Improving the success rate in additive manufacturing and designing highly optimized structures require proper understanding of material behaviour. This study proposes a novel experimental method by which anisotropic mechanical properties of additively manufactured materials can be assessed. The procedure is based on tensile testing of flat specimens, manufactured by laser powder bed fusion (LPBF) at different orientations relative to the build plate. In this study, the procedure was applied to the Inconel 718 alloy. Three identical specimen sets were built, each of which received complementary postprocessing treatments. The tensile tests were carried out on specimens with as‐built surface finish. Digital image correlation was used to record the strain field evolution on two perpendicular surfaces of the tensile specimens under loading. An optimization algorithm is also proposed for determining the anisotropic elastic constants using only a few tensile test results. It was observed that both build orientation and postprocessing have strong influence on the anisotropic mechanical properties of the material. The effect of microstructure was also investigated and characterised. Consequently, three transversely isotropic compliance matrices were constructed, representing the effect of the different processing conditions.

This paper aims to introduce the ideas of practical implications of using industrial robots to implement additive/hybrid manufacturing. The process is discussed and briefly demonstrated. This paper also introduces recent developments on human–machine interface for robotic manufacturing cells, namely the ones used for additive/hybrid manufacturing, as well as interoperability methods between the computer-aided design (CAD) data and material modeling systems. It is presented – using a few solutions developed by the authors – as a set of conceptual guidelines discussed throughout the paper and as a way to demonstrate how they can be applied and their practical implications. The possibility to program the system from CAD information, which is argued to be crucial, is explored, and the methods necessary for connecting the CAD data to material modeling systems are introduced. This paper also discusses in detail the main requirements (also from a system point-of-view) needed for a full implementation of the presented ideas and methods. A few simulations to better characterize the interactions from heat conduction and physical metallurgy were conducted in an effort to better tune the additive manufacturing process. The results demonstrate how the toolpath planning and deposition strategies can be extracted and studied from a CAD model. The paper fully demonstrates the possibility to use a robotic setup for additive manufacturing applications and shows the first steps of an innovative system designed with that objective. Using the aimed platform, unsupervised net-shaping of complex components will substitute the cumbersome processes, and it is expected that such a visionary concept brings about a significant reduction in cost, energy consumption, lead time and production waste through the introduction of optimized and interactive processes. This can be considered as a breakthrough in the field of manufacturing and metal processing as the performance is indicated to increase significantly compared to the current instruction-dependent methods.