Frictional Behaviour of the Microstructural Surfaces Created by Cylindrical Grinding Processes

Cylindrical surface grinding can create defined textural patterns on a component with high quantity. This paper presents an experimental investigation of the frictional behaviours of ground cylindrical microstructural surfaces under a well lubrication condition. It shows that the coefficient of friction (COF) of microstructural surface is influenced by different workload and rotation speed. The results reveal that conventional surface roughness parameters do not present the influence of surface microstructure on friction performance well. However, the paper presents an interesting discovery that the friction behaviour of microstructural surfaces created by grinding could be controlled by combining dressing and grinding conditions. Such a discovery provides a logic way to reduce surface friction for energy efficiency applications. A few functional relationships have been established to illustrate the influence of microstructural features on friction. It was found that the ground microstructural surface could improve friction performance up to 20% compared to the smoother surfaces without defined surface textural patterns.

A Novel Biomimetic Nanocomposite Exhibiting Petal Wetting Phenomenon: Fabrication and Experimental Investigations

A functional composite material that simultaneously exhibits hydrophobicity and water droplet adhesion has monumental potential in controlling fluid flow, studying phase separation, and biological research. This article reports the fabrication of a petal wetting biomimetic Boron Nitride Nanotubes (BNNTs) -Polydimethylsiloxane (PDMS) nanocomposite achieved by drop casting. The petal effect was investigated by non-destructive techniques. The nanotubes were synthesized by chemical vapor deposition at 1150 °C and were characterized by X-ray diffraction, scanning electron microscopy, and high-resolution transmission electron microscopy. The mean diameter of the nanotubes was found to be 70 nm. The nanocomposites had BNNT fillers ranging from 0.5 wt. % to 2 wt. %. Water contact angles for pure PDMS polymer was 94.7° and for the 2 wt. % BNNT-PDMS nanocomposite was 132.4°. The petal wetting nanocomposite displayed a characteristic trait of high contact angle hysteresis. The surface roughness parameters of the nanocomposites were determined by atomic force microscopy. Laser scanning confocal microscopy aided in analyzing the droplet penetration and in observing the trapped air between the water droplet and the nanocomposite surface. Based on surface observations, roughness parameters, and the extent of droplet penetration by the surface, we shed light on the Cassie impregnating wetting regime followed by the biomimetic nanocomposite. Such a surface would be beneficial in the study of the embryogenesis of cells and aid in moisture collection.

The Influence of the Material Type and the Placement in the Print Chamber on the Roughness of MJF-Printed 3D Objects

This paper describes a surface-roughness study performed on samples manufactured additively using the Multi Jet Fusion (MJF) technology. The samples were divided into three groups based on the material used in the process: polypropylene (PP), thermoplastic polyurethane (TPU), and polyamide 11 (PA11). Subsequently, they were tested by means of a roughness-measuring system, which made it possible to determine the typical surface roughness parameters (Ra, Rq, Rz). The tests were designed to examine whether the placement and orientation of 3D objects while printing, in connection with the material used, can significantly influence the surface quality of MJF-printed objects. The results show that the TPU samples have a surface roughness much higher than the PP and PA11 ones, which exhibit roughness levels very similar to each other. It can also be concluded that surfaces printed vertically (along the Z-axis) tend to be less smooth—similarly to the surfaces of objects made of TPU located in the central zones of the print chamber during printing. This information may be of value in cases where low surface roughness is preferred (e.g., manufacturing patient-specific orthoses), although this particular study does not focus on one specific application.

Artificial neural network tools for predicting the functional response of ultrafast laser textured/structured surfaces

Artificial Neural Networks (ANNs) are well-established knowledge acquisition systems with proven capacity for learning and generalisation. Therefore, ANNs are widely applied to solve engineering problems and are often used in laser-based manufacturing applications. There are different pattern recognition and control problems where ANNs can be effectively applied, and one of them is laser structuring/texturing for surface functionalisation, e.g. in generating Laser-Induced Periodic Surface Structures (LIPSS). They are a particular type of sub-micron structures that are very sensitive to changes in laser processing conditions due to processing disturbances like varying Focal Offset Distance (FOD) and/or Beam Incident Angle (BIA) during the laser processing of 3D surfaces. As a result, the functional response of LIPSS-treated surfaces might be affected, too, and typically needs to be analysed with time-consuming experimental tests. Also, there is a lack of sufficient process monitoring and quality control tools available for LIPSS-treated surfaces that could identify processing patterns and interdependences. These tools are needed to determine whether the LIPSS generation process is in control and consequently whether the surface’s functional performance is still retained. In this research, an ANN-based approach is proposed for predicting the functional response of ultrafast laser structured/textured surfaces. It was demonstrated that the processing disturbances affecting the LIPSS treatments can be classified, and then, the surface response, namely wettability, of processed surfaces can be predicted with a very high accuracy using the developed ANN tools for pre- and post-processing of LIPSS topography data, i.e. their areal surface roughness parameters. A Generative Adversarial Network (GAN) was applied as a pre-processing tool to significantly reduce the number of required experimental data. The number of areal surface roughness parameters needed to fully characterise the functional response of a surface was minimised using a combination of feature selection methods. Based on statistical analysis and evolutionary optimisation, these methods narrowed down the initial set of 21 elements to a group of 10 and 6 elements, according to redundancy and relevance criteria, respectively. The validation of ANN tools, using the salient surface parameters, yielded accuracy close to 85% when applied for identification of processing disturbances, while the wettability was predicted within an r.m.s. error of 11 degrees, equivalent to the static water contact angle (CA) measurement uncertainty.

Prediction of Surface Roughness During Dry Sliding Wear

Due to the relatively low strength and poor wear resistance of unalloyed titanium and its good mechanical properties, corrosion resistance, and biocompatibility. Ti6Al4V has been extensively used in various type of application including aerospace, biomedical and offshore industries. The goal of this research is to enhance the surface properties of the high strength alloys are examine such as Ti6Al4V pin sliding against Al2O3disc, due to the various surfaces roughness parameters. The COF and the wear rate were found to be lower at higher applied load due to higher frictional heating leading to thermal oxidation and thereby formation of several mm thick tribo-layers on the worn surfaces. Characterization of the tribological sample was performed using a scanning electron microscope (SEM) equipped with energy dispersive X-ray analysis (EDAX) to ensure that the wear pattern and debris morphologies of the Ti6Al4V and alumina disks were distinct, suggesting a surface roughness value determined by 3D profilometer at various load and sliding speed of 0.01ms-1.

3D texture parameters for wear scars after severe regime

Purpose This paper aims to present an analysis of several 3 D texture parameters for the entire wear scars obtained in severe regime, on a four-ball tester. The aim of this analysis is to correlate the tribological parameter as wear scar diameter to texture parameters. Design/methodology/approach Tested lubricants were rapeseed oil, rapeseed oil additivated with 1% Wt nano TiO2 and rapeseed oil additivated with 1%Wt nano ZnO. The severe regime was applied for 1400 rpm and for loads increasing in steps of 50 N, from 500 to 900 N. Several analyzed roughness parameters (height parameters and functional ones) could be related to the evolution of a wear parameter, the wear scar diameter. Comparing the values for neat rapeseed oil and additivated variants, the texture parameters allow for evaluating if the additives protect or not the worn surfaces. Findings Measurements pointed out two groups of roughness parameters: one that has an evolution depending on wear scar diameter (WSD) and load (Sa, St, functional parameters) and one including Ssk that has shown no dependence on load and WSD. Also, the functional parameters Spk and Svk follow in a similar manner the wear parameter, WSD, but Sk is the least dependent on load. For the highest load, amplitude parameters such as Sa and St are following the tendency of WSD. Each lubricant has its particular correlation between wear parameters and texture quality, expressed by the help of a set of roughness parameters. Research limitations/implications Such studies help tribologists to rank lubricants based on a combined analysis with wear parameters and texture parameters. Practical implications The results allow for evaluating new formulated lubricants. Originality/value The study on the quality on worn surfaces introduces the original idea of analyzing the entire wear scar surface (approximated by an ellipse with the axes as those experimentally measured) by the help of a set of 3 D roughness parameters.

A GEOMETRICAL SURFACE TEXTURE STUDY OF CYCLOID DRIVE DISCS AFTER BENCH TESTS

The article presents the results of a geometrical surface texture study of cycloid drive discs after bench tests. For this purpose, the working surfaces, such as peak and valley areas of the epicycloid and the holes inner surfaces of both discs, were investigated using contact profilometry. From each surface, a transverse profiles were extracted, before and after 50 cycles of bench test. The discs and the profiles were examined for signs of wear and roughness changes. For each profile, the Ra and Rz roughness parameters were determined. On the base of the obtained profiles and the values of roughness parameters, it can be stated that the assumed test parameters provide stable working conditions, with an uninterrupted lubrication film, which results in practically negligible and unmeasurable wear. Taking into account the operating specification of a helicopter winch as an example of potential application of the presented cycloidal drive, the developed solution fulfils the requirements concerning wear resistance.

Anomalies in the Geometric Surface Structure of Shaped Elements Composed of Inconel 718 Alloy

This paper presents the results of investigation that was performed on shafts composed of Inconel 718. Tests were performed in dry and wet conditions. Cutting parameters, such as feed and depth of cut, were constant. The cutting speed was changed. The investigation was performed for various shaft shapes: cylindrical, taper 30°, taper 45°, and sphere. For that reason, the value of the angle between the machined surface and the cutting edge changed. The lowest values of the roughness parameters, Ra and Rz, were obtained for a larger value of the angle between the machined surface and cutting edge. The investigation showed that cutting speed, machining conditions (dry and wet machining), and the variable angle between the machined surface and the cutting edge influenced the surface roughness. Application of a higher cutting speed resulted in lower roughness values. Lower values of roughness parameters were obtained by wet machining.