Integrated statistical modelling and process optimization of laser cladding of IN625 on Rene 125 turbine blade using advanced correlation analysis

This study investigates the influence of critical laser cladding parameters(laser power (P), scan speed (V), and powder feed rate (F))on the geometric characteristics of IN625 single-pass tracks deposited on the constrained surface (∼1.6 mm width) of Rene 125 turbine blades, diverging from conventional research typically conducted on flat plate substrates. A full factorial design systematically varied P (200–350 W), V (5–11 mm/s), and F (0–250 mg/s) to fabricate 36 single-pass tracks. Comprehensive cross-sectional analysis via SEM, integrated with advanced Pearson correlation analysis, evaluated key responses: track width (W), height (H), penetration depth (b), dilution (D), and wetting angle (T). Quadratic polynomial models achieved R² values of 0.65–0.83, confirming adequate predictive accuracy while underscoring the process complexity. Pearson correlations revealed unconventional trends distinct from flat-surface studies: laser power exhibited a significant negative correlation with track width (r ≈ −0.43) but a positive correlation with wetting angle (r ≈ 0.34). Scan speed positively influenced W while reducing H, whereas elevated powder feed rates increased H (r ≈ 0.51) yet decreased D (r ≈ −0.57) and b (r ≈ −0.49). These findings highlight the unique interplay of parameters in turbine blade repair contexts, where geometric constraints alter conventional process dynamics. Through multi-response optimization, the optimal parameter set(275 $\pm 15$ W, 8 $\pm 0.5$ mm/s, and 150 $\pm 10$ mg/s) was identified to achieve precise geometric control, balancing dimensional accuracy and metallurgical integrity essential for aerospace component restoration.