Dimension Error Predictions in the Fused Deposition Modeling Based on the Multilayer Perceptron Model
Nowadays,the fused deposition modeling(FDM)or fused filament fabrication(FFF)is one of the most common and widely used 3D printing technologies,which could be used to manufacture various functional components.However,part defects of low dimensional accuracy,poor surface quality,susceptibility to warping,and insufficient mechanical strength often occur after printing.These problems are usually solved by optimizing the process parameters,but extensive experiments and complex data processing works are required.Therefore,taking the 3D printing of carbon fiber-reinforced composites as the example,this paper proposed a dimension error prediction method in FDM(FFF)based on the multilayer perceptron(MLP)model.The experimental results indicate that by using the 4-Layers-a network structure with four hidden layers and a conventional design of neuroses,the MLP model could predict the size error.The error prediction accuracy is over95%,meaning that the4-Layers-a MLP model is an effective tool to be employed in the process parameter optimizations for FDM(FFF).
万方数据
维普
