction of the weight and the strain energy with respect to the installation space and the applied forces.

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