2021
DOI: 10.1016/j.promfg.2021.06.039
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A digital twin strategy for major failure detection in fused deposition modeling processes

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Cited by 21 publications
(3 citation statements)
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“…As per the study conducted by Henson et al [61], part distortion during AM can lead to significant waste of resources and catastrophic failure. Current research is more focused on identifying and detecting specific causes that might cause part failures such as extruder clogging.…”
Section: Mukherjee and Debroymentioning
confidence: 89%
“…As per the study conducted by Henson et al [61], part distortion during AM can lead to significant waste of resources and catastrophic failure. Current research is more focused on identifying and detecting specific causes that might cause part failures such as extruder clogging.…”
Section: Mukherjee and Debroymentioning
confidence: 89%
“…Numerous studies have been conducted to explore the implementation of digital twin for fused deposition modeling (FDM) field, with a particular emphasis of defect monitoring and analyzing anomalies in the FDM production process [12], [13], [14]. These anomalies cover various aspects including surface defects, cracks, failure cases and production of substandard products.…”
Section: General Concept Of the Digital Twin For Additive Manufacturingmentioning
confidence: 99%
“…The growing use of 3D printing and the need to design functional parts for final use in the industry has generated the need to develop Design For Additive Manufacturing (DFAM) guidelines that, together with the support of analytical tools, try to predict and improve the mechanical behavior of parts obtained by 3D printing [4]. Thus, the need to investigate the influence of the various printing parameters on the mechanical properties is justified, namely the infill, as this is one of the parameters with a direct influence on the printing time and amount of material consumed in 3D printing [5,6,7].…”
Section: Introductionmentioning
confidence: 99%