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Metal additive manufacturing often uses powder bed fusion (PBF), a renowned technology that
selectively fuses metal powder particles in a bed using a laser or electron beam to create threedimensional objects. The metal powder exposed to the laser undergoes enormous temperature and
phase change variations in a short period of time during PBF, resulting in undesired thermal
stresses known as residual stresses. To quantify these stresses, the bridge curvature method (BCM)
was applied. Multiscale modelling using adaptive coarsening was used to predict distortions based
on experimentally validated models. Taguchi and Response Surface Method (TM and RSM) were
used to minimize residual stress in stainless steel 316L. Based on optimal parametric results for
minimal residual stress from part-scale simulation and statistical techniques, the parts were printed
avoiding costly experiments. There was a minimum 8% error between optimized predicted and
experimental results. The approach used was critical in lowering computational printing expense.
The effects of individual parameters and their combinations in terms of energy density on residual
stress were also analyzed. The relationship between residual stress, hatch spacing, scanning speed,
and power in metal additive manufacturing can be characterized by an initial increase in residual
stress, followed by a decrease as hatch spacing and scanning speed are increased, while power is
also increased. The effect of beam diameter is very nominal and diminishes in comparison with
energy density parameters.