Real Time Monitoring in L-PBF Using a Machine Learning Approach

Laser powder bed fusion (L-PBF) is an additive manufacturing process whereby a heat source (laser) is used to consolidate material in powder form to build three-dimensional parts. This paper uses real-time monitoring in L-PBF for quality control. Acoustic Emission (AE) is used to detect various defects like pores and cracks during the powder bed selective laser melting process via the machine learning approach. Data collection is performed …