The hybrid manufacturing process which integrates additive manufacturing with subtractive machining is competitive and promising in component repair. To automate this process, detecting the missing volume and generating the deposition tracks is the key. In this study, strategies for repairing defects on flat and non-flat surfaces were investigated. A cost-effective reverse engineering tool was utilized to reconstruct STL models of damaged objects. Point data of the fracture surface on flat

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... ces was obtained to generate the tool path for material building up. For defects on non-flat surfaces, the damaged model was best-fitted with the nominal model. Then both models were sliced and by using area comparison method, the defective domain was detected. Then a series of projection rays were utilized to slice the damaged cross-sections to extract the repair volume. Finally, repair experiments were performed to assess the repair quality through repair automation.