Abstract
This paper presents an optimum design approach of a spindle-tool system to improvise the dynamic stability of end-milling. Initially, the tool-tip frequency response function is obtained by analyzing the spindle-tool assembly with the finite element model. The chatter-free regions are maximized using an optimization methodology by considering the spindle and tool parameters as design variables. A simulated experimental dynamic data consisting of the average stable depth of cut is obtained for different combinations of design variables by the method of design of experiments (DOE) and analysis of variance technique is applied to find the influence of design parameters on the outputs. Based on the obtained results, the data is generalized with the help of a neural network model that works as an estimator of the average stable depths for the optimization module. The average stable depth of cut over a range of operating speeds is maximized by selecting optimal tool and spindle parameters.
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