Optimizing the Process Parameters for Eco-Friendly Minimum Quantity Lubrication-Turning of AISI 4340 Alloy with Nano-Lubricants Using a Grey Wolf Optimization Approach

Optimization of turning process parameters in minimum quantity lubrication (MQL)-assisted mode is obligatory for enhanced efficiency and product integrity. However, little attention has been paid to analyzing situations where high search precision needed when evaluating the optimal parameters. This article applies grey wolf optimization (GWO) approach optimize AISI 4340 alloy enhance cutting force, surface roughness tool wear. Based on literature data, was conducted with MQL-assisted CuO Al2O3 nanofluids. The problem formulated by mimicking six wolves different objective functions. functions have responses as dependent variables including speed, feed depth independent variables. hunting behavior they encircle prey interpreted machining task optimization. It involves three hierarchically-evaluated guides- alpha, beta delta wolves- positioned optimally other are updated accordingly. bound lower upper limits 80 140m/min, 0.05 0.20m/m/rev 0.1 0.4mm, respectively. algorithm optimizes yield wear using 199.50N, -23.54mm 0.06mm, For CuO, corresponding wear, nano lubricants produced best results. mass production, selective use should be made. usefulness this research endeavor help engineers make decisions producing low-cost components manufacturing.