Optimization of laser cladding parameters based on IKrJaya algorithm

Considering that the multi-track overlapping cladding process involves multiple parameters that restrict and influence each other, it has an important influence on the cladding quality. To improve the optimization efficiency, an efficient surrogate model-assisted optimization algorithm, IKrJaya optimization algorithm is proposed to optimize the process parameters of laser cladding multi-pass lap. Firstly, a Kriging model based on constrained point addition is constructed to describe the relationship between multi-track laser cladding process parameters and cladding quality. The model mainly includes three core constraints, namely, sample screening rule, regional difference measurement and difference focusing plus point rule to achieve an efficient update of the Kriging model. Secondly, an improved multi-objective Jaya (IMOJaya) optimization algorithm is proposed, which uses the mixed distributed random number and adaptive update strategy to optimize the update process of individual positions, so as to solve the limitation of the Jaya algorithm in exploration ability. Finally, by integrating the Kriging model based on constraint adding points and the IMOJaya algorithm, the IKrJaya algorithm is proposed to achieve efficient optimization, which makes full use of its advantages in complex model simulation and global search to optimize multiple objectives. The simulation and experiment demonstrate the effectiveness and superiority of the IKrJaya algorithm in the optimization of laser cladding process parameters.