Multi-objective optimization of laser cladding process parameters for Q345B steel

Abstract

To optimize the process parameters of laser cladding Fe-based alloy on Q345B steel, a single-pass laser cladding experiment was conducted by response surface methodology(RSM). The mathematical models were constructed to analyze the influence of process parameters (laser power, scanning speed, powder feed rate) on coating performance (aspect ratio, dilution rate, hardness). Subsequently, multi-objective optimization was performed by Non-dominated Sorting Genetic Algorithm II (NSGA-II), and the optimized process parameters were validated through experiments. The results indicate that powder feed rate significantly affects coating hardness and aspect ratio, laser power primarily influences coating dilution rate, and there is a significant interaction between scanning speed and powder feed rate in terms of coating hardness. The optimized process parameters were determined as follows: laser power of 990 W, scanning speed of 381 mm/min, powder feed rate of 0.65 r/min. Consequently, the corresponding aspect ratio was found to be 3.01 with a dilution rate of 34.72% and a hardness value of 639 HV.The coatings exhibited dendrites crystal and eutectic tightly bonded to the substrate without any defects such as pores or cracks.Finally,the application value for engineering purposes is demonstrated by effectively improving comprehensive coating performance through multi-objective optimization utilizing RSM combined with NSGA-II.