| Currently, the economic development faces severe challenges on the sharp earth’s resources drop and environment deterioration. Manufacturing with high efficiency and low carbon has become an important way to adapt to the needs of the society, to deal with the fierce competition. Metal cutting is the main way of machining. And turning is about20%to35%of cutting. In the process of metal turning, cutting speed, feed rate and the cutting depth have a tremendous impact on the processing efficiency and carbon emissions. Based on analyzing the relationship between energy consumption characteristics, cutting parameters and processing time of turning machining process, the multi-objective machining parameters optimization model for high efficiency and low carbon is established. Taking a typical CNC machine as an example, and in turn this paper analyzes the influence of tool material, workpiece material and workpiece size, on the optimization results adopts improved Non-dominated Sorting Genetic Algorithm (NSGA-Ⅱ) optimization solution. This will provide Give a support for selecting parameters for manufacturing with high efficiency and low carbon.Firstly, turning energy consumptions are divided into the machine starts, the auxiliary processing and removal of material processing energy consumption. From the points of energy, materials and waste, this paper establishes the carbon emissions model of turning process by introducing the carbon emission factor of power, tool and cutting fluid. According to the characteristics of the actual machining (cutting depth of each pass are not necessarily the same), the relationships between cutting speed, feed rate, cutting depth and processing time are studied. The processing time of empty travel path is counted into auxiliary time, so as to obtain a more realistic model of calculating processing time. A complete multi-objective turning parameters optimization model for high efficiency and low carbon is obtained with the constraints of machine tools, cutting tools and machining quality. Which will build the basis of high-efficiency and low-carbon cutting parameters optimization.Secondly, based on the features of multi-objective machining parameters optimization model for high efficiency and low carbon, improved Non-dominated Sorting Genetic Algorithm (NSGA-Ⅱ) is selected to solve the multi-objective model, and obtain the pareto solution set. The processing cost model is built by introducing carbon tax. Based on the processing cost, a utility function is built to select the optimal solution from pareto solution set. Taking the CK6136machine as an example, this paper analyzes the impact cutting parameters on carbon emissions and processing time, and further analyzes of the impact of the tool material, workpiece material and workpiece size on optimal results. The results show that:(1) Manufacturing with high efficiency and low carbon can be achieved easily by choosing smaller cutting feed rate and larger cutting speed.(2) Compared to high-speed steel cutting tools, the carbon emissions and processing time generated by carbide cutting tools will be smaller.(3) Constant cutting speed has more advantages than constant rotational speed in manufacturing with high efficiency and low carbon.Finally, on the basis of these studies, the above this paper develops man-machine interactive interface using Visual Basic6.0. This may provide technical support for choosing the optimal parameters in the process of cutting. Then the rationality and accuracy of the proposed model is verified by comparing carbon emissions and processing time generated by turning a part with CK6136. |
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