Abstract: To realize the low-carbonization of turning machining process and to improve the machining quality,based on analyzing the relation among energy consuming,cutting temperature and cutting tool geometry parameters in the machining process,by considering the constraints such as machine tool property and processing quality,the tool geometric parameters optimization model for low-carbon turning which took the cutting tool rake angle and cutting tool edge angle as the optimization variables was built.An adaptive genetic algorithm was proposed and applied to solve the proposed model.The case analysis indicated that the carbon emissions and cutting temperature were reduced by 12% and 17% than the original tool parameters by taking carbon emission as the optimization model,the cutting temperature,machine tool property and processing quality as the constraints.The proposed model and method could provide support for the manufacturing enterprise selecting optimal low-carbon turning tool geometry parameters in response to low-carbon requirements.

Key words: low-carbon manufacturing, tool geometric parameter, turning machining, daptive genetic algorithm

摘要： 为了实现车削加工过程的低碳化并提高加工质量,在分析车削加工过程中能耗特征及切削温度与刀具几何参数之间关系的基础上,以刀具前角和主偏角为优化变量,考虑加工过程机床设备和加工质量等约束,建立了车削加工刀具几何参数低碳优化模型;针对所建模型,提出一种基于改进的自适应遗传算法的优化求解方法。实例分析表明,以低碳排放为优化目标、以切削温度为约束条件优化车削刀具几何参数,可使碳排放和切削温度比原刀具参数分别降低12%和17%。所建模型和方法可为制造企业优化选择刀具几何参数降低碳排放提供理论方法支持。

关键词: 低碳制造, 刀具几何参数, 车削加工, 自适应遗传算法