Model-Based Investigation of Machining Systems Characteristics : Static and Dynamic Stability Analysis

Sammanfattning: The increasing demands for precision and efficiency in machining call for new control strategies for machining systems based on the identification of static and dynamic characteristics under operational conditions. By considering the machining system as a closed-loop system consisting of a machine tool structure and a machining process, the join system characteristics can be analyzed. The capability of a machining system is mainly determined by its static and dynamic stiffness. The goal of this thesis is to introduce some concepts and methods regarding the identification of machining system stability. Two methods are discussed, one for the static behaviour analysis of a machine tool, and one for dynamic stability of a machining system. Preliminary results are indicating unambiguous identification of capabilities of machining systems static and dynamic characteristics. The static behaviour of a machine tool is evaluated by use of a loaded double ball bar (LDBB) device. The device reproduces the real interaction between the join system, the machine tool elastic structure and the cutting process. This load is not equivalent to real cutting forces, but it does have a similar effect on the structure. This has been investigated both trough simulation and experimental work. It is possible to capture the process – ­machine interaction in a machining system by use of the model-based identification approach. The identification approach takes into consideration this interaction and can therefore be used to characterize the machining system under operational conditions. The approach provides realistic prerequisites for in-process machining system testing. The model parameters can be further employed for control and optimization of the cutting process. Using different classification schemes, the model-based identification method is promising for the detection of instability. Furthermore, it is the author’s belief that a model-based stability analysis approach is needed to exploit the full potential of a model driven parts manufacturing approach.