Machining Feature Based Cutting Conditions Optimization For High Performance CNC Machining Of Key Machine Parts

According to the application status of CNC machining technology inChina and the high performance CNC machining of key machine parts asthe research object, the extraction and parameterization of typicalmachining features, the machining feature based cutting conditionsoptimization and its optimization method are studied on the basisdynamic modeling and simulation for milling operation. Thecorresponding cutting tests have confirmed the correctness andeffectiveness of the optimization models and solution methods.In terms of dynamic modeling and simulation, based on the classicaldynamic modeling results of milling process, the prediction of thedynamic cutting forces and chatter stability of end milling withcylindrical end mill were implemented.In terms of typical machining feature extraction and parametrization,4typical machining features such as face milling, pocket milling, T-slotmilling were extracted by in-depth analyzing the CNC processingtechnology of key machining parts. On the basis, these machiningfeatures were parameterized by in the aspect of geometry, manufacturingand process.As for the three extracted machining features of face milling, pocketmilling and T-slot milling, the cutting conditions optimization model wasestablished based on the dynamic modeling and simulation, in which thecutting efficiency as object function, the cutting conditions such asspindle speed, cutting depths and federate as the designing variables, andthe constraint conditions are considered. On the basis, a optimization ideabased step-optimization method was proposed. As a result, the optimizedcutting conditions were determined. The results of cutting tests show thatthe optimization method can improve the cutting efficiency.As for the optimization hole group machining using helical milling,the optimization problem was decomposed into two sub-problems, i.e.,the machining path optimization and cutting conditions optimization of helical milling. In terms of machining path optimization, it is abstractedinto a typicalTraveling Salesman Problem. In terms of cutting conditionsoptimization of helical milling, the optimization model was estabilishedand solved using Simulated Annealing Genetic Algorithm, in which thecutting efficiency as object function, the cutting conditions as designingvariables and constraint conditions are considered. The results of cuttingtests confirmed the correctness and effectiveness of the proposedoptimization models and solving methods.