Nickel-based super alloys are popular for applications in the energy and aerospace industries due to their excellent corrosion and high-temperature resistance. Direct metal deposition (DMD) of nickel alloys has reached technology readiness for several applications, especially for the repair of turbomachinery components. However, issues related to part quality and defect formation during the DMD process still persist. Laser remelting can effectively prevent and repair defects during metal additive manufacturing (AM); however, very few studies have focused on numerical modeling and experimental process parameter optimization in this context. Therefore, the aim of this study is to investigate the effect of determining the remelting process parameters via numerical simulation and experimental analyses in order to optimize an industrial process chain for part repair by DMD. A heat conduction model analyzed 360 different process conditions, and the predicted melt geometry was compared with observations from a fluid flow model and experimental single tracks for selected reference conditions. Subsequently, the remelting process was applied to a demonstrator repair case. The results show that the models can well predict the melt pool shape and that the optimized remelting process increases the bonding quality between base and DMD materials. Therefore, DMD part fabrication and repair processes can benefit from the remelting step developed here.
Keywords: Inconel; additive manufacturing; direct metal deposition; laser remelting; process chain; process modeling; repair welding.