Selective laser sintering and selective laser melting (SLS/SLM) are additive manufacturing processes based on a layer-by-layer part construction approach by powder bed stacking. At each layer, the laser beam melts a material on the powder bed to create a new section of the part being built. Defects on the powder layer may be carried over to the final part and result in pores, cracks, or other undesirable defects. Monitoring systems are commonly applied to such manufacturing processes, increasing its reliability, thus producing better quality parts. In this research, an imaging method designed to analyze a nonprocessed powder layer is presented. First, a monocular digital camera is used to capture a perpendicular and properly lit image from each powder layer set by a deposition system. The images taken are then digitally sharpened. Subsequently, the images are binarized and processed to acquire the percentage of black and white pixels. Thereon, by comparing the ratio and concentration of black and white pixels of each layer to the normally distributed values of the group, the layers containing defects stand out. The method is feedstock material dependent, as its optical and morphological characteristics change the measured ratio distribution. The here suggested ensemble of method and hardware is applicable to SLS/SLM processes and could evaluate the quality of each layer set, allowing laid flaws to be corrected before becoming defects. Future improvements of this technique may include the fields of machine learning and artificial intelligence.
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