Monitoring of deformations and cracks for laser powder bed fusion using gas-borne acoustic emission

Abstract

Additive manufacturing (AM) is a manufacturing technique that involves building parts in a layer-by-layer manner from a computer-aided design model. Laser powder bed fusion (L-PBF) is an AM process that uses metal powders as its manufacturing material where a laser beam is used to melt the powder layer pre-deposited onto the substrate. Solidified single layers form along the laser path resulting in 3D objects being built in a layer-by-layer manner. The quality and resulting material properties of the L-PBF parts depend on many factors, such as the laser parameters, build environment and material properties. Deformation, delaminations and cracks within the material are mainly caused by the residual stresses induced during the L-PBF build process by the rapid heating and cooling cycles. With the increase in the implementation of AM technology in industry, there has also been a growing need for quality control and assurance measures for the final product. The effective use of modern methods of non-destructive testing (NDT) online monitoring systems, which can detect deformation and delaminations in the L-PBF process, is currently being investigated. Acoustic emission (AE) is a cost-effective NDT online monitoring method which monitors stress waves propagated by a sudden redistribution of stress in a material. AE has been shown to be effective in monitoring defects such as cracks in pressure vessels and building structures. In this study, cantilever samples, which would crack in an anticipated manner, were designed using simulation techniques from known residual stress phenomena, then built and monitored using gas-borne AE on the EOS M280 system with TI6Al4V(ELI) powder. It was shown that the cracks/delaminations that occur during the metal L-PBF process can be detected and distinguished from other machine noises using their frequency and time-domain AE features. The peaks in the amplitude of the signal emitted in the time domain during the build process could be used to indicate the occurrence of cracks after applying an adequate filter and voltage threshold. The frequency characteristics of the signal could also clearly indicate the occurrence of the cracks and differentiate between the signals from the cracks and the machine noise