Research On The Characteristics And Optimal Method Of Carbon Emission In Product Fused Deposition Manufacturing

Manufacturing industry has created a large number of material wealth,but it also brings serious environmental problems due to the excessive consumption of energy and resources.In order to reduce the environmental pollution and meet the needs of sustainable development,“low carbon manufacturing”,which aims at aims at energy saving and emission reduction,is attracting attentions from academia and industry.Fused deposition modeling recently received much concern for its advantages,for instance,it's easy to forming the complicated products.But there seems little researches focused on the carbon emission in modeling process.Thus,studying the low carbon manufacturing method and technology in fused deposition modeling process is significant.Firstly,the carbon emission in fused deposition modeling process was classified by carbon source.The carbon emission calculated boundary was determined by analyzing the relationship between carbon emission and modeling process.The characteristics of material consumption,energy consumption and chip processing based on the flow of material,energy and chip.In addition,the quantitative method of carbon emission was studied.Secondly,the characteristics of carbon emission in fused deposition modeling process were further studied by comparing with carbon emission in cutting process.By analyzing the carbon emissions in cutting process,the boundary of carbon emission was determined.In order to quantitative carbon emission,the dynamic characteristic of the power in the machine tool's different process phase was analyzed.Besides,the carbon emission models caused by cutting tool consumption and cutting fluid consumption were proposed.An experiment was performed to verify the feasibility of the quantitative methods of the carbon emission in cutting process and fused deposition modeling process,the results showed that electric energy consumption is the biggest contributor of carbon emission in fused deposition modeling process.Finally,the definition of energy efficiency was proposed to reduce the electric energy consumption in fused deposition modeling process.On the basis of orthogonal experiment data and Back Propagation Neural Network,the energy efficiency optimization model was established.Self-adaptive niching genetic algorithm was adopted to solve the optimization model,and the optimal result was applied in an experiment which had achieved a better application effect.