Additive Manufacturing (AM) is the forefront of advanced manufacturing technologies and has the potential to revolutionize manufacturing, with a dramatic change in the design and project paradigms. A comprehensive review of existent metal AM processes, processable materials, respective defects and inspection methods (destructive and non-destructive) is presented in a succinct manner. Particularly, the AM design optimization methodologies are reviewed and their threats and constraints discussed. Finally, an aerospace industry case study is presented and several cost-effective examples are enumerated.

The potential of Additive Manufacturing (AM) is high, with a whole new set of manufactured parts with unseen complexity being offered. However, the process has limitations, and for the sake of economic competitiveness, these should also be considered. Therefore, a computational methodology, capable of including the referenced limitations and providing initial solid designs for Selective Laser Melting (SLM) is the subject of the present work. The combination of Topology Optimization (TO) with the simplified fabrication model is the selected methodology. Its formulation, implementation, and integration on the classic TO algorithm is briefly discussed, being capable of addressing the minimum feature size and the overhang constraint limitations. Moreover, the performance and numerical stability of the methodology is evaluated, and numerical variables, such as the accuracy of structural equilibrium equations and the material interpolation model, are considered. A comparative study between these variables is presented. The paper then proposes an enhanced version of the selected methodology, with a better convergence towards a discrete solution.

The potential of additive layer manufacturing (ALM) is high, with a whole new set of manufacturable parts with unseen complexity being offered. Moreover, the combination of topology optimization (TO) with ALM has brought mutual advantages. However, the transition between TO and ALM is a nontrivial step that requires a robust methodology. Thus, the purpose of this work is to evaluate the capabilities of adopting the commonly used Laplacian smoothing methodology as the bridging tool between TO and ALM. Several algorithms are presented and compared in terms of efficiency and performance. Most importantly, a different concept of Laplacian smoothing is presented as well as a set of metrics to evaluate the performance of the algorithms, with the advantages and disadvantages of each algorithm being discussed. In the end, the proposed mutable diffusion Laplacian algorithm is presented and exhibits less volume shrinkage and shows better preservation of some geometrical features such as thin members and edges. Moreover, a new volume constraint is presented, decreasing the resulting structural changes in the presented geometry and improving the final mesh quality.