Antriebsbasierte Schwingungsdämpfung für Werkzeugmaschinen und Fahrzeugantriebe

In this thesis, algorithms for the damping of oscillations via closed-loop control are developed for mechatronic systems and further investigated exemplary for a machine tool and an electrical vehicle. It is shown that the same control structure can be used for the damping of the first eigenfrequency of a machine tool’s position control loop as well as for the improvement of the low-frequency vibration behavior of an electrical vehicle

Steps towards a protection system for machine tool main spindles against crash-caused damages

High productivity and availability of machining centers can only be achieved by avoiding unplanned machine downtimes. Machine failures induced by wear can be coped with by implementing preventive and conditionbased maintenance strategies so that downtimes are as short as possible. In contrast, machine damages caused by collisions cannot be avoided by these strategies, but only fixed afterwards by reactive maintenance, leading to high repair costs and long machine downtimes. This article presents a new approach for the avoidance of damages to the main spindle unit caused by collisions in machining centers. The mechanical components of this protection system enable the controlled reversible decoupling of the main spindle from the machine structure in case of exceedance of an adjustable force limit. Decoupling leads to a reduction of the whole machine stiffness, resulting in the decrease of the acting collision force. Consequently, all machine components in the collision’s force flux are protected against overload and damage. Once a collision occurred, a general method is shown, where the spindle and its collision objects are separated automatically by the machine’s numerical control. Due to the reversible decoupling mechanism of the protection system, the described retreat strategy eases the handling after a collision for the machine operator

Auf dem Weg zur selbstüberwachenden Werkzeugmaschine

Currently, machine tools are evolving from isolated solutions to become intelligent elements within intercommunicating production systems. This development holds the potential to predict machine-related cost-intensive production shutdowns and integrate these insights into the production planning and machine development. The present paper defines the objective of a machine tool that is autonomously and integrally able to identify, predict and communicate its condition. The objective is derived as a direct consequence of current trends in the condition analysis and prediction of production machines. The combination of methods from production technology and computer science is at the core of 'industry 4.0', opening up the possibility of an innovative fusion of machine and production knowledge with access to a multitude of semantically rich operational data and information. Against this backdrop, the basis for developing a selfmonitoring machine tool exists. It could lead to a more reliable maintenance and production planning as well as shop scheduling. In this paper innovative solutions for the implementation of the objective will be presented