Intelligent machine tool

The productivity and working accuracy of machine tools are limited not only by the drive power, but mainly by the dynamic machine properties. Under unfavorable conditions, the static and dynamic forces occurring in the process can lead to chatter vibrations. These self-stimulated vibrations are also noticeable on the work piece surface due to so-called chatter marks. The chatter marks can cause surface tolerances not to be met. The occurrence of chatter vibrations depends on various process variables, such as the depth of cut / and width or the spindle speed. The selection of suitable parameters requires a lot of time for experiments and calculations, expensive measuring equipment and a high level of expert knowledge. The objective of this project is the development and prototypical implementation of an "intelligent machine tool". During the process this machine successively learns at which parameters the process is stable and at the same time as productive as possible. By doing so, the parameters in the process are then adjusted autonomously in such a way that chatter vibrations are avoided, but nevertheless the highest possible material removal is achieved. For this project, the investigations are carried out on the "feeling machine", which uses process-internal sensors to determine the process forces. Methods from the field of artificial intelligence are used for the autonomous adaptation of the process parameters. In this way the feeling machine becomes a learning and intelligent machine in this project.