Efforts have been made and reported in literature to successfully build AM parts and understand the interaction between the processing parameters and the resulting microstructures and mechanical properties of such parts.
However, these studies are very often limited to a functional set of processing parameters, that limit the knowledge about the full potential of AM processes. There is therefore a need to carry on the exploration of such processes, in particular to propose complete maps, for determining the best set of process parameters for any given application.

A precise understanding of process parameters (depending on both machine and AM process used) is a key challenge to produce parts with a defects-free microstructure and an interesting mechanical behaviour.

In this way, we propose to study the influence of the process used and its corresponding settings on the mechanical performance of produced parts. In this framework, a previous PhD has been conducted on the influence of AM process (SLM and DED-LP) on the microstructure, tensile and fatigue behaviour of TA6V parts. An ongoing project studies the dynamic compressive response of 316L architected materials made with DED-LP.

Beyond purely materials considerations, it is also a key challenge to address economic, environmental and social impacts aspects of AM processes to ensure the sustainability of companies. Economic aspects of sustainability are mainly defined as manufacturing costs; environmental aspects are linked to energy and material efficiency, waste and emission reduction; while social aspects
focus on employees, customers and communities. Nowadays, little attention has been given to this topic, especially for environmental aspects.

Besides potential benefits provided by AM processes (component upgrade, on-demand manufacturing…), issues, such as energy consumption, generation of waste, emissions of particles, need to be considered to assess if adoption of AM technologies in production is a suitable solution.

In this research line, we propose a multidisciplinary approach (mechanical and industrial engineering) to improve the knowledge on AM technologies. The scientific main objective is to develop decision support systems for assisting the choice of an AM process.

Existing industrial relationships and regional network (Addimalliance) will be an asset to carry out this research work, especially to define user needs and requirements.