Emo is a Slovenian SME specialising in the production of tools and dies for the automobile industry. As part of its production process, which uses laser-based metal deposition techniques, Emo needs to to gather and interpret the various process parameters. This results in significant volumes of data. The objective of this case study is to process these data (thermal high-speed image sequences and 3D profiles) using an HPC-based cloud.
This will enable the use of machine-learning techniques to extract relevant information and to understand better the interrelations between the various process parameters.