H13 steel (4Cr5MoSiVl), a hot-working die steel, exhibits excellent wear resistance, hardness, and heat fatigue resistance. It is a crucial material for manufacturing hot extrusion and die-casting molds, which operate under high-temperature conditions and are subject to wear, corrosion, and other failure modes. These can lead to premature failure, reduced service life, significant economic losses, and resource wastage. Therefore, extending the service life of molds by repairing damaged sections, restoring geometry, and ensuring mechanical properties that are comparable to or exceed those of new molds is highly significant. The quality of the cladding layer (including geometric dimensions, dilution rate, macroscopic defects, and mechanical properties) depends not only on the matrix material and cladding powder but also on process parameters such as laser power, scanning speed, and powder feed rate. Excessive laser power may induce high residual stress, leading to cracks in the cladding layer, while insufficient laser power results in inadequate matrix melting and poor bonding strength between the matrix and cladding layer. Identifying the optimal combination of process parameters is, therefore, critical to achieving high-quality cladding layers. However, most existing studies utilize circular light spots, and fewer studies focus on large-size rectangular light spots due to challenges in their energy distribution. Circular spots typically require multi-pass overlapping cladding due to their limited irradiation size. Rectangular broadband spots, on the other hand, enhance cladding efficiency and allow for investigations into the impact of overlap rate on surface flatness under different conditions.

The matrix material used is H13 steel, and the powder material is H13 powder, ensuring minimal thermal and physical property differences to avoid cracking of the cladding layer. Laser power, scanning speed, powder feed rate, and overlap rate are considered as inputs in a four-factor and four-level orthogonal test design for cladding H13 powder onto the H13 substrate. Cladding specimens are sectioned using wire cutting and sequentially polished with sandpapers. The sections are corroded using a nitrate alcohol solution for microscopic analysis. Cross-sectional images are captured using an optical microscope, and ImageJ software is used for data measurement. To characterize the geometric morphology of the cladding layer along the scanning velocity direction, three cross-sections are measured, and average geometric parameters of the cladding layer are calculated. The influence of process parameters on the geometry of the cladding layer is analyzed, with cladding width (W), flatness (τ), and dilution rate (η) selected as output response values.Grey correlation analysis (GRA), technique for order preference by similarity to ideal solution (TOPSIS), and rank-sum ratio (RSR), combined with the entropy weight method (EWM), are employed to evaluate and compare the response values. The longitudinal and transverse microhardness of the optimized cladding layer are measured using a microhardness tester. Additionally, the cross-sectional microstructure is observed using a scanning electron microscope (SEM), while element distribution is analyzed using the SEM's energy dispersive spectrometer to determine the reasons for the increased hardness.

Through the orthogonal test design, it is determined that different process parameters have varying effects on the geometric morphology of single-layer multi-pass cladding (Table 2, Fig. 3). The macroscopic morphology is analyzed in detail, and variance analysis is conducted to assess the influence of rectangular laser spot parameters on the geometric morphology of the cladding layer and its variation trends (Tables 3, 4). Using W, τ, and η as response values, the GRA, TOPSIS, and RSR methods, combined with the EWM, provide multi-objective comprehensive evaluations. The optimal parameter combinations under each method are identified (Fig. 6), and the specimens' comprehensive performance is improved under all three combinations (Tables 7, 8, 9). Experimental comparisons show that the error between the predicted comprehensive evaluation coefficient (0.819) and the actual value (0.871) using the GRA-EWM method is only 6.0%. The average microhardness of the cladding layer (867.6 HV0.3) is found to be 4.01 times higher than that of the matrix (216.2 HV0.3) (Figs. 7).

Variance analysis reveals that cladding width (W) is primarily influenced by the overlap rate. The scanning speed has the most significant impact on the height (H) of the cladding layer and the cladding layer area (S_c). For the molten pool area (S_m), laser power exerts the greatest influence. Furthermore, flatness (τ) is most affected by the overlap rate and shows a negative correlation with it. Laser power, scanning speed, powder feed rate, and overlap rate significantly affect the dilution rate (η), with η positively correlated with laser power and scanning speed but negatively correlated with powder feed rate and overlap rate. From the perspective of improving the accuracy of comprehensive evaluation or minimizing errors, the GRA-EWM method is notably effective, with an error of only 6.0% between predicted and experimental values. This method outperforms the TOPSIS-EWM and RSR-EWM methods in accuracy and yields cladding specimens with superior hardness improvements, aligning with the repair objectives.