**Feeling Machine for Process Monitoring of Turning Hybrid Solid Components**

#### **Berend Denkena, Benjamin Bergmann and Matthias Witt \***

Institute of Production Engineering and Machine Tools, Leibniz University Hannover, 30823 Garbsen, Germany; denkena@ifw.uni-hannover.de (B.D.); bergmann@ifw.uni-hannover.de (B.B.)

**\*** Correspondence: witt@ifw.uni-hannover.de; Tel.: +49-511-762-18095

Received: 11 June 2020; Accepted: 8 July 2020; Published: 10 July 2020

**Abstract:** The realization of the increasing automation of production systems requires the guarantee of process security as well as the resulting workpiece quality. For this purpose, monitoring systems are used, which monitor the machining based on machine control signals and external sensors. These systems are challenged by innovative design concepts such as hybrid components made of different materials, which lead to new disturbance variables in the process. Therefore, it is important to obtain as much process information as possible in order to achieve a robust and sensitive evaluation of the machining. Feeling machines with force sensing capabilities represent a promising approach to assist the monitoring. This paper provides, for the first time, an overview of the suitability of the feeling machine for process monitoring during turning operations. The process faults tool breakage, tool wear, and the variation of the material transition position of hybrid shafts that were researched and compared with a force dynamometer. For the investigation, longitudinal turning processes with shafts made of EN AW-6082 and 20MnCr5 were carried out. The results show the feeling machine is sensitive to all kinds of examined errors and can compete with a force dynamometer, especially for roughing operations.

**Keywords:** turning; process monitoring; tailored forming; feeling machine; benchmark
