Statistical analysis, modeling and multi-objective optimization of parameters intermittent turning process of AISI D3

Intermittent machining is characterized by its complex and irregular context. This intermittency causes to occur under difficult conditions that greatly influence the technological performance parameters. The aim of present work evaluate effects input parameters, cutting speed, Vc, depth cut, ap, tool nose radius, r feed rate, f, on surface roughness, Ra, tangential force, Fz, motor power consumption, Pm, power, Pc material removal rate (MRR), during intermittent turning (IT) AISI D3 steel. Machining was performed with a triple CVD coated carbide (AI2O3/TiC/TiCN) adopting Taguchi L9 (3^4) experimental design. ANOVA RSM methods were used analyze factors outputs parameters resulting in statistical prediction models. In addition, multi-objective optimization exploiting desirability function (DF) done according four cases relative importance corresponding different industrial contexts. Furthermore, grey relational analysis (GRA) method applied compared DF method. results show optimal regime found method, (r =1.6mm, Vc= 240 m/min, f = 0.084 mm/rev ap 0.64 mm), favors Ra MRR. On other hand, for GRA combination 0.4 mm, Vc m/min 0.08 0.3 mm) minimization Pm Pc. presents an originality because are very useful field better control process IT.