Proactive Error Prevention in Manufacturing Based on an Adaptable Machine Learning Environment

Abstract

This paper gives an introduction into a concept for proactive error prevention in manufacturing. The challenges for research include the accuracy of predictions, the automated adaptation of prediction models to heterogeneous and varied processes, and the management of prediction models in changing processes. The solution is a combination of machine learning technology, big data approaches and knowledge modelling.