Over the recent years, several studies have pointed out the impact of manufacturing on the environment. Especially machining offers great potential for the conservation of energy, resources and the reuse of raw materials. ...

Data-based methods are capable to monitor machine components. Approaches for semi-supervised anomaly detection are trained using sensor data that describe the normal state of machine components. Thus, such approaches are ...

Energy efficiency is an essential factor for promoting sustainable manufacturing. Various types of energy consumption occur in modern process chains. This includes usage of electrical energy, e.g. for machine tools or air ...

Sales revenues of enterprises are often subject to seasonal fluctuation. This leads to high or low utilized resources and this in turn to revenue losses. Hence, the enterprises invest a high effort to improve long and ...

Numerous methods have been developed to detect process anomalies during machining. Statistical approaches for semi-supervised anomaly detection compute decision boundaries using information of normal running processes for ...