Correlation of the process signals during grinding and the resulting workpiece quality

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Modern process monitoring systems are frequently used in industrial manufacturing processes with geometrically determined cutting edge and, for example, enable automated fault detection during the machining process. However, due to the indeterminate geometry and the large number of cutting edges, process monitoring is only used in very specific cases when grinding. The previous knowledge in this area does not allow a direct correlation of the process signals provided by the machine control and the resulting quality of the workpiece. At the same time, more and more measuring signals are available due to the advancing developments in sensor technology and open machine controls of modern machine tools. This ever-increasing amount of process information can help to facilitate process design and to improve the work performance.The existing findings from the current state of art as well as from preliminary work show the potential for the successful use of process monitoring during grinding. However, due to a lack of knowledge about the holistic relationships between the process signals and the manipulated variables of the grinding process, this potential can not yet be exploited and used to predict the grinding result. However, the preliminary investigations have also shown that there is a direct correlation between the process signals and component-describing parameters such as surface roughness or residual stresses. These signals can be recorded using current machine tool controls and measuring systems before evaluating them using statistical methods. For this reason, the goal of this project is to gain knowledge about the correlations between machine environment, process variables, changes in the process signals and the grinding result.