Interactive Tool for Predicting Lack-of-fusion Porosity in Additive Manufacturing

Additive manufacturing is now used in industries like medical devices and aerospace, where precision and reliability are crucial. However, porosity remains a major challenge, as it can weaken the performance of 3D-printed parts, especially affecting properties like fatigue resistance. Predicting porosity, especially in terms of visualization, presents a considerable challenge. In this work, we introduce an interactive platform designed to predict lack-of-fusion porosity in additively manufactured components. This tool is tailored to assist industrial researchers in optimizing processing parameters, such as hatch spacing, layer thickness, and beam rotation angle, to enhance part quality. Additionally, it provides capabilities for optimizing build rates, enabling time-efficient production without compromising the integrity of the parts.