Research On Hybrid Optimization Of Low-carbon Supply Chain Network And Scheduling Of Distributed 3D Printing Intelligent Factory

With the continuous development of advanced information technology,more and more manufacturing enterprises begin to transform and upgrade and move forward to the intelligent manufacturing advocated by the state.On the other hand,in order to promote the development of circular economy,“carbon peak” and “carbon neutralization” have become the goal of sustainable development of enterprises.In this context,how will manufacturing enterprises improve production efficiency? Therefore,how the distributed 3D printing intelligent factory studied in this thesis can realize lowcost operation through the mixed optimization of “low-carbon supply chain” and“production scheduling” has become a frontier problem of the times.On the basis of relevant research in academic circles,combined with the related concepts of intelligent factory,3D printing intelligent factory and distributed production,this thesis summarizes the concept of distributed 3D printing intelligent factory,and then combines the low-carbon supply chain and some theoretical basis to construct the low-carbon supply chain architecture of distributed 3D printing intelligent factory,and puts forward the problem of hybrid optimization of low carbon and scheduling.In view of the increasingly prominent cost and carbon emission problems in the low-carbon supply chain of the distributed 3D printing intelligent factory,this thesis constructs a hybrid optimization model of the low-carbon supply chain network and scheduling of the distributed 3D printing intelligent factory.In this model,the raw material purchase cost,supplier selection cost,production cost,fixed cost,transportation cost and carbon emission cost of 3D printing products are considered in order to meet the goal of cost minimization.And the mathematical solution software is used to solve the model,work out the scheduling scheme,and analyze the sensitivity of the results through simulation experiments.The simulation results verify the effectiveness of the model proposed in this thesis,and show that the changes of demand,factory size and production capacity will produce different production distribution results,in which the more the demand or the lower the production capacity,the more complex the low-carbon supply chain structure will be;with the increase of demand,factory size or production capacity,the cost of carbon emissions gradually becomes the main factor affecting the total cost.The total cost will decrease with the increase of production capacity,and the production capacity of factories with continuous operational processes will have the greatest impact on the total cost;in addition,with the growth of demand,the impact of carbon price on the total cost of manufacturing enterprises is becoming increasingly prominent.Therefore,the simulation results of this study are of reference value for the management decisionmaking of distributed 3D printing intelligent factory under the background of “double carbon”.This study is innovative and makes up for the academic gap of the hybrid optimization of low-carbon supply chain network and scheduling in the distributed 3D printing intelligent factory.By innovating the low-carbon supply chain model of distributed 3D printing intelligent factory,we can make it conform to the trend of the development of the times and promote the development of green and economy in our country.And it can be used as a reference for the transformation and upgrading of China’s manufacturing enterprises,university production,scientific and technological progress and green development.