双刀并行数控车削中的切削参数优化方法

Optimization Approach of Cutting Parameters in Parallel NC Turnings with Two Cutters

为优化双刀并行车削中的切削参数,降低加工成本,提出了结合蚁群算法和子问题枚举算法的切削参数优化算法。以最小化加工成本为目标函数,以粗精车削两阶段的切削参数为决策变量,建立了双刀并行车削的切削参数优化模型;根据车削加工的特点,将参数优化问题分解成若干个子问题,并推导出相应的加工成本理论下限,从而有效降低问题的复杂度。模拟结果表明,该算法运算效率高,能快速找到优化的车削参数,从而节约加工成本。

To optimize cutting parameters in parallel turnings so as to reduce unit production cost （UC） ,a hybrid optimization approach（ACO-EAS） was proposed,which combined ACO with EAS. Taking minimization of the UC as objective function,the cutting parameters in both rough and finish machining as decision variables, the mathematical model of cutting parameters in parallel turnings was established. And then according to the characteristics of turning operations, the optimization problem of cutting parameters was dived into several sub-problems. The corresponding theoretical lower bounds on UC were derived,which were effective to decrease the complexity of the problem. Simulation results show that the proposed ACO-EAS can achieve optimal cutting parameters with high efficiency in order to save UC.