Reliability optimization of micro-milling cutting parameters using slime mould sequence algorithm

An optimal selection of cutting parameters is of great significance for increasing machining efficiency, improving accuracy, and reducing the cost of micro-milling. An accurate description of the machining mechanism and the cutting process is the premise of obtaining high-precision cutting parameter optimization results. In this work, a framework is presented for analyzing cutting forces, tool deflection and workpiece surface roughness, considering size effects, tool runout and minimum cutting thickness in micro-milling. Moreover, the novel slime mold sequence algorithm is proposed based on the feedback effect of slime mold on food propagation waves and the decoupling of the optimization process and reliability evaluation. Based on the proposed algorithm, to improve the efficiency of optimization, the material removal rate, machining cost and time are selected as objective functions while the cutting forces, tool deformation, workpiece surface roughness, and parameter uncertainty are considered as optimization constraints. The accuracy of the developed model is verified by micro-milling experiments. Furthermore, the reliability optimization results show that the material removal rate is increased by 12.6%, the processing cost is reduced by 6.94%, and the processing time is reduced by 9.74%, which provides theoretical guidance for optimizing the cutting processes of precision parts.