Macrozones are similarly orientated regions in the microstructure of some Near-α and α+β titanium alloys mainly present in mill products, such as Timetal 834, Ti6242 and Ti64. These regions are typically produced during thermomechanical processing and can prevail further processing. The presence of macrozones in the final component make the part susceptible to Cold Dwell fatigue that can lead to catastrophic failure. Understanding how macrozones evolve during processing is an important step in optimising the thermomechanical processing routes for these alloys and therefore improve fatigue performance.

EBSD is the main characterization technique for orientation data acquisition. However, post-processing analysis is required for the identification of macrozones. In this work, a computational routing for the post-processing of EBSD datasets has been developed for automatic macrozone identification in Ti834 billet material. The main procedure aims to automatically detect macrozones in titanium alloys based on pixel density and disorientation criteria. The tool will be demonstrated in Ti834 mill products that were manufactured with different macrozone size by alternative thermomechanical processing routes. This tool will allow to obtain statistical information such as the size, shape, orientation and texture of macrozones.