During the robotic milling process, vibration is one of the main factors that affect the machining accuracy and surface quality due to the low stiffness of the robot structure. Intelligent material, magneto-rheological elastomer (MRE), owns the features of adjustable stiffness, reversible and fast response, has been gradually used for vibration suppression. Therefore, to suppress the forced vibration for robotic milling, this paper used the principle of vibration absorption and combined it with MRE material to design a snubber. A series of excitation and milling experiments were carried out to evaluate its vibration attenuation characteristics. In the excitation experiment, sine signals with frequencies of 40 Hz, 42.02 Hz and 60 Hz with the same amplitude of 5 N were applied to the MRE absorber. In the milling experiment, the dominant frequencies under speeds of 800 RPM, 840 RPM and 1200 RPM were analyzed first. Then, the vibration mitigation characteristics of the MRE absorber during robotic milling of aluminum alloy were explored by adjusting the current. Experimental results showed that under the action of MRE absorber, the acceleration responses are suppressed effectively. In detail, after tuning the current, the amplitude and the root mean square of vibration acceleration in three directions of sinusoidal excitation could be suppressed by more than 19.23% and 7.35% correspondingly. The power spectral density value of the peak frequency could be reduced by more than 69.13%. In milling experiments, the MRE absorber also achieved certain vibration absorption effects. Furthermore, the surface roughness of the workpiece was also fallen by more than 16.51% which provides support for further engineering application in the field of robotic milling. Undoubtedly, the absorber needs further optimization to achieve better vibration suppression ability and a larger working bandwidth.

Directing at the hard machinability of high volume fraction 70% SiCp/Al composites, a longitudinal and torsional ultrasonic-assisted milling (LTUAM) method is proposed to improve the edge quality and machining efficiency. By observing the metallographic structure of the material, a three-dimensional (3D) finite element model of random distribution of spherical, elliptical and polygonal SiC particles is established and analyzed by ABAQUS simulation software. The formation mechanism of edge defects, stress distribution, defect characteristics and the effect of machining parameters on milling forces are investigated during ultrasonic-assisted milling. The results show that the edge defects appear at the inlet, outlet and middle edge position, especially is more serious at the outlet position. The SiC particles failure modes mainly include particle pullout, particle shearing, and crushing, moreover, the edge defects mainly include matrix tearing, edge breakage, burrs, bulges and pits. Ultrasonic-assisted milling (UAM) with a certain range of ultrasonic amplitude could effectively reduce the surface fragmentation rate and milling force, and it not only could slow down the expansion of cracks, but also increase the plastic flow of material, and obtain better edge quality compared with the traditional machining method. Comparing the results of finite element analysis and experimental tests, it shows that the simulation results are in good agreement with that of tests.

The machining system based on an industrial robot is a new type of equipment to meet the requirements of high quality, high efficiency and high flexibility for large and complex components of aircraft and spacecraft. The error compensation technology is widely used in robotic machining to improve the positioning accuracy of an industrial robot with the intention of meeting the precision requirements of aerospace manufacturing. However, the robot’s positioning accuracy decreases significantly when the orientation of the tool changes dramatically. This stems from the fact that the existing robot compensation methods ignore the uncertainties of Tool Center Point (TCP) calibration. This paper presents a novel regionalized compensation method for improving the positioning accuracy of the robot with calibration uncertainties and large orientation variation of the TCP. The method is experimentally validated through the drilling of curved surface parts of plexiglass using a KUKA KR2830MT robot. Compared with a published error compensation method, the proposed approach improves the positioning accuracy of the robot under the large orientation variation to 0.235 mm. This research can broaden the field of robot calibration technology and further improve the adaptability of robotic machining.