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The main aim of this paper is description of new apparatus and approach for contact less evaluation of surface roughness. For characterization of surface roughness, the procedures based on classical and non‐classical (complexity) parameters are proposed.

For obtaining the roughness profile in the selected direction (on the line transect of the surface), the special arrangements of textile bend around sharp edge is used. The image analysis is used for extraction of surface profile. The system of controlled movement allows one to obtain surface roughness profile in two dimensions.

By using aggregation (cut length principle), the roughness resolution is decreased and roughness profile is created without local roughness variation. After application of cut length principle, the direct combination of slices leads to the creation of roughness surface.

There exists plenty of roughness characteristics based on standard statistics or analysis of spatial processes. For evaluation of suitability of these characteristics, it will be necessary to compare results from sets of textile surfaces.

The measurement of fabric roughness by an RCM device is useful as simple tool for description of roughness in individual slices and in the whole rough plane. This method replaces the traditional contact stylus profiling methods

The reconstruction of surface roughness from individual slices. The utilization of aggregation principle for creation of micro and macro roughness. The evaluation of roughness parameters based on the geometrical characteristics, harmonic analysis and complexity indices.

The purpose of this paper is to explore the effect of surface roughness characterized by fractal geometry on squeeze film damping characteristics in damper of the linear rolling guide, which has not been studied so far.

The stochastic model of film thickness between rail and damper is established by using the two-variable Weierstrass–Mandelbrot function defining multi-scale and self-affinity properties of the rough surface topography. The stochastically averaged Reynolds equation is solved by using the variables separation method to further derive the film pressure distribution, the damping coefficient, the damping force and squeeze film time. The effect of surface roughness on squeeze film damping characteristics of the damper is analyzed and discussed through simulation.

By comparing cases of the rough surface for different fractal parameters and the smooth surface, it is shown that for the isotropic roughness structure, the presence of surface roughness of the damper decreases the squeeze film damping characteristics. It is found that roughness effect on the damping coefficient is associated with the film thickness. In addition, the vibration amplitude effect is negligible for the damper of the linear rolling guide.

To investigate the random surface roughness effect, the rough surface topography of damper of the linear rolling guide is characterized by using the fractal method instead of the traditional mathematical statistics method.

The purpose of this paper is to investigate the coupling mechanism of the roughness distribution characteristic and surface textures on the cylinder liner.

The cylinder liner-piston ring lubrication model with non-Gaussian roughness distribution surface was proposed in this paper to find the optimum cylinder liner surface. The motored engine tests were carried out to verify the simulation results.

The calculation and experiment results show that the large negative skewness surface has the optimal lubrication performance in the un-textured liner, while in the textured liner, the small negative skewness surface is more appropriate, which means surface textures couple with small negative skewness surface can improve the lubrication performance.

Although there are some works related to liner surface roughness and textures, the combine of roughness distribution and surface textures is not usually taken into account. Therefore, this research is different from others, as the present model considers with real non-Gaussian roughness distribution liners.

Aluminium silicon carbide reinforced metal matrix composite (Al/SiC‐MMC) materials are rapidly replacing conventional materials in various automotive, aerospace and other industries. Accordingly, the need for accurate machining of composites has increased enormously. The present work analyzes the machining of Al/SiC composites for surface roughness. An empirical model has been developed to correlate the machining parameters and their interactions with surface roughness. Response surface regression and analysis of variance are used for making the model. The developed model can be effectively used to predict the surface roughness in machining Al/SiC‐MMC composites. The influences of different parameters in machining Al/SiC particulate composites have been analyzed through contour graphs and 3D plots.

This study aims to present the optimization of parameters and effects of annealing and vapor smoothing post-processing treatments on the surface roughness and tensile mechanical properties of fused deposition modeling (FDM) printed acrylonitrile butadiene styrene (ABS).

Full-factorial test matrices were designed to determine the most effective treatment parameters for post-processing. The parameters for annealing were temperature and time, whereas the parameters for the vapor smoothing were volume of acetone and time. Analysis of surface roughness and tensile test results determined influences of the levels of parameters to find an ideal balance between mechanical properties and roughness.

Optimal parameters for vapor smoothing and annealing were determined. Vapor smoothing resulted in significantly higher improvements to surface roughness than annealing. Both treatments generally resulted in decreased mechanical properties. Of all treatments tested, annealing at 100 °C for 60 min provided the greatest benefit to tensile properties and vapor smoothing with 20 mL of acetone for 15 min provided the greatest benefit to surface roughness while balancing effects on properties.

Vapor smoothing and annealing of FDM ABS have typically been studied independently for their effects on surface roughness and material properties, respectively, with varying materials and manufacturing methods. This study objectively compares the effects of each treatment on both characteristics simultaneously to recommend ideal treatments for maximizing the balance between the final quality and performance of FDM components. The significance of the input variables for each treatment have also been analyzed. These findings should provide value to end-users of 3D printed components seeking to balance these critical aspects of manufacturing.

The purpose of this study is to realize the multi-objective optimization for MRR and surface roughness in micro-milling of Inconel 718.

Taguchi method has been applied to conduct experiments, and the cutting parameters are spindle speed, feed per tooth and depth of cut. The first-order models used to predict surface roughness and MRR for micro-milling of Inconel 718 have been developed by regression analysis. Genetic algorithm has been utilized to implement multi-objective optimization between surface roughness and MRR for micro-milling of Inconel 718.

This paper implemented the multi-objective optimization between surface roughness and MRR for micro-milling of Inconel 718. And some conclusions can be summarized. Depth of cut is the major cutting parameter influencing surface roughness. Feed per tooth is the major cutting parameter influencing MRR. A number of cutting parameters have been obtained along with the set of pareto optimal solu-tions of MRR and surface roughness in micro-milling of Inconel 718.

There are a lot of cutting parameters affecting surface roughness and MRR in micro-milling, such as tool diameter, depth of cut, feed per tooth, spindle speed and workpiece material, etc. However, to the best our knowledge, there are no published literatures about the multi-objective optimization of surface roughness and MRR in micro-milling of Inconel 718.

Investigates the effects of the most influential cutting parameters (cutting speed, feed rate, depth of cut, tool nose radius, tool length and work piece length) on surface roughness quality and on the formation of built‐up edge in a lathe dry turning process of mild carbon steel samples. A full factorial design (384 experiments), taking into account the three‐level interactions between the independent variables has been conducted. The results show that the following three‐level interactions: feed rate × cutting speed × depth of cut, feed rate × cutting speed × tool nose radius and tool nose radius × depth of cut × tool length have significant effects on surface roughness in this type of machining operation. Shows that the analysis of main effects alone and even two‐level interactions could lead to a false interpretation of the results. The analysis of variance revealed that the best surface roughness is achieved with a low feed rate, a large tool nose radius and a high cutting speed. The results also show that the depth of cut has no significant effect on surface roughness when operating at cutting speeds higher than 160m/min. Furthermore, it is shown that built‐up edge formation deteriorates surface roughness when machining mild carbon steel at specific feed rate, tool nose radius and cutting speed levels. Proposes a new model for evaluating the limiting cutting speed to avoid the built‐up edge formation. Finally, shows through experimentation that an increase in depth of cut would lead to improved surface roughness when tool vibration is increased.

Fused deposition modeling (FDM) is one of the most adopted additive manufacturing techniques to produce prototypes and/or final parts regardless of geometrical complexity restrictions. One of the most challenging aspects of this technology is the attainable roughness. The purpose of this study is to evaluate the capability of the slurry impacts to improve the surface roughness of parts fabricated using FDM. Moreover, a regression model for predicting the values of surface roughness was developed.

The developed technique imposes a silica–water mixture which softens the staircase on the surface and leaves it smoother. The process introduces three main factors: building orientation; layer thickness; and impact angle of the slurry particles. Experimentally, a test rig was used to evaluate the effect of these factors on surface roughness. Statistically, Analysis of variance (ANOVA) and regression analysis were conducted to study the contribution of the individual factors on the roughness.

The results reveal that the effect of slurry impacts has a good impact on surface roughness, and the three factors have significant effect on surface roughness.

This paper contributes to new knowledge by providing a new technique for enhancing the surface roughness of FDMed products. ANOVA and regression analysis is a useful tool to parametrically study the surface roughness in terms of building and testing factors.

The purpose of this paper is to get a better understanding of roughness evolution and micropitting initiation on the tooth flank, as well as the evolution of surface topography during the test load stages in a modified DGMK short micropitting test procedure.

A modified DGMK short micropitting test procedure was performed, using an increased number of surface observations (three times more) in order to understand the evolution of the surface during each load stage performed. Each of these surface observations consists in the evaluation of surface roughness, surface topography, visual inspection and also weigh measurements as well as lubricant analysis.

This work showed that the larger modifications on surface took place in the beginning of tests, especially during load stage K3 (lowest load, considered as running‐in) and on the first period of load stage K6, that is, during the first 200,000 cycles of the test. The 3D roughness parameters (St and Sv), obtained from the surface topographies, gave a more precise indication about surface roughness evolution and micropitting generation than the 2D parameters, especially in what concerns to inferring the depth of micropits and the reduction of roughness. Tooth flank topography allows to identify local changes on the surface and the appearance of first micropits.

This work was performed with gears holding a high surface roughness and with a ester‐based lubricant. It was interesting to see the differences observed for surface evolution, for other base oils and also for gears with lower roughness.

The main implication of this work is the understanding that major changes in the surface took place in the first cycles, indicating that the running‐in procedure could be very important for the surface fatigue life. This work also showed that micropitting depends on local contact conditions. Depending on the roughness of the counter surface, micropitting can appear on the bottom of the deep valleys and/or do not appear on the tip of the roughness peaks. The surface topography, and implicitly 3D roughness parameters, is very useful for the observation of surface evolution.

This paper shows in detail the evolution of the tooth surface during a micropitting test. The micropits generation and evolution and also surface wear evolution are presented.

This paper presents a study of the development of surface roughness model when turning the mild steel hardened up to 484 HV with mixed alumina ceramic (KY1615) and coated alumina ceramic cutting tools (KY4400). The model was developed in terms of main cutting parameters such as cutting speed, feed rate and depth of cut, using response surface methodology. The established equation indicated that the feed rate affected the surface roughness the most, but other parametres remined stable for arithmetic average height parametre (Ra). However, it decreased with increasing the cutting speed, and with the starting and finishing point of cut for ten point height parametre (Rz). The cutting speed and the depth of cut had a slight effect on surface roughness values of Ra, Rz when using KY4400 cutting tools. Furthermore, the average surface roughness value of Ra was about 0.926 um, 1.089 um for KY1615, KY4400 cutting tools, respectively. The predicted surface roughness was found to be very close to experimentally observed ones at 95% confidence level. Moreover, analysis of variance indicated that squares terms were significant but interaction terms were insignificant for both cutting tools.