Optimization of different parameters related to milling tools to maximize the allowable cutting depth for chatter-free machining

Abstract

Determination of optimal parameters of cutting tool is one of the most significant factors in any operation planning of metal elements, especially in micro-milling process. This article presents an optimization procedure, based on genetic algorithms, to optimize some parameters related to micro-milling tool including number of teeth, shank diameter, fluted section diameter, shank length, taper length, and length of fluted section. The aim of this optimization is maximizing the minimum value of cutting depth on the border of stability lobe diagrams, which is called allowable cutting depth, for chatter-free machining. Cutting tool is modeled as a three-dimensional spinning cantilever Timoshenko beam based on strain gradient elasticity theory. Structural nonlinearity, gyroscopic moment, rotary inertia, and velocity-dependent process damping are also considered in the cutting tool model. The values of natural frequency, damping ratio, and material length scale of the micro-milling tool are calculated using a system identification based on genetic algorithm to match the analytical response with recorded experimental vibration signal. Using beam model, the allowable cutting depth is increased in the optimization process for a specific range of spindle speed to avoid the chatter phenomenon. Analytical study of micro-milling process stability is carried out to determine the cost function of the genetic algorithm. A plot of the greatest fitness in each generation is sketched. In addition, stability lobe diagrams before and after optimization process are presented to show the efficiency of the optimized micro-milling tool. In the presented examples, the results of genetic algorithm may lead to design or find a micro-milling tool that its acceptable cutting depth increases up to 1.9313 times.