高质量绿色环保的精车切削优化

Optimization of finish turning for high quality in modern green manufacturing machining

绿色制造中的切削参数优化对于提高加工质量、加工成本、产品利润和节能环保具有非常重要的意义。考虑实际加工约束条件,建立了加工精度与切削能量的双目标精车切削优化模型。通过实例运用NSGA-II算法与MOPSO算法对精车优化切削模型进行仿真,结果表明,NSGA-II算法获得了更优的Pareto最优解集。在给定加工余量条件下,加工精度与切削能量的Pareto最优前沿可由三次曲线方程拟合,且拟合相关指数为0.999 9。在加工精度与切削能量的Pareto最优解集下,加工精度和进给量的关系可由二次曲线方程拟合,且拟合相关指数为0.999 99,为精车切削参数优化选择提供了实践指导。

The cutting parameters optimization of green manufacturing machining is very important for machining quality, machining economics and profit. Subject to various practical cutting constraints, a dual-objective optimization model for finish turning cutting, based on the minimum cutting energy and the minimum machining precision, is proposed. The Non-dominated Sorting Genetic Algorithm-II（ NSGA-II） and Multi-Objective Particle Swarm Optimization （ MOPSO） are applied to the dual-objective nonlinear constrained optimization finish turning cutting model. Simulation results indicate that the Pareto-optimal solutions set by using NSGA-II algorithm are obtained more complete than the Pareto-optimal solutions set by applying the MOPSO algorithm. Under certain depth of cut, the Pareto-optimal front for the cutting energy and machining precision can be fitted by the cubic polynomials equation and the fitting relevant index is equal to 0. 9999. Under the Pareto-optimal front, the machining precision and feed rates can be also fitted by the quadratic polynomials equation and the fitting relevant index is equal to 0.99999, which provides practical guides for optimization of machining parameters.