An integrated process and data framework for the purpose of knowledge management and closed-loop quality feedback in additive manufacturing

The Additive Manufacturing (AM) process chain has many steps, each of which generates data, potentially, in different formats. This paper aims to show how these data may be used together to mature the process. However, there are many challenges to getting these data and using it to generate knowledge and close the feedback loop. The biggest current challenges which were common to the AM end uses are: identifying key process variables, knowing which data to capture during the process, understanding how to use in-line inspection to detect defects and managing and using the data collected during the whole AM process chain. The digital process itself is not digital, there is still a lot of work done manually, especially data and information handling, and very limited use of data analysis and knowledge management. This paper maps the processes and the data along the AM process chain and proposed an integrated process and data framework for Additive Manufacturing for the purpose of knowledge management and closed-loop feedback.