A Supervised Machine Learning Model for Regression to Predict Melt Pool Formation and Morphology in Laser Powder Bed Fusion

A Supervised Machine Learning Model for Regression to Predict Melt Pool Formation and Morphology in Laser Powder Bed Fusion

In the additive manufacturing laser powder bed fusion (L-PBF) process, the optimization of the print process parameters and the development of conduction zones in the laser power (P) and scanning speed (V) parameter spaces are critical to meeting production quality, productivity, and volume goals. I...

Full description

Bibliographic Details
Main Authors: Niccolò Baldi, Alessandro Giorgetti, Alessandro Polidoro, Marco Palladino, Iacopo Giovannetti, Gabriele Arcidiacono, Paolo Citti
Format: Article
Language:English
Published: MDPI AG 2023-12-01
Series:Applied Sciences
Subjects:
laser powder bed fusion
melt pool morphology
powder bed fusion–laser melting
PBF–LM
Inconel 718
design for additive manufacturing
Online Access:https://www.mdpi.com/2076-3417/14/1/328

Internet

https://www.mdpi.com/2076-3417/14/1/328

Similar Items