Modeling and optimization for laser cladding via multi-objective quantum-behaved particle swarm optimization algorithm

The process parameters of laser cladding have significant effects on the quality of the laser clad coating. Generally, optimizing one property usual lead to deterioration in some other performances. In this study, the influence of key parameters to preparing the CoCr1.5FeNiNb0.5 coating, namely laser beam power, scanning speed and defocus, on the dilution and residual stress were systematically researched. The polynomial model for the parameters on dilution and residual stress was designed by response surface methodology and the effect of each parameter on the responses was investigated. Then the quadratic models were used as the constraint functions and multi-objective quantum-behaved particle swarm optimization was applied to find the minimum dilution and residual stress. At last, the optimal process parameters were predicted by this algorithm and the high entropy alloy coating was manufactured. The CoCr1.5FeNiNb0.5 HEA coating consisted of FCC and Laves phase.