Additive manufacturing is gaining importance in different industries, being on the verge to broad industrial application. Especially in laser beam melting (LBM) of metals, support structures play a vital role in the successful production of parts, since they are responsible for supporting overhanging features and preventing warpage. Today, these support structures are often massive and lead to high postprocessing effort for removal and surface finishing. Existing structures do not meet the needs of the individual part, adding cost to the production of additive parts without even fulfilling all their respective tasks. To reduce the manufacturing and finishing effort in LBM, new ways of support structure application have to be found. One way to decrease the material consumption, and therefore the overall costs in terms of raw material and manufacturing effort, is to use topology optimization for the generation of support structures. This study presents an extension of the current approaches, which take into account the task of supporting overhanging features, by using a finite element analysis of the manufacturing process of LBM to assess the loads applied to the support structures by residual stresses during the manufacturing process. This is critical especially to the LBM of metals. A case study of a cantilever beam is carried out to investigate the general validity of the proposed procedure. First, a simulation of the manufacturing process of the cantilever as well as the respective support structures is conducted. Second, using the simulation's results as input, topology optimization of the support structures by applying the solid isotropic material with penalization method is executed. The result, resembling tree-like features, demonstrates the capabilities of the procedure and points out the possibility of using variable densities within one structure. Finally, critical needs in research to further develop the approach are pointed out.

Additive manufacturing (AM) as a highly digitalized manufacturing technology is capable of the implementation of the concept of the digital twin (DT), which promises highly automated and optimized part production. Since the DT is a quite novel concept requiring a wide framework of various technologies, it is not state of the art yet, though. Especially the combination with artificial intelligence (AI) methods is still challenging. Applying the methodology of the systematic review, the state of the art regarding the DT in AM with emphasis of required technologies and current challenges is assessed. Furthermore, the topic of AI is investigated focusing the main applications in AM as well as the possibility to integrate today’s approaches into a DT environment.

This paper presents a five-step design methodology to generate designs of biomimetic structural components from topology optimization results. In step one, all material allocated by topology optimization is classified as either beam like structures or nodes to generate an auxiliary model consisting of preserved regions, cylindrical beams, and ball nodes, which is an abstraction of the original topology optimization result. In step two, the auxiliary model is exposed to the original boundary conditions in a finite element analysis. Then, internal forces, torsion, and bending moments in all beams of the auxiliary model are identified with respect to both of their ends. In step three, a database is used to find a suitable biomimetic beam for each previously analyzed beam in the auxiliary model. In step four, adapted nodes are designed to connect the biomimetic beams and preserved regions to generate an intermediate biomimetic component design. And in step five, a design iteration and a validation of the final design are performed. The design methodology allows for reproducible bio-mimetic component designs, a trackable and easily documentable component development process, and the possibility of automating the design process to ultimately save development costs when designing structural components.

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