Study of the effect of cutting modes on output parameters under high-speed steel turn-milling

Introduction. The article elucidates increasing the efficiency of turn-milling of powdered metal high-speed steel products. Turn-milling can be used as an alternative to the traditional turning method. The article describes advantages of the turn-milling method. A review of studies devoted to improving the surface quality of parts when turning by milling is given. The work aims at determining the effect of cutting modes on the surface roughness by the orthogonal turning method through milling powdered high-speed steel with a monolithic cutter.Materials and Methods. Statistical analysis methods based on the creation of a mathematical model for predicting microgeometric deviations of the treated surface were used. An experimental research method was applied to verify the adequacy of the mathematical model. The experiment was planned according to the non-composite design proposed by Box and Behnken. The experiment was carried out on a turning machining center with a driving tool. Powdered highspeed steel BÖHLER S390 MICROCLEAN was used as sample material for the experiment. A monolithic carbide milling cutter served as a cutting tool. During the experiment, the cutting speed, milling width, and feed per tooth varied. The roughness of the treated surface was measured by a contact profilometer.Results. A mathematical model of the formation of surface roughness depending on the processing modes was developed. During the experiments, the effect of cutting speed, tool feed, and radial cutting depth on the roughness of the treated surface was determined. It was established that the dependence of roughness on feed had a linear character over the entire investigated range of cutting modes. In turn, the dependence of roughness on the cutting speed and cutting width had a parabolic character. The results obtained allowed us to achieve the roughness of the treated surface Ra = 1.85 without reducing the processing performance. Discussion andConclusions. The developed mathematical model reflects the impact of cutting modes on the surface roughness when turning high-speed steel with a monolithic cutter. The results of the conducted research can be used to determine the optimal cutting modes that provide a given surface quality in the manufacture of real parts under the production conditions. It is recommended to continue the research with the control of additional output parameters, such as temperature and vibration. Reducing the effect of regenerative self-oscillations on the roughness of the treated surface can be reached through assigning the cutting modes based on the results of a modal analysis of the process system

Study of the effect of cutting modes on output parameters under high-speed steel turn-milling

Introduction. The article elucidates increasing the efficiency of turn-milling of powdered metal high-speed steel products. Turn-milling can be used as an alternative to the traditional turning method. The article describes advantages of the turn-milling method. A review of studies devoted to improving the surface quality of parts when turning by milling is given. The work aims at determining the effect of cutting modes on the surface roughness by the orthogonal turning method through milling powdered high-speed steel with a monolithic cutter.Materials and Methods. Statistical analysis methods based on the creation of a mathematical model for predicting microgeometric deviations of the treated surface were used. An experimental research method was applied to verify the adequacy of the mathematical model. The experiment was planned according to the non-composite design proposed by Box and Behnken. The experiment was carried out on a turning machining center with a driving tool. Powdered highspeed steel BÖHLER S390 MICROCLEAN was used as sample material for the experiment. A monolithic carbide milling cutter served as a cutting tool. During the experiment, the cutting speed, milling width, and feed per tooth varied. The roughness of the treated surface was measured by a contact profilometer.Results. A mathematical model of the formation of surface roughness depending on the processing modes was developed. During the experiments, the effect of cutting speed, tool feed, and radial cutting depth on the roughness of the treated surface was determined. It was established that the dependence of roughness on feed had a linear character over the entire investigated range of cutting modes. In turn, the dependence of roughness on the cutting speed and cutting width had a parabolic character. The results obtained allowed us to achieve the roughness of the treated surface Ra = 1.85 without reducing the processing performance. Discussion andConclusions. The developed mathematical model reflects the impact of cutting modes on the surface roughness when turning high-speed steel with a monolithic cutter. The results of the conducted research can be used to determine the optimal cutting modes that provide a given surface quality in the manufacture of real parts under the production conditions. It is recommended to continue the research with the control of additional output parameters, such as temperature and vibration. Reducing the effect of regenerative self-oscillations on the roughness of the treated surface can be reached through assigning the cutting modes based on the results of a modal analysis of the process system.</jats:p

Estimating the Noise Level Function with the Tree of Shapes and Non-parametric Statistics

International audienceThe knowledge of the noise level within an image is a valuableinformation for many image processing applications. Estimating the noise level function (NLF) requires the identification of homogeneous regions, upon which the noise parameters are computed. Sutour et al. have proposed a method to estimate this NLF based on the search for homogeneous regions of square shape. We generalize this method to the search for homogeneous regions with arbitrary shape thanks to the tree of shapes representation of the image under study, thus allowing a more robust and precise estimation of the noise level function