Optimizing Nickel-Cobalt Electrodeposition for Sustainable Agricultural Equipment: Wear Resistance Enhancement through Multi-Response Optimization

Abstract

The rapid wear of sugarcane harvester blades, caused by continuous abrasion and impact, leads to increased operational costs and reduced efficiency in the sugarcane industry. To address this issue, this study focuses on optimizing nickel-cobalt (Ni-Co) electrodeposition parameters to enhance the wear resistance and service life of harvester blades. While individual parameter adjustments have been studied, a comprehensive multi-response optimization approach for agricultural machinery remains underexplored. This research applied the Grey-Taguchi method to optimize two key parameters: current (0.02 A, 0.04 A, 0.06 A) and cobalt volume (10%, 20%, 30%). A Taguchi L9 orthogonal array was used to design the experiments, while Grey Relational Analysis (GRA) integrated multiple responses to minimize wear volume and control coating thickness. The effects of the parameters were further analyzed using Analysis of Variance (ANOVA) to assess statistical significance. Results showed that current had the most significant impact on wear resistance, contributing 96.72% to the total variation, while cobalt volume played a lesser but still important role. The optimized parameters (0.04 A current and 10% cobalt) led to a substantial reduction in wear volume (0.00177 mm³) and improved coating performance. Confirmation experiments validated these findings. The study demonstrates that the Grey-Taguchi method is an effective approach for optimizing Ni-Co coatings in agricultural machinery, leading to improved blade durability and reduced maintenance costs. Future research should explore additional process parameters and assess the environmental impact of these coatings.