Surface Finishing of Zirconium Dioxide with Abrasive Brushing Tools

Selected Properties of the Surface Layer of C45 Steel Samples after Slide Burnishing

This paper presents the experimental results of a study investigating the impact of the machining fluid type, the variable factor, used in slide burnishing on 2D and 3D surface roughness; surface topography; Abbott-Firestone curve shape; microhardness; and SFE (surface free energy). In the experiment, pre-ground, ringed samples of C45 steel were used. The results showed an over eight-fold decrease in the value of the Ra (arithmetical mean deviation) parameter and over a five-fold decrease in the Rt (total height of profile) parameter in relation to their values after grinding. The parameters Rpk (reduced peak height), Rk (core roughness depth), and Rvk (reduced valley depth) were also reduced. The Abbott-Firestone curve after slide burnishing changed its angle of inclination (it was more flattened), and the material ratio Smr increased. The reduction in the Rpk and Rk parameters and increased material ratio will most likely contribute to restoring the functionality of these surfaces (increased resistance to abrasive wear). After slide burnishing, the maximum 25% increase in microhardness was obtained compared to the value after grinding, while the layer thickness was 20 μm. The surface energy of elements subjected to slide burnishing using various machining fluids slightly increased, or its value was close to that of the ground surface. The most favourable properties of the surface layer in terms of mating between two elements were obtained for a part that was slide-burnished with a mixture of oil + polymethyl methacrylate (PMM) + molybdenum disulphide (MoS2).

Numerical and Experimental Research on the Brushing Aluminium Alloy Mechanism Using an Abrasive Filament Brush

Abrasive filament brushes have been widely used in surface processes for a wide range of applications, including blending, edge-radiusing, and polishing. However, the associated brush mechanics of material removal is still not clear. In order to analyze the brush grinding of aluminium alloy, this paper constructed a kinematic model of a single filament, simulated the scratch process of a single abrasive grain, and investigated the brush force and material removal based on the finite element approach. The simulated result shows that the brush grinding can be changed from elastic-plastic deformation to chip formation when increasing the brush speed to 1000 r/min. The normal and tangential forces increase linearly and quadratically with the increase in the rotation speed (500-5000 r/min), respectively, and increase linearly with the increase in the penetration depth (0.1-1 mm), which is consistent with the experiment results. In addition, the amount of material removal initially increases with the increase in penetration depth, and then decreases. This paper provides a new approach to understanding the process of material removal and is helpful for the selection of reasonable brush parameters in the intelligent grinding control application.

Advances and Trends in Non-Conventional, Abrasive and Precision Machining

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Data-Driven Intelligent 3D Surface Measurement in Smart Manufacturing: Review and Outlook

High-fidelity characterization and effective monitoring of spatial and spatiotemporal processes are crucial for high-performance quality control of many manufacturing processes and systems in the era of smart manufacturing. Although the recent development in measurement technologies has made it possible to acquire high-resolution three-dimensional (3D) surface measurement data, it is generally expensive and time-consuming to use such technologies in real-world production settings. Data-driven approaches that stem from statistics and machine learning can potentially enable intelligent, cost-effective surface measurement and thus allow manufacturers to use high-resolution surface data for better decision-making without introducing substantial production cost induced by data acquisition. Among these methods, spatial and spatiotemporal interpolation techniques can draw inferences about unmeasured locations on a surface using the measurement of other locations, thus decreasing the measurement cost and time. However, interpolation methods are very sensitive to the availability of measurement data, and their performances largely depend on the measurement scheme or the sampling design, i.e., how to allocate measurement efforts. As such, sampling design is considered to be another important field that enables intelligent surface measurement. This paper reviews and summarizes the state-of-the-art research in interpolation and sampling design for surface measurement in varied manufacturing applications. Research gaps and future research directions are also identified and can serve as a fundamental guideline to industrial practitioners and researchers for future studies in these areas.