Linking alloy thermo-physical behavior to laser process parameters for density optimization in LPBF

This work reports on employing X-ray computed tomography (XCT) to develop a predictive model aimed at optimizing laser process parameters for laser powder bed fusion. A commercially available statistical analysis software was successfully combined with XCT obtained porosity data obtained from 316L stainless steel to develop an accurate model that predicted the parameter sets and ranges with the lowest porosity. The predictions indicated that laser velocity and hatch spacing had a numerically linear relationship with laser power and can be combined to minimize porosity at any selected laser power in a specific range. In fact, the predictions indicated that the minimum porosity at any laser power is associated with a specific line energy input of approximately 0.13 J/mm for this alloy. The lowest predicted porosity at each laser power was fabricated and tested with the 85- and 92-W powers confirming ultra-low porosity. Lower laser powers, however, exhibited significantly higher porosity in contrast with the prediction. This resulted from the lower hatch spacing and velocity causing higher energy density and metallurgical defects from macro-balling. Thermodynamic calculations in the optimum laser power range yielded a line energy of 0.131 J/mm, which agrees rather well with the XCT predicted line energy and indicates that porosity generation is governed by the thermo-physical behavior of the alloy. A parameter space in the optimum range was fabricated and confirmed that the lowest porosities exist along a line energy of 0.13 J/mm, where melt pool temperature was predicted to be between 2526 and 2785 °C.