Abstract The Corporation of Science and Technology for the Development of the Maritime and Fluvial Shipbuilding Industry COTECMAR has been using for more than 4 years the process of electric arc thermal projection with commercial materials such as 530AS, 560AS and 140MXC to mitigate corrosion phenomena and wear of the different devices that make up the boats. The problem lies in mixing these materials (140MXC-530AS and 140MXC-560AS) to produce dissimilar coatings, making it more difficult to optimize the process, whose problem lies in the parameterization of the arc-beam thermal imaging equipment. In the first phase of the project, a Taguchi L 9 (3 4-2 ) model (fractional factorial orthogonal arrangement) was used to produce the coatings, taking into account the projection parameters of the equipment such as current (A), voltage (V) Primary air pressure (Pp) and secondary air pressure (Ps), which were considered as input variables or experiments for the optimization process. Subsequently the coatings were characterized by techniques such as Scanning Electron Microscopy (SEM) and microhardness to take these data as attributes or output of results in order to obtain the minimization of the size of the projected particles (corrosion) and the microhardness maximization of the coatings (wear). Symbolic regression was used as a technique for obtaining the mathematical models (objective functions), which was done through the "Eureqa Formulize-Desktop" program, because it is considered very complex the modeling of all input variables by conventional mathematical methods. The adaptation of the NSGA-II Multi-Objective Genetic Algorithm was performed through a structured programming in "Matlab", being able to verify that the optimal Pareto fronts obtained in the runs with this Algorithm meet the requirements of the objective functions which are related with the attributes of the selected coatings.