SUMMARY

Metal additive manufacturing (AM) and the laser powder bed fusion (LPBF) AM process have gained prevalence over the last decade due their unique capabilities which nullify many design constraints typically imposed by traditional manufacturing processes for metals. However, it has been observed that processing-induced defects can introduce high scatter in the material and mechanical properties of the manufactured workpiece, creating uncertainty in end-component performance. This lack of process repeatability defies the typical concept of a ‘material lot,’ which implies that materials which share a common manufacturing pedigree also share similar properties. That is to say, even when critical parameters of the LPBF process are held constant throughout manufacture, defect content can significantly vary across and within workpieces. The precise nature and causal factors of this scatter remains elusive and current engineering models applied to the LPBF process do not account for or predict it – a definitive treatment of the subject is required. In response to this, the proposed research will (1) study the scope and nature of material lot variability in LPBF, (2) determine which LPBF process signatures can be used to understand variability in defect formation and (3) investigate modeling frameworks capable of predicting workpiece quality based on these process signatures. Through this work, processing behaviors in need of greater control to reduce lot variability will be identified, e.g., workpiece spatial origin, spread powder bed quality, and spatter redistribution. The results will enable process optimization efforts and best practice implementations which address high material lot variability, thereby enabling lower risk implementation of LPBF.

The proposal presentation will be held in-person (MRDC 4211) and virtually (tinyurl.com/JBerezPhDProposalPres).