An integrated approach for detecting and classifying pores and surface topology for fatigue assessment 316L manufactured by powder bed fusion of metals using a laser beam using µCT and machine learning algorithms - Data

Description: This dataset contains micro-computed tomography (µCT) scans and fatigue test data for specimens manufactured from 316L stainless steel using laser-based powder bed fusion of metals (PBF-LB/M). All specimens were scanned by µCT and subsequently subjected to fatigue testing. The dataset links the fatigue test results of each specimen to the corresponding µCT scan, enabling the investigation of relationships between internal manufacturing defects, specimen characteristics, and fatigue performance. The specimen geometry, manufacturing conditions, experimental procedures, and evaluation methods are described in the related journal publication. Related Journal publication: Diller J, Siebert L, Winkler M, et al. An integrated approach for detecting and classifying pores and surface topology for fatigue assessment 316L manufactured by powder bed fusion of metals using a laser beam using μCT and machine learning algorithms. Fatigue Fract Eng Mater Struct. 2024;47(9):3392-3407. doi:10.1111/ffe.14375