IDENTIFICATION AND MODELING OF PROCESS-INDUCED DAMPING IN MACHINE TOOLS

The interaction between machine and process can lead to unwanted vibrational effects and even instabilities, such as chatter. Consequences can reach from increased tool wear and insufficient machining results up to damages of the machine tool. In order to avert these unwanted vibrational effects and to increase the cutting performance of machine tools, it is necessary to predict the interaction between the machine tool structure and the process with high accuracy.

Motivation

Increasing cost pressure on the global market forces machine tool manufacturers to optimize their development processes. An important tool in this context is the use of modern simulation methods, which can accurately predict the dynamic behavior of a machine tool even in early development stages. The primary challenge here is the representation of damping effects. In order to solve this challenge, the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) has supported the research group FOR1087 “Damping effects in machine tools”, in which the damping of a mechatronic machine tool structure was analyzed. For different occurring dissipation sources, predictable linear and nonlinear damping models have been identified. By using appropriate modeling approaches, the research group was able to incorporate influences of the damping of mechatronic machine tool structures into the simulation. This modeling approach, in combination with the identified damping models, now allows the prediction of the dynamic behavior of machine tool structures with high accuracy. In order to integrate the cutting process into the simulation, suitable cutting force models are needed. However for the process damping effect there are usually no practicable models and parameters available.

Process damping originates from the interaction between the tool and the workpiece. For low cutting speeds, in particular, the process stability is strongly influenced by process damping. For difficult-to-cut materials like titanium or nickel alloys, this influence plays an important role. Neglecting process damping leads to an inaccurate prediction of the stability limit for low cutting speeds. In addition, the process influences the damping in the machine tool structure. Varying machining positions, feed rates, spindle speeds, as well as loads in the machine components have an impact on the structure’s damping distribution. However, in the state of the art these effects are not considered in a sufficient manner.

Objective

The goal of this research project is the simulation of the overall system consisting of the machine tool structure and the cutting process. Based on the results of the research group FOR1087, this allows the next step towards a virtual machine tool. In order to achieve this goal, the influences of the process on damping have to be researched and incorporated into the simulation next to the damping originating from the machine tool structure. This allows new possibilities for optimizing the machine tool, extending stability limits of processes, designing the machining process in a targeted manner and eventually increasing the cutting performance.

Approach

In a first step, different methods are to be investigated with which frequency responses can be measured during the machining process. These methods are, in the next step, assessed and evaluated based on their suitability to identify process-induced influences on the damping effects. Based on these methods, the individual damping effects are measured and analyzed. Additionally, the distribution of damping in the machine tool structure is investigated. With the help of the resulting damping distribution, the relevance of effects like the process-damping itself, the damping originating from the rotating spindle, or the change of damping in the structure due to the contact between the tool and the workpiece, can be assessed. For effects with high influences, detailed local damping models as well as reduced analogous models are to be identified and parametrized. With the detailed models, a highly accurate simulation model of the overall system, consisting of the structure as well as the process, can be built. This enables the holistic optimization of the structure-process interaction. The reduced analogous models, which are to be parametrized automatically, allow for a fast, easy and accurate estimation of stability limits.

Acknowledgments

We want to thank the German Research Foundation (DFG) for the support of this research project (ZA 288/77-1).