Scientific cooperation in additive manufacturing for robust control of the value chain

Description of the scientific and technological objectives for the exercise:

1) To generate the necessary scientific knowledge in the selected additive manufacturing technologies: Powder Bed Manufacture (PB) and Direct Energy Deposition (DED), in order to address the actual industrialization of the process, considering the different stages or processes of the entire value chain. Currently, these technologies are being used industrially to manufacture prototypes or small batches, but the viability of the result (due to the lack of control over the numerous variables involved throughout the entire value chain) makes the efficiency very low, with numerous trial-and-error experiments.

2) Analyze the influence of different process variables—those affecting raw material characteristics, procedural variables, and those affecting main and auxiliary systems—throughout the entire value chain of Selective Laser Melting (SLM) and Binder Jetting (both Powder Bed technologies), Laser Metal Deposition (LMD) and Wire Arc Additive Manufacturing (WAMM) (both DED technologies), and FDM (Factory Deposition Modeling), to ensure the robustness of the entire process and define a safe processing range to facilitate standardization.

3) Define standards, criteria, and best practice guidelines to guarantee process and product quality. This involves generating ad-hoc raw material criteria or specifications for additive manufacturing technologies, optimizing post-processing treatments to create best practice guidelines, and determining the properties of the final products and the evaluation methods for assessing these properties, among other things.

4) Create digital standards to ensure traceability and quality throughout the processes involved in the value chain of the Additive Manufacturing technologies selected in this project. Having a system or platform capable of acquiring, storing, and managing a large amount of data and information related to the variables of the different processes in the value chain is essential.