Bayesian inference-based decision of fatigue life model for metal additive manufacturing considering effects of build orientation and post-processing

This study proposes a Bayesian inference-based decision framework to quantify the physical uncertainty based on fatigue life tests maraging steel according post-processing treatments and build orientations. Uncertainty quantification of models is performed determine most suitable for metal additive manufacturing process by employing inference. To select one models, we introduce weighted-equivalent metric (WEM) compare evaluation results from different statistical metrics. By evaluating WEM value, logistic model Zhurkov are identified as steel.