A distributed framework for the digitalization of Additive Manufacturing
Please login to view abstract download link
Additive Manufacturing (AM) has become a key technology in different manufacturing sectors. Characterized by its flexibility, it drives high customization of products while helping also in the achievement of important targets related with the sustainability of manufacturing processes by reducing materials waste or emissions. However, such degree of adaptability can be only achieved through the exploitation of knowledge that is materialized in large amounts of data. In the case of AM, this data results particularly complex to capture and handle due to its typical level of heterogeneity. The optimization of the caption and representation of this data results a key topic for the development of a digital representation of an AM process. Given that on such digital context, different data-driven procedures can be easily deployed, exploiting such information to optimize different phases of the AM process such as product design or process optimization. Here we present two specific software tools developed to address the optimization of data caption and visualization within the AM process of metallic parts. For that, we also introduce a specific data structure proposed with the intention of exploiting it for process optimization purposes. The combination of these tools can be used to address the integration of all the information from AM processes in industrial digital frameworks.