Surface roughness parameter prediction and evaluation are important factors in determining the satisfactory performance of machined surfaces in many fields. The recent trend towards the measurement and evaluation of surface roughness has led to renewed interest in the use of newly developed non-contact sensors. In the present work, an attempt has been made to measure the surface roughness parameter of different machined surfaces using a high sensitivity capacitive sensor. A capacitive response model is proposed to predict theoretical average capacitive surface roughness and compare it with the capacitive sensor measurement results. The measurements were carried out for 18 specimens using the proposed capacitive-sensor-based non-contact measurement setup. The results show that surface roughness values measured using a sensor well agree with the model output. For ground and milled surfaces, the correlation coefficients obtained are high, while for the surfaces generated by shaping, the correlation coefficient is low. It is observed that the sensor can effectively assess the fine and moderate rough-machined surfaces compared to rough surfaces generated by a shaping process. Furthermore, a linear regression model is proposed to predict the surface roughness from the measured average capacitive roughness. It can be further used in on-machine measurement, on-line monitoring and control of surface roughness in the machine tool environment.
The article presents the results of research on the finishing of M63 Z4 brass by vibratory machining. Brass alloy was used for the research due to the common use of ammunition elements, cartridge case and good cold forming properties on the construction. Until now, the authors have not met with the results of research to determine the impact of abrasive pastes in container processing. It was found that the additive for container abrasive treatment of abrasive paste causes larger mass losses and faster surface smoothing effects. The treatment was carried out in two stages: in the first stage, the workpieces were deburred and then polished. Considerations were given to the impact of mass of workpieces, machining time and its type on mass loss and changes in the geometric structure of the surface. The surface roughness of machining samples was measured with the Talysurf CCI Lite optical profiler. The suggestions for future research may be to carry out tests using abrasive pastes with a larger granulation of abrasive grains, and to carry out tests for longer processing times and to determine the time after which the parameters of SGP change is unnoticeable.