Currently, more and more cyber-physical systems that constantly collect a variety of data are introduced into production lines. This data is often not completely evaluated, even though it could provide new approaches to significantly increase the productivity, flexibility as well as resource and energy efficiency of the production. This paper presents a fully automated procedure to collect and analyze machine drive-based signals of a programmable logic controller. The goal is to derive a workpiece flaw diagnosis from the processed raw data of the machine tool and examine the influence of cutting parameters on the diagnosis and tool wear. In order to conduct this multi-sensor-analysis, the signals of the machine drives are measured at the frequency inverter and evaluated using a script, which is integrated in a monitoring software. It is shown that the cutting parameters have a strong influence on tool wear and the accuracy of the diagnosis.
Bauerdick, Christoph; Helfert, Mark; Petruschke, Lars; Sossenheimer, Johannes; Abele, Eberhard: An Automated Procedure for Workpiece Quality Monitoring Based on Machine Drive-Based Signals in Machine Tools.