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

现代过程监控系统经常用于具有几何确定的切削刃的工业制造过程中，并且例如能够在加工过程期间实现自动故障检测。然而，由于几何形状不确定且切削刃数量众多，过程监控仅在磨削时的特定情况下使用。该领域的现有知识不允许将由机器控制器提供的过程信号与工件的最终质量直接关联。与此同时，由于传感器技术和现代机床的开放式机床控制的不断发展，越来越多的测量信号可用。这些不断增加的过程信息有助于促进过程设计和提高工作绩效。现有的研究结果表明，在磨削过程中成功使用过程监控是有潜力的。然而，由于缺乏关于过程信号与磨削过程的操纵变量之间的整体关系的知识，这种潜力还不能被开发并用于预测磨削结果。然而，初步的调查也表明，有一个直接的相关性之间的过程信号和组件的描述参数，如表面粗糙度或残余应力。这些信号可以使用当前的机床控制和测量系统记录，然后使用统计方法对其进行评估。因此，本项目的目标是了解机床环境、过程变量、过程信号变化和磨削结果之间的相关性。

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.