Large raw parts require a long time consuming process of alignment into the machine, before the machining process starts. Alignment process requires two steps: first, characterization of geometry, and second, alignment. Important skills are necessary, and, besides the time consumption of workforce and machine, the risk of getting into shortage of material is high. The paper presents a machine integrated 3D vision approach based on stereo-photogrammetry able to autonomously verify the alignment and calculate the required raw part set-up corrections. The potential of the solution to reduce the alignment process time of raw parts in machine tools is demonstrated in two milling pilot cases.