Automated workflow enhances repair efficiency and reproducibility for turbine blades, suggesting improved additive manufacturing processes.
Turbine blades are high-value components whose replacement is costly and slow, increasing the demand for effective repair strategies. Although PBF-LB/M supports precise additive repair, its application is limited by manual and time-intensive part preparation. This work introduces an automated digital workflow for cutting plane definition, repair geometry reconstruction and part alignment, improving reproducibility and reducing preparation time in PBF-LB/M-based turbine blade repair.
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Maalaoui et al. (2026) studied this question.
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