3D Printer Fused Deposition Molding Process Numerical Simulation And Molding Accuracy Research

Fused Deposition Modeling(FDM)is one of the Rapid Prototyping that develops rapidly in recent years.Due to the advantages of fast molding speed,simple operation and meeting the individual needs,it has been widely used in the fields of developing new product,rapid mold manufacturing,and art creation.However,the de,velopment of FDM is limited by its lower accuracy.The choice of the process parameters will directly affect the accuracy of molded parts.This thesis,On the basis of the FDM equipment using ABS(Acrylonitrile Butadiene Styrene)resin as molding material,studies the numerical simulation and optimizing the process parameters of FDM equipment to improve the accuracy of part.The main works are illustrated in the following aspects:(1)The main influencing factors for the principle error,molding error and the post-processing error have been analyzed systematically.The bonding mechanism of materials and the warp deformation are analyzed in detail,which determines the main technological parameters this paper studies that affecting the bonding quality and the accuracy of the part.(2)Using the finite analysis software ANSYS,this thesis establishes the analysis model of FDM temperature and stress field,getting the law of temperature and stress changes over time of key point,temperature gravity and stress distribution.This thesis vitally studies the effects of different scanning speed,layer thickness,melting temperature,molding room temperature on the part temperature and stress field in the forming process.(3)An orthogonal experiment with four factors and three levels has been designed and implemented.By using Two statistical analysis methods,Signal-to-noise ratio(S/N)and Analysis of Variance(ANOVA),the influence of selected process parameters on the warp deformation of the part can be achieved,and the simulation results can be verified.Moreover,the optimal process parameters minimizing the warp deformation can be obtained.(4)The prediction model for warp deformation of FDM parts based on BP neural network is established.And the genetic algorithm is used to improve the model's prediction accuracy.The process parameter optimization technology is studied by using the genetic algorithm again.The actual molding experiments are performed by using the optimized process parameters.The experiment results demonstrate the feasibility and practicability of the FDM parameter optimization method.