LAUSR

This paper presents an efficient optimization method of combining off-line optimization with on-line adaptive control for CNC (Computerized Numerical Control) machining parameter, and develops the corresponding system, aims to multi-objective optimization and cutting force stability. Firstly, the multi-objective optimization solution of machining parameters is obtained by off-line optimization based on Pareto genetic algorithm and TRIZ theory. Then, on this basis, feed speed is adjusted online based on adaptive control system. Next, current is used as feedback to control cutting force, and cutting force can be kept at a set value by the on-line adjusting. We obtain the relationship between off-line optimization and on-line adaptive control. Finally, we build the combined optimization module and embed the self-developed CNC machining system. Based on the system, the experimental results verify that the optimized process parameters make the processing time reduced by 14 s, and no matter how cutting conditions change, cutting force can be stabilized as soon as possible by adjusting feed speed online for keeping the cutting process stability. From the perspective of building the parameter optimization function module, it provides a new idea for the self-development of CNC machining system.