Abstract

The search for continuous improvement of the processes and products offered to the market combined with continuous efforts to reduce energy consumption stimulates the development of techniques and tools geared towards their optimization. Thus, this manuscript describes the application of multivariate optimization in the process of face milling of DIN GGG 50 nodular cast iron by means of experimental design techniques, regression models, and Taguchi loss function. Three input parameters (axial “ap” and radial “ae” depth of cut, and feed-rate “f”) were used as controllable factors of the process and two output parameters (specific cuttingenergy “es” and roughnessaverage “Ra”) were considered as response variables. The output obtained as a result of optimization wases= 1.41 J/mm3andRa= 0.85 µm by applying the input parametersap= 2.34 mm,ae= 33.4 mm andf= 0.44 mm/rev.

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