Structural dynamic design optimization and experimental verification of a machine tool

Abstract

Structural dynamic performance of a machine tool greatly affects machining precision and productivity. One effective approach in improving the dynamic performance is by applying topology design optimization to the machine tool structure. However, traditional topology optimization method is hard to implement and does not provide a clear stiffener layout. Furthermore, the topology optimization of certain components does not signify the performance improvement of a holistic machine tool. This paper suggests a new structural dynamic design optimization method for the holistic machine tool. The Adaptive Growth Method which is based on the growth mechanism of natural branch systems is adopted to design the inner stiffener layout of structures, and an optimization strategy for the holistic machine tool utilizing dynamic sensitivity analysis is studied. Both components and contact parts are considered. The dynamic sensitivities of the components are analyzed based on modal test data, and help to determine which components need to be optimized. Then, the headstock, column, and bed are optimized, and the weak contact stiffness is improved. The FEA (finite element analysis) results of an optimized machine tool show that the TCP (tool center point) harmonic displacement is decreased distinctly. To validate the effectiveness of the suggested method, an experiment of the manufactured machine tool structure is conducted, and the experimental results had shown great improvements in the holistic machine tool.