Evaluation of: MOSSA, MOALO, MOVO and MOGWO algorithms in green machining to enhance the turning performances of X210Cr12 steel

The current study investigates the Wet and MQL machining, when turning of X210Cr12 steel, using a multilayer-coated carbide insert (GC-4215) with various nose radius, the consideration of the tool geometry with different cooling modes allow as to assess the comportment of the machined steel against the cutting combinations. The response surface methodology (RSM) has been used for regression analysis and to evaluate the contribution of the cutting parameters on surface roughness, tangential force and cutting power using ANOVA analysis. The developed models have been used to predict the studied output factors according to the selected cutting parameters for wet and MQL machining. A comparative between the cooling techniques have been established to determine the most effective technique in terms of part quality, lubricant consumption and power consumption. Finally, four new optimization technics have been used for the process optimization using the MQL models for an environment-friendly machining.