The present work concerns an experimental study of turning with coated cermet tools with TiCN-TiN coating layer of AISI 52100 bearing steel. The main objectives are firstly focused on the effect of cutting parameters and coating material on the performances of cutting tools. Secondly, to perform a Multi-objective optimization for minimizing surface roughness (Ra) and maximizing material removal rate by desirability approach. A mathematical model was developed based on the Response Surface Methodology (RSM). ANOVA method was used to quantify the cutting parameters effects on the machining surface quality and the material removal rate. The results analysis shows that the feed rate has the most effect on the surface quality. The effect of coating layers on the surface quality is also studied. It is observed that a lower surface roughness is obtained when using PVD (TiCN-TiN) coated insert when compared with uncoated tool. The values of root mean square deviation and coefficient of correlation between the theoretical and experimental data are also given in this work where the maximum calculated error is 2.65 %.

The present research work investigated the machining of AISI304 austenitic stainless steel in terms of machining force evolution, power consumption, specific cutting force and surface roughness where a factorial experiment design and analysis of variance technique were used and several factors were evaluated for their effects on each level. The case of dry turning process was studied based on design of experiments in order to obtain empirical equations characterizing material machinability according to cutting conditions such as cutting speed, feed rate and depth of cut and the latter ones were put in relationship with the machining output variables (Ra, Fc, Kc and Pc) through the response surface methodology (RSM). Results revealed that feed rate was the most preponderant factor affecting surface roughness (71.04%). However, the depth of cut affects considerably cutting force and cutting power by (60.74% and 67.11%), respectively. In addition, the specific cutting force was found affected significantly by cutting speed with a contribution of 41.43%. The quadratic model of RSM associated with response optimization technique and composite desirability was used to find optimum values of machining parameters (104.54 m/min, 0.08 mm/rev and 0.295 mm).