Stereo vision-based repair of metallic components

Abstract

Purpose This paper aims to investigate a stereo vision-based hybrid (additive and subtractive) manufacturing process using direct laser metal deposition, computer numerical control (CNC) machining and in-process scanning to repair metallic components automatically. The focus of this work was to realize automated alignment and adaptive tool path generation that can repair metallic components after a single setup. Design/methodology/approach Stereo vision was used to detect the defect area for automated alignment. After the defect is located, a laser displacement sensor is used to scan the defect area before and after laser metal deposition. The scan is then processed by an adaptive algorithm to generate a tool path for repairing the defect. Findings The hybrid manufacturing processes for repairing metallic component combine the advantages of free-form fabrication from additive manufacturing with the high-accuracy offered by CNC machining. A Ti-6Al-4V component with a manufacturing defect was repaired by the proposed process. Compared to previous research on repairing worn components, introducing stereo vision and laser scanning dramatically simplifies the manual labor required to extract and reconstruct the defect area’s geometry. Originality/value This paper demonstrates an automated metallic component repair process by integrating stereo vision and a laser displacement sensor into a hybrid manufacturing system. Experimental results and microstructure analysis shows that the defect area could be repaired feasibly and efficiently with acceptable heat affected zone using the proposed approach.