Research On Cutting Tool Geometry Parameters Optimization For Low Carbon Turning

The low carbon economy has become the urgent needs to deal with carbon emission in the world. The survey based on the International Energy Agency (IEA) showed that the manufacturing industry has become an important source of the carbon emission, which accounts for 30% of total carbon emission. Metal cutting is the most widely used processing method in the mechanical manufacturing industry. The number of the machine tools is more than 8 million in China. The cutting tool parameters affect the processing quality and efficiency, cost of production, processing energy and carbon emission. The optimal selection of cutting tool parameters has a great effect on cutting down carbon emissions of manufacturing companies. Based on the relevance analysis of turning process between energy consumption, cutting temperature, processing time and cutting tool geometry parameters, this paper builds a cutting tool geometry parameters optimization model for low carbon manufacturing, and then presents the optimization method based on adaptive genetic algorithm (AGA)and system platforms. The main contents include:First, taking the cutting tool rake angle (CTRA) and cutting tool edge angle (CTEA) which have important influences on the turning process as the dependent variables, this paper builds the carbon emission calculation model of the turning process, which takes the carbon emissions caused by the power consumption, the cutting tool and cutting fluid into consideration. In additional, the constraint functions of the cutting temperature, spindle speed, maximum cutting force and machining quality are given, too. And then, the optimization model of the cutting tool geometry parameters for the low-carbon turning process is proposed so as to select the optimal tool geometry parameters.Secondly, according to the characteristics of the optimization model of the cutting tool geometry parameters for the low carbon turning process, the solving method based on an improved AGA is proposed. The analysis of the test function example shows that the solving accuracy and global optimization capability of the AGA are improved by adapting the calculation ways of the crossover and mutation probability. Based on the proposed model and the solution method, this paper analyzes an engineering application case of cutting tool geometry parameters optimization. And then the influence laws of the cutting parameters, tool material and workpiece material on the carbon emissions are analyzed. The analysis results of the case optimization show that:(1) The carbon emissions are reduced by 11.7% after optimization. (2) The turning carbon emissions is smaller in rough machining compared with fine machining when the other processing conditions are determined. (3) Compared with carbide cutting tool, the carbon emissions by high-speed steel cutting tool will be bigger while machining 45 steel. (4) The carbon content and heat treatment effect of the processed material affect the processing performance, and the carbon emissions increase with the difficulty of machining material.Finally, on the basis of the above studies, the interactive interface of the cutting tool geometry optimization for low carbon is developed by the use of Matlab, which will provide the technical support for the optimal selection of cutting tool parameters in turning process.The research of this paper will provide the theory approach and technical tool support for the manufacturing enterprises in our country selecting the optimal cutting tool geometry parameters in the turning process to reduce carbon emissions and improve the market competitiveness.