2021
DOI: 10.1007/s00170-021-08158-0
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Rapid residual stress prediction and feedback control during fused deposition modeling of PLA

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Cited by 18 publications
(10 citation statements)
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“…The extrusion temperature is crucial in FDM printing. The temperature directly impacts the viscosity and adhesion of the filament, which are deciding factors of the functionality of the print [17]. For parts that are designed for aesthetic purposes, the issue is not a consideration.…”
Section: Common Defects Posed By Fdm Printingmentioning
confidence: 99%
“…The extrusion temperature is crucial in FDM printing. The temperature directly impacts the viscosity and adhesion of the filament, which are deciding factors of the functionality of the print [17]. For parts that are designed for aesthetic purposes, the issue is not a consideration.…”
Section: Common Defects Posed By Fdm Printingmentioning
confidence: 99%
“…However, the durability of 3D-printed parts has not been thoroughly investigated or disclosed. Moreover, the fused deposition molding (FDM) process, which is widely employed in 3D printing, often produces substantial thermal residual stress in the printed parts due to repeated heating and cooling cycles [ 30 , 31 ]. This residual stress can be relieved in a humid environment, leading to structural deformation and ultimately affecting the usability and functionality of the component.…”
Section: Introductionmentioning
confidence: 99%
“…The study from Zhu et al. [ 11 ] utilizes a feedback control strategy in AM by combining FEA and intelligent algorithms with physical modeling and data analysis. To predict the residual stresses, the back propagation (BP) neural network algorithm is applied.…”
Section: Introductionmentioning
confidence: 99%
“…Out of the four different scanning filling paths, the honeycomb path's stress distribution was the most uniform and resulted in minimal deformation. The study from Zhu et al [11] utilizes a feedback control strategy in AM by combining FEA and intelligent algorithms with physical modeling and data analysis. To predict the residual stresses, the back propagation (BP) neural network algorithm is applied.…”
Section: Introductionmentioning
confidence: 99%