Enhancing precision and safety in metallographic sample preparation: Reduce the stochasticity and workload with robotization

Abstract Despite advancements in metallography automation, sample preparation remains largely semi-automated with isolated subprocesses like sectioning, grinding, and polishing. Leveraging modern technologies such as collaborative robotics, AI-driven computer vision, and advanced sensors could enable fully integrated automation. However, the diversity of processes requires skilled human oversight. Integrating user-friendly cobot interfaces may promote a synergistic workspace that enhances safety, reduces monotony, and supports complex studies and documentation aligned with open science principles. Our study explores cost-effective mini robots in critical preparation stages, highlighting steps toward complex automation in metallography.