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As climate change and resource scarcity become more critical, demand for energy efficiency, emission reduction, and resource conservation increases. Forming technology offers high potential for lightweight design, cost effectiveness, and resource efficiency. However, forming-induced ductile damage, such as void formation, is often overlooked in component design, which focuses on mechanical properties and safety factors. A deeper understanding of forming-induced ductile damage can lead to more efficient, lightweight structures. Therefore, the void distribution was analyzed using focused ion beam and scanning electron microscopy, enabling the development of a 3D model via AI-based image segmentation. To assess void inclusion interactions, an intersection analysis was performed in Fiji ImageJ by merging in-lens images of sulfides with secondary electron images of voids, allowing a volumetric representation of their intersections.

Evaluation of damage mechanisms in full-forward rod extruded AISI 5115 steel by AI-based image segmentation