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为了使金属切削加工中，切削参数能实现实时优化保证产品质量和设备效率，提出采用基因算法。它是基于生物进化理论的优化算法，对问题进行全局的、并行的启发式探索优化，因而可以防止收敛于局部最优解，且搜索效率优于其它方法；适用于具有多参数、多约束条件和多目标的切削参数优化。基因算法结合现场实际工况的反馈信息实现了实时优化，在任一不同的生产条件下均能达到最优值。
In order to make metal cutting, cutting parameters can be optimized in real time to ensure product quality and equipment efficiency, the proposed use of genetic algorithms. It is based on the biological evolutionary theory optimization algorithm, the problem of global, parallel heuristic exploration and optimization, which can prevent the convergence of the local optimal solution, and the search efficiency is superior to other methods; for multi-parameter, multiple constraints And multi-target cutting parameters optimization. The genetic algorithm real-time optimization combined with the feedback information of the actual working conditions in the field can reach the optimal value under any of the different production conditions.