Research On Collaborative Optimization Of Logistics, Energy Flow, And Value Flow Of Copper Smelting Enterprises

The key to the system energy saving and cost reduction of copper smelting is the optimization control of the matte grade.Reasonable smelting matte grade that ensures the rational distribution and optimization of material and energy r esources in production process,improves metal recovery of each process,and further reduce the system closed-loop dissipation,reduces the material energy costs and improve enterprise's core competitiveness is a crucial mean.Studying on the synergistic optimization of material flow,energy flow and value flow of copper smelting,it can get the optimal matte grade under the smelting condition,optimize and adjust the charge mixture of ISA furnace,converter and anode furnace.It is of great theoretical significance and application value to reduce the cost and energy-saving of copper smelting process.First,the production and process characteristics of copper smelting were analyzed,and the synergistic effect of material flow,energy flow and value flow was dissected.Based on the analysis,the model of the material balance,thermal equilibrium mechanism model and smelting cost statistical model were established for ISA furnace,converter and anode furnace.And considering the mutual restraint among the production units,the matte grade is optimized by the optimal model based on making the lowest smelting cost of each furnace the objective function.In the model solution,the modified genetic algorithm was used to solve the optimal control model based on segmented real coded.The comparison between the results of the model and the actual data shows that:The model and algorithm is scientific and effective,the obtained optimum smelting matte grade is 55.6%,and corresponding lowest smelting cost is 2030.36 yuan/ton anode copper.On the basis of establishing the optimal control model of matte grade,utilizing the prediction performance of BPNN and considering all kinds of factors of matte grade,the matte grade BPNN prediction model is established by MATLAB.And combining with the best matte grade,the model can optimize the ingredients and the supply of wind/oxygen of the ISA furnace and other furnaces.Then the paper optimizes weights and thresholds of BPNN to search for the optimal solution by GA.Analysis results indicate that the predicted performance of BPNN prediction model after GA optimizing is better,the mean absolute error is reduced to less than 0.51%.Finally,using the Java programming language,three-flow model coupled system of copper smelting is designed and developed to guide production operation on the basis of the model.The application result shows that the system has the favorable stability,and will obtain the best matte grade under different furnace conditions in 20 seconds,and make the best material and energy resource allocation plan of ISA furnace,converter and anode furnace to guide and optimize the production of copper smelting.