FEM simulation and experimental study on milling Laser-clad Inconel 718

Abstract

Laser cladding of Inconel 718 coatings offers significant advantages in the repair of high-value components, but its low dimensional accuracy and high surface roughness limit direct application. This study developed a novel 3D milling simulation model incorporating cladding layer anisotropy and experimentally optimized machining parameters through milling, aiming to minimize axial cutting forces, improve surface quality, and maximize material removal rate (MRR). First, optimal laser cladding parameters were designed, and experiments achieved a surface flatness of 85.247% for the cladding layer. A novel 3D milling simulation model incorporating cladding layer anisotropy was developed, and a multi-objective genetic algorithm was employed to resolve the Pareto frontier. Next, finite element simulations analyzed the axial force, Mises stress, and temperature under cutting speeds ranging from 50 to 80 m/min, feed rates of 0.04 to 0.08 mm/z, and cutting depths of 0.3 to 0.7 mm. The results showed that cutting speed and feed rate are key factors for optimizing the laser cladding milling process. Orthogonal and one-factor experiments were conducted for milling of fused cladding. Experimental validation indicated that the deviation from the simulated forces was less than 15%, confirming the reliability of the model. A multi-objective optimization model (MOGA) was constructed based on a genetic algorithm, obtaining a Pareto optimal solution set. The optimized parameters (59 m/min cutting speed, 0.4 mm depth, 0.04 mm/z feed rate) yielded experimental errors below 10%. This study provides a systematic process framework for additive-subtractive hybrid manufacturing of anisotropic laser-clad components, achieving a synergistic optimization of high precision and high efficiency.