The SCALDATA project, developed by CiTD and Elliot Cloud with the support of the Smart City Cluster, reaches its final stretch
Currently, the distribution of defects in a printed part is obtained thanks to non-destructive inspection methods such as tomography or x-ray, being necessary to reach minimum resolutions to be able to detect defects that could be critical for the proper functioning of the part. This process is inefficient in cost and time and often leads to the discarding of parts after the expensive manufacturing, machining or other post-process and inspection processes.
The SCALDATA project, approved within the line of Digital Technologies Projects of the Call for Aid to Innovative Business Groups 2022 (AEI) promoted by the Ministry of Industry, Tourism and Commerce of the Government of Spain; proposes the use of artificial intelligence to generate predictions for the typology, location and effect of defects in parts produced in additive manufacturing processes of metal powder bed.
This type of advanced manufacturing process has many advantages both from the point of view of material saving and design optimization. However, there are still many factors that prevent the adoption of such technology, especially the appearance of defects in manufactured parts, since defects are generally unpredictable, random and difficult to detect.
For all the above, the results of the SCALDATA project contribute to the implementation of this type of manufacturing technologies, which allow the production of optimized parts, reducing the material and energy necessary for production processes.
