Laser additive remanufacturing parameters optimization and experimental study of heavy-duty sprocket

Abstract

Experimental research on laser additive remanufacturing technology of heavy-duty sprocket was carried out. The influences of laser power, scanning speed and powder feeding rate on cladding height, cladding area, melting area and dilution rate were compared and analyzed. The prediction models of the combination of process parameters with the geometric characteristics of cladding layer and dilution were established. A multi-objective process parameter optimization model with the maximum cladding height and cladding area maximum, the minimum melting area and dilution rate as objective functions was established, and the model was optimized and solved based on MOPSO algorithm. The laser additive remanufacturing repairing experiment of damaged sprocket was carried out by using the optimal parameters combination, and the microstructure and mechanical properties of the repaired region were analyzed. The results show that the scanning speed and powder feeding rate are the main factors influencing the geometric characteristics and dilution of the cladding area, and the models have good prediction accuracy. The optimal process parameters (1150 W, 950 mm/min, 3.8 rad/min) obtained by MOPSO algorithm is adopted to repair the damaged sprocket. The repaired area without cracks and pores, the cladding layer shows good metallurgical bonding with the substrate and the microhardness is twice that of the substrate. The experimental results prove that the laser additive remanufacturing technology is feasible to repair the damaged heavy-duty sprocket and has a strong engineering application prospect.

Multi-Objective Process Optimization of Laser Cladding Co-Based Alloy by Process Window and Grey Relational Analysis

“…The unreasonable selection of laser process parameters such as laser power, scanning speed, and powder feeding rate is the main reason for the poor forming characteristics of the cladding layer [9]. Scholars have carried out a lot of research on various methods to optimize the process parameters of laser cladding, including the response surface method (RSM) [10][11][12], grey relational analysis [13,14], optimization algorithm [15], and linear regression method, etc. [16][17][18].…”

“…The grey correlation value increased by 0.229 under optimal conditions. Guo et al [15] established a multi-objective optimization model based on the maximum cladding height and cross-section area, minimum heat-affected zone area, and dilution rate, and further optimized the solution by the MOPSO algorithm. They concluded that the model has higher prediction accuracy, in addition, the scanning speed and powder feeding rate had a significant influence on the dilution rate and the geometric characteristics of the cladding layer.…”