Optimization of Laser Cladding Parameters for High-Entropy Alloy-Reinforced 316L Stainless-Steel via Grey Relational Analysis

Abstract

Laser cladding technology serves as a pivotal technique in industrial production, especially in the realms of additive manufacturing, surface enhancement, coating preparation, and the repair of part surfaces. This study investigates the influence of metal powder composition and processing parameters on laser cladding coatings utilizing the Taguchi orthogonal experimental design method. To optimize the laser cladding parameters, multi-response grey relational analysis (GRA) was employed, aiming to improve both the microhardness and the overall quality of the coatings. The optimal parameter combinations identified through GRA were subsequently validated through experimental tests. The results reveal that the microhardness and quality of the coatings are substantially influenced by several critical factors, including the powder feed rate, laser power, high-entropy alloy (HEA) addition rate, scanning speed, and substrate tilt angle. Specifically, the powder feed rate exerts the most significant effect on the microhardness, dilution rate, and average contact angle. In contrast, laser power primarily impacts the mean contact angle difference. The HEA addition rate notably affects the mean contact angle difference, while the scanning speed affects the microhardness and the substrate tilt angle influences the average contact angle. The results of the validation experiment showed a deviation of only 0.95% from the predicted values, underscoring the efficacy of the grey relational analysis (GRA) in optimizing the laser cladding process parameters. The methodology presented in this paper can be applied to determine the ideal processing parameters for multi-response laser cladding processes, encompassing applications such as surface peening and surface repair.