The analysis of machine data offers a lot of potential for manufacturing companies. It enables the identification and prognosis of deficits in industrial production processes. Using the example of additive manufacturing, a practice-oriented procedure to implement such an analysis is presented in this article. Using a gradient boosting algorithm, it is shown how a leakage error can be identified as well as predicted. Furthermore, requirements for the necessary database are discussed and practical recommendations for manufacturing companies are derived.
