ANN-NSGA-assisted investigation of tribo-performance of lead-free nickel boron coating

Abstract

In recent times electroless Ni-B coatings free of lead are being investigated with an aim to replace the lead stabilized bath. Traditional formulations of Ni-B coatings often rely on the use of heavy metal/lead-based stabilizers. However, the environmental and health concerns associated with these stabilizers have prompted the exploration of stabilizer-free formulations. The tribological behavior and wear mechanisms of heat-treated heavy metal-free Ni-B coatings were investigated systematically by varying load (10–50 N), speed (0.5–1.5 m/s) and distance (400–1000 m) in accordance with Taguchi's L₂₇ orthogonal array. An artificial neural network (ANN) combined with genetic algorithm is proposed to investigate and optimize wear rate and coefficient of friction (COF) of heat-treated Ni-B coatings. Globular morphology was obtained for the coatings with crystalline peaks of Ni, Ni₃B and Ni₂B for coatings heat treated at 350°C for 1 h. The mean absolute percentage error of ANN model for wear rate and COF was 5.2846% and 2.0572%, respectively. The multiobjective optimization showed 30.325 N load, 0.50007 m/s speed and 759.2959 m distance corresponding to simultaneous minimum wear rate and COF of 0.005297 × 10⁻⁶ g N⁻¹ m⁻¹ and 0.25238 respectively. The worn surface of optimized conditions coatings exhibited oxidized flattened nodules and debris that act as load bearing area leading to lower wear rate and COF.