Enhancing Expert Knowledge Based Cause-Effect Networks Using Continuous Production Data

In micro forming, a precise planning of processes constitutes a challenging task due to inherent uncertainties. The method “Micro - Process Planning and Analysis” uses cause-effect networks to achieve this task. This article presents a method, which enables updating these networks based on new data regularly. It enables the use of discrete and continuous machine data, such as force profiles. Finally, the method is evaluated using simulated data, modelled according to a real process. The results show a quick registration of changes in the process behavior and a high prediction accuracy in terms of the expected mean and variance.