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AbstractThis study aims to evaluate the lubrication performance of a nano-TiO2 oil-in-water (O/W) emulsion during the hot rolling process. A series of O/W emulsions with varying concentrations of TiO2 nanoparticles (0.05, 0.1, 0.3, and 0.5 wt.%) were synthesized. Tribological tests were conducted under a load of 70 N for 10 minutes to determine the optimal concentration based on anti-frictional properties. The O/W nano-emulsion optimized with a 0.1 wt.% concentration of TiO2 applied in the hot rolling process of IS 2062 E250 grade steel. This application resulted in a reduction of rolling force (RF) and surface roughness, suggesting its potential as an alternative lubricant. The results indicated superior antifriction performance at a TiO2 concentration of 0.1 wt.%, leading to a 15% reduction in RF. Additionally, the use of the nano-emulsion contributed to a significant reduction in oxide scale formation. Surface roughness measurements of the rolled samples revealed a 19% decrease, with a roughness value of 2.125 µm, compared to samples rolled with a nano-free O/W emulsion. These findings suggest that nano-TiO2 O/W emulsions could serve as an effective alternative to conventional O/W emulsions in future industrial metalworking applications. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the bond strength between PEEK/PEKK and composite resins after various laser treatments and to compare the effectiveness of lasers on these polymers. 130 disc-shaped PEEK and PEKK blocks were obtained (10 mm diameter-4 mm height). One sample from each group (10 in total) was selected for scanning electron microscopy (SEM) analysis. The samples were randomly divided into 5 different surface treatment groups for each material (PEEK and PEKK): Er: YAG laser, Nd: YAG laser, diode laser, femtosecond laser and control (no surface treatment) (n = 12). Baseline and post-treatment surface roughness measurements were performed using a profilometer. The composite resin was bonded and SBS was measured. Comparisons among the groups were conducted via Kruskal–Wallis, one-way ANOVA; Tukey and Dunn tests were used as a post hoc test (p ≤ 0.05). All lasers significantly increased the roughness values of the PEEK and PEKK samples. In terms of shear bond strength; the Er: YAG and femtosecond laser groups had the highest values and the Nd: YAG, diode and control groups had the lowest values of the PEEK samples (p ≤ 0.05). The control group had the highest bond strength values and the femtosecond group had the lowest values for PEKK samples (p ≤ 0.05). All laser treatments increased the surface roughness of the PEEK and PEKK. Lasers increased the bond strength of PEEK to the veneering composite resin and decreased the bond strength values of PEKK. This shows that lasers behave differently in PEEK and PEKK materials. [ABSTRACT FROM AUTHOR]

Traditional mechanical processing of zirconium leads to an unfavorable transformation, from a metastable tetragonal phase to a monoclinic phase (t→m), which weakens the structure of the material and subsequently leads to damage to the prosthetic restoration. The aim of this research is to compare commonly used surface treatments to determine which has the least effect on t→m. Thirty cylindrical samples made of sintered zirconium were divided into six groups based on the following treatments: polishing, grinding, sandblasting, chemical etching, laser structuring or dry plasma etching. After surface treatment, the samples were subjected to the following tests: X-Ray Diffraction, microscopic examination, surface wettability and surface roughness measurements. Chemical etching, laser structuring and plasma etching significantly reduce the content of the monoclinic phase. All surface treatments significantly reduced the final amount of the monoclinic phase. However, chemical etching did not provide sufficient surface roughness. Both laser and plasma processing offer the advantage of creating structural patterns on the surface of elements. However, as plasma etching requires a mask to obtain the appropriate pattern on the surface, it seems that laser processing offers more and varied structuring possibilities. Laser structuring is easier to control and more economical than the other methods. [ABSTRACT FROM AUTHOR]

Wire-electrical discharge machining (wire-EDM) is gaining wider acceptance for producing components of Al-matrix composites (Al-MCs) that are hard to machine by traditional methodologies. The related research is primarily limited to ex-situ Al-MCs commonly reinforced with ceramic particles; however, Al-MCs reinforced with in-situ ordered intermetallics have evolved as superior composites nowadays. This research has focused on wire-EDM of in-situ Al/Al3Fe composites developed by the reactive stir-casting route. The influence of three machining variables (pulse-on-time, servo voltage, and peak-current) and one material parameter (vol% of reinforcement) have been studied following the L27 Taguchi design. The integrity of the machined surface has been characterized via measurements of surface roughness (SR) and the alteration of surface chemistry (ASC, ΣCu + Zn + O), in addition to the evaluation of kerf width (KW) as a machining performance indicator. It has been established that all four control factors are significant for KW, while ASC is influenced by all factors except vol% of reinforcement; however, only pulse-on-time is substantial for SR. Analytical models of individual responses are developed while the desirability approach helps to accomplish the multi-response optimization; several confirmation experiments establish the authenticity of these predictions with an error < 8%. Characterizations of machined surfaces and wire electrodes by FESEM and EDS techniques reveal that the surface integrity of in-situ Al/Al3Fe composites varies significantly with machining conditions. [ABSTRACT FROM AUTHOR]

This paper presents the influence of the preparation of the inspected surface on the deviations obtained when measuring the basic roughness parameters using the contact method. The problems described in the article are often encountered in industry when measurements are performed in mass production conditions, where a short measurement time is extremely important. Presented are the measurement results of five samples made of 1.0503 steel after the grinding process, subjected to various methods of preparation for roughness measurement: sample immediately after treatment, sample after treatment and after evaporation of liquid part of the coolant, sample after blowing with compressed air, sample after blowing with compressed air and washing in isopropyl alcohol, and the sample after blowing with compressed air and washing with acetone. The measurement results obtained from the contact profilometer provide the basis for developing recommendations regarding the preparation of surfaces for inter-operational and final measurements in the production process. [ABSTRACT FROM AUTHOR]

AbstractTraditional electrical discharge machining (EDM) electrodes have several limitations such as long machining time, low material removal rate MRR, hazard emissions and high energy consumption. To overcome these limitations, new electrodes (plane and frame U-shaped) were manufactured considering the electrode manufacturing classifications, such as electrode flushing mechanism, electrode cross-sectional area and electrode bottom machining area. Experiments were performed on a die-sinking EDM machine using copper electrodes and aluminum alloy workpieces. The results were compared with those obtained using the conventional electrode. The newly manufactured electrodes significantly improved the EDM process performance, reducing the machining time by more than 50%, which implies a higher MRR. The reduced machining time also led to lower costs, emissions and energy consumption for efficient EDM processes. Additionally, surface roughness measurements were performed to compare the surface quality of the machined areas using different pulse-code generator systems and electrodes. The results showed an improvement in the machined surface quality when using the new electrodes in comparison with the conventional electrode when using a roughing pulse code generator system. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to evaluate the interactions of fluoride-containing gels and varnishes on the optical properties and surface texture of composite resins, compomers, and bulk-fill composite resins. Thus, it seeks to address the current gap in the literature regarding the effect of fluoride agents on bulk-fill restorative materials. Methods: Using Teflon moulds, 50 specimens of 6 mm diameter and 2 mm thickness were produced for each of the G-ænial Posterior, Filtek™ One Bulk-Fill and Dyract-XP materials. Baseline color and surface roughnesss measurements of the specimens were performed. The specimens were subjected to the following applications: Study groups (Topex NaF gel, Topex APF gel, ProShield varnish, and MI varnish with RECALDENTTM) and Control group (distilled water). Color and surface roughness measurements were repeated after the application period. The surface microhardness of the specimens (study groups and control group) was measured using Vickers microhardness tester. Statistical analyses, including two-way analyses of variance (comparison of color, whiteness and microhardness parameters) and three-way analyses of variance (comparison of surface roughness parameter), and Pearson's correlation test (the relationship between surface roughness and color change and surface roughness), were applied. Results: The restorative material significantly (p-value<0.001) influenced the color changes (ΔE00), with the Filtek™ One Bulk-Fill/Topex APF gel interaction yielding the highest ΔE00 average value (2.1±1.15). Materials and fluoride agents exerted significant effects on the Whiteness Index (ΔWID) for Dentistry (pvalue< 0.001). Dyract-XP displayed lower initial surface roughness (1.05±1.38), with all materials exhibiting comparable values after fluoride treatment. Microhardness varied among the materials, with Filtek™ One Bulk-Fill having the highest total value (65.39±2.67) and G-ænial Posterior having the lowest total (42.97±3.32) value. When considering the interaction of restorative materials, fluoride treatment, Topex APF gel-treated G-ænial Posterior showed the lowest (40.56±1.78) microhardness, whereas Filtek™ One Bulk-Fill showed the highest (65.06±1.88) values. Conclusions: Topical fluoride agents induce alterations in the color, roughness, and hardness of restorative materials, depending on the material type, fluoride agent, and duration of application. [ABSTRACT FROM AUTHOR]

Surface grinding is a widely employed finishing process in industrial sectors dedicated to achieve desired Surface characteristics of components. This study experimentally investigates the impact of the grinding parameters pertaining to the surface characteristics of Inconel 800, which is a nickel-iron-chromium alloy extensively used in high-temperature applications. Various commercially available grinding wheels were employed to grind Inconel800 under different grinding conditions. The ground surfaces were comprehensively analyzed using surface roughness measurements, Three-dimensional profilometry, optical microscopy, findings from XRD and SEM reveal that grinding parameters and wheel characteristics significantly impact the surface texture, topographical features, residual stress, and surface morphology of the machined nickel alloy.. The insights from this investigation contribute to the understanding of the grinding behavior of nickel-based superalloys and provide a basis for optimizing the grinding process for enhanced surface integrity. The findings are valuable for industries dealing with the machining of high-performance nickel alloy components. [ABSTRACT FROM AUTHOR]

The heat transfer surfaces of heat exchangers are usually made of metals which may suffer from severe corrosion. When corrosive fluids are present, highly corrosion-resistant metals, graphite or ceramics are used, resulting in high costs. This study presents measured data on the thermophysical and mechanical properties of recently developed corrosion-resistant polymer composite tubes for use in heat exchangers. Extruded polymer composite tubes based on polypropylene or polyphenylene sulfide filled with graphite flakes were investigated. The anisotropic thermal conductivities of the polymer composite tubes were measured at various temperatures. The through-wall thermal conductivity of the tubes made of polypropylene filled with 50 vol.% graphite is increased by a factor of 30 compared to pure polypropylene, resulting in a thermal conductivity of 6.5 W/(m K) at 25 °C. The tubes composed of polyphenylene sulfide filled with 50 vol.% graphite have a through-wall thermal conductivity of 4.5 W/(m K) at 25 °C. The mechanical properties of the polymer composites were measured using tensile and flexural tests at different temperatures. The composite materials are more rigid and keep their mechanical properties up to a higher temperature level compared to the unfilled polymers. Surface roughness measurements show the very smooth and sealed surface of the composite tubes. The results contribute to establishing the viability of using polymer composites for heat exchanger applications with corrosive fluids. [ABSTRACT FROM AUTHOR]

The performance of the final part of the turning process, a topic of practical importance, heavily depends on the cutting parameters. Surface quality, a crucial product attribute in manufacturing, often tops consumer demands during machining due to its significant influence on product functionality. This paper assesses the correlation between the detected vibration signal, statistical parameters (Crest, Kurtosis and I-kaz3D coefficient) and surface roughness and provides valuable insights for practical applications. When the tool experiences vibrations during material removal, these oscillations leave a ripple effect on the surface of the workpiece. We aim to determine the impact of cutting parameters on surface roughness while turning 42CrMo4 steel using a carbide tool insert. Cutting parameters, such as spindle speed, feed, and depth of cut, were used. Signal processing is carried out using different techniques to identify the effect of the cutting parameters on vibration signals. Finally, we delve into the interaction effects between the cutting parameters, vibration signals and surface roughness, offering a comprehensive understanding of real-world manufacturing scenarios. Higher I-kaz3D coefficients correspond to higher surface roughness values. The I-kaz3D coefficient decreases as the surface roughness measurements decrease, indicating that the I-kaz3D technique can accurately indicate an increase or decrease in surface roughness. On the other hand, the cutting force Fc was the component most strongly correlated with surface roughness (Ra), yielding the best results across all indices (adjusted R²adj = 95.1%, er=.8 ± 2.3%). [ABSTRACT FROM AUTHOR]

The visual measurement method of grinding surface roughness is mainly predicted by designing image feature indicators. In contrast, the self-extraction method of grinding surface features based on deep learning has problems such as noise, low resolution and poor perception of details. This paper proposes a visual measurement method for grinding surface roughness to address these problems by combining filters and branching convolutional networks. The method adopts a two-branch convolutional neural network, inputs the images using filter denoising and the original grinding workpiece surface images simultaneously, self-extracts roughness correlation features and fuses them to achieve feature enhancement, effectively improves the recognition accuracy and generalisation ability of the model, and verifies the robustness of the model in the case of rusting on the workpiece surface. The experimental results show that the method can effectively solve the problem of the grinding process’s weak and difficult recognition of surface roughness feature information and provide a basis for automated visual online measurement of grinding surface roughness. [ABSTRACT FROM AUTHOR]

The TC4 titanium alloy is widely used in medical, aerospace, automotive, shipbuilding, and other fields due to its excellent comprehensive properties. As an advanced processing technology, laser processing can be used to improve the surface quality of TC4 titanium alloy. In the present research, a new type of rotational laser processing method was adopted, by using a beam shaper to modulate the Gaussian spot into a line spot, with uniform energy distribution. The effects of the laser power and rotational speed on the laser ablation surface of the TC4 titanium alloy were analyzed. The results reveal that the melting mechanism of the material surface gradually changes from surface over melt to surface shallow melt with the increase in the measurement radius and the surface roughness increases first, then decreases and, finally, tends to be stable. By changing the laser power, the surface roughness changes significantly with the variation in the measurement radius. Because low laser power cannot provide sufficient laser energy, the measurement radius corresponding to the surface roughness peak of the microcrack area is reduced. Under a laser power of 11 W, the surface roughness reaches its peak when the measurement radius is 600 μm, which is 200 μm lower than that of a laser power of 12 W, 13 W, and 14 W. By changing the rotational speed, the centrifugal force generated by the rotation of the specimen affects the distribution and re-condensation of the molten pool of the surface. As the rotational speed increases, the shallow pit around the pit is made shallower by the filling of the pit with molten material and the height of the bulge decreases, until it disappears. The surface oxygen content of the material increases first and then decreases with the increase in the measurement radius and gradually approaches the initial surface state. Compared with a traditional laser processing spot, the rotational line spot covers a larger processing area of 22.05 mm2. This work can be used as the research basis for rotational modulation laser polishing and has significance for guiding the innovative development of high-quality and high-efficiency laser processing technology. [ABSTRACT FROM AUTHOR]

For space missions to either the Moon or Mars, protecting mechanical moving parts from the abrasive effects of prevailing surface dust is crucial. This paper compares the abrasive effects of two lunar and two Martian simulant regoliths using special pin-on-disc tests on a stainless steel/polytetrafluoroethylene (PTFE) sealing material pair. Due to the regolith particles entering the contact zone, a three-body abrasion mechanism took place. We found that friction coefficients stabilised between 0.2 and 0.4 for all simulants. Wear curves, surface roughness measurements, and microscopic images all suggest a significantly lower abrasion effect of the Martian regoliths than that of the lunar ones. It applies not only to steel surfaces but also to the PTFE pins. The dominant abrasive micro-mechanism of the disc surface is micro-ploughing in the case of all tests, while the transformation of the counterface is mixed. The surface of pin material is plastically transformed through micro-ploughing, while the material is removed through micro-cutting due to the slide over hard soil particles. [ABSTRACT FROM AUTHOR]

Selective laser melting (SLM) offers an innovative manufacturing approach compared to traditional methods. It has found diverse applications in various fields, ranging from medical devices to aerospace, using a variety of metals. However, products manufactured with the metal AlSi10Mg using the SLM technique have a significant surface roughness defect. Consequently, products produced through SLM necessitate post-processing. In this study, electro-polishing was conducted on AlSi10Mg specimens manufactured at four different inclinations. Surface roughness measurements and 3D scans were performed at various time intervals to observe changes in roughness. It was observed that an increase in electro-polishing time effectively reduced surface roughness. This research provides data on post-processing for three-dimensional structures manufactured using the SLM technique. [ABSTRACT FROM AUTHOR]

Glass is a widely used material in key fields such as Micro-Electro-Mechanical Systems (MEMS) due to its excellent properties. The existing non-traditional glass machining methods have problems such as high pollution, difficult operation, and poor sustainability, this article utilizes the effective combination of electrochemical discharge machining and grinding (named electrochemical discharge grinding, ECDG), by using NaHCO 3 solution as electrolyte to achieve green machining. Utilizing ultrasonic vibration and multi-hole tube electrode to achieve precise and stable machining. Modeling and simulation analysis were conducted on the material removal rate and grinding force during the machining process, which profoundly revealed the joint improvement mechanism of spark discharge and ultrasonic vibration on grinding quality. First, a single factor experiment was used to preliminarily determine the machining threshold. Second, the Plackett-Burman experiment was used to screen key machining parameters. Then, Box-Behnken experiment was conducted on key machining parameters, and multi-objective and multi-factor optimization was performed to obtain the optimal combination of machining parameters. Compared with normal ECDG with cylindrical grinding electrode, the overcut is reduced by 8.3 %, the edge damage is reduced by 17.5 % and the surface roughness value is reduced by 70.6 %. Finally, by using the optimized combination of machining parameters, high-quality and stable machining of typical microchannel structures was achieved. The milling depth of the microchannel is 400 µm. The machining width is 1175 ± 5 µm. The surface roughness of the measurement area is 0.375 µm. The green, high-quality and stable machining of micro glass micro components further demonstrates the potential application of this compound technology. [Display omitted] [ABSTRACT FROM AUTHOR]

Dimethylformamide (DMF), a polar solvent, is commonly used for preparing graphene/epoxy nanocomposites. While previous research has commonly predominantly highlighted the improvement in physio-mechanical properties of these nanocomposites, the effect of DMF on processing and its direct influence on the final characteristics of MXene/epoxy nanocomposites have not been investigated. This unexplored link between DMF dosage, MXene concentrations, and the final composite properties presents an exciting direction for future research. In this study, a fixed dosage of DMF was used with varying MXene concentrations to fabricate the nanocomposites. To assess the reliability of DMF dosage on the characteristics of the fabricated nanocomposites, various evaluation techniques were employed, including dispersion evaluation, mechanical tests, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), scanning electron microscopy (SEM), electromagnetic interference (EMI) shielding, and surface roughness measurements. The research outcomes revealed that as MXene concentration increased, the characteristics of the MXene/epoxy nanocomposites, improved across the board, indicating their potential for use in energy storage applications. [ABSTRACT FROM AUTHOR]

This study explores the effect of using dental brushes with or without metacrylate-based modeling resins on long-term color stability and surface topographies of resin-based composites. This study examined the effects of two variables: (1) the type of brush used (Art brush, Micro-brush, or Mylar strip) and (2) the application of a modeling resin (applied or not applied). The specimens were artificially aged through 10,000 cycles of thermocycling and subsequently immersed in coffee for 30 days. Measurements of color and surface roughness were taken at baseline and after the aging, using a non-contact profilometer for surface roughness and a spectrophotometer for color. Data were analyzed using paired t-tests and one-way ANOVA. Resin-based composites smoothed with dental brushes or micro brushes without modeling resins exhibited lower color change (ΔE) than other groups. Paired t-tests revealed significant differences in average surface roughness (Ra) and valley depth (Rv) for each surfacing technique before and after aging (p ⩽ 0.01). The root means square average of the profile heights (Rq) significantly increased in the control and micro-brush groups (p ⩽ 0.01). In conclusion, the use of brushes in resin-based composites placement does not increase the susceptibility to staining. Instead, the inclusion of resin modeling contributes to discoloration over time. [ABSTRACT FROM AUTHOR]

Due to the self-affine property of the grinding surface, the sample images with different roughness captured by the micron-scale camera exhibit certain similarities. This similarity affects the prediction accuracy of the deep learning model. In this paper, we propose an illumination method that can mitigate the impact of self-affinity using the two-scale fractal theory as a foundation. This is followed by the establishment of a machine vision detection method that integrates a neural network and correlation function. Initially, a neural network is employed to categorize and forecast the microscopic image of the workpiece surface, thereby determining its roughness category. Subsequently, the corresponding correlation function is determined in accordance with the established roughness category. Finally, the surface roughness of the workpiece was calculated based on the correlation function. The experimental results demonstrate that images obtained using this lighting method exhibit significantly enhanced accuracy in neural network classification. In comparison to traditional lighting methods, the accuracy of this method on the micrometer scale has been found to have significantly increased from approximately 50% to over 95%. Concurrently, the mean squared error (MSE) of the surface roughness calculated by the proposed method does not exceed 0.003, and the mean relative error (MRE) does not exceed 5%. The two-scale fractal geometry offers a novel approach to image processing and machine learning, with significant potential for advancement. [ABSTRACT FROM AUTHOR]

In order to enhance the formability and ridging resistance of Sn microalloyed ferritic stainless steel (FSS), an investigation was conducted on the texture and microstructure evolution, as well as formability and surface ridging of Sn microalloyed FSS at various hot rolling finishing temperatures (HRFTs). This study employed x-ray diffraction, optical microscopy, electron backscattering diffraction, tensile testing, and surface roughness measurement techniques. Hot-rolled sheets with HRFTs of 940, 870, 800, and 730 °C were subjected to annealing at 950 °C for 5 min and cold rolling at a reduction of 80%. Subsequently, they were annealed at 900 °C for 2 min. The research indicates that decreasing the HRFT has a positive impact on reducing {001} <110> grains and its texture intensity. Additionally, it leads to microstructure refinement and intensification of <111> //ND (ND: normal direction), thereby improving formability and resistance against ridging. When the HRFTs are within the range of 940–730 °C, the final sheet with an HRFT of 800 °C exhibits optimal formability and surface quality due to the formation of fine recrystallized <111> //ND grains with a sharp texture intensity. In comparison to the final sheet produced through conventional hot rolling with an HRFT of 940 °C, the average r value for the final sheet with an HRFT of 800 °C is increased by 19.4%, while the ridging height is reduced by 46.5%. This demonstrates the significance of reasonable optimization of the hot rolling process in enhancing the formability and ridging resistance of Sn microalloyed FSS. [ABSTRACT FROM AUTHOR]

This study investigates the methods for controlling porosity in thermal pipes manufactured using selective laser melting (SLM) technology. Experiments conducted include water permeability tests and surface roughness measurements, which are complemented by SEM image ML-based analysis for pore recognition. The results elucidate the impact of SLM printing parameters on water permeability. Specifically, an increase in hatch and point distances leads to a linear rise in permeability, while higher laser power diminishes permeability. Using machine learning (ML) techniques, precise pore identification on SEM images depicting surface microstructures of the samples is achieved. The average percentage of the surface area containing detected pores for microstructure samples printed with laser parameters (laser power (W) _ hatch distance (µm) _ point distance (µm)) 175_ 80_80 was found to be 5.2%, while for 225_120_120, it was 4.2%, and for 275_160_160, it was 3.8%. Pore recognition was conducted using the Haar feature-based method, and the optimal patch size was determined to be 36 pixels on monochrome images of microstructures with a magnification of 33×, which were acquired using a Leica S9 D microscope. [ABSTRACT FROM AUTHOR]

In this paper, a method for detecting surface roughness in machining processes is proposed to solve the problem of low detection accuracy caused by a small sample size in machine vision detection. The proposed method combines QR decomposition with the support vector machine (SVM) classifier to accurately assess surface roughness. First, a contact roughness detector is used to measure the surface roughness value, and a CCD camera is used to capture the processed surface image to obtain the sample. Subsequently, an improved QR decomposition method is employed to generate virtual samples and expand the sample size. Texture feature values of the image are then extracted using the grayscale level co-occurrence matrix, and the correlation between roughness and texture features is determined. Finally, SVM is employed to classify the surface roughness of machined components. Experimental results demonstrated that the accuracy of the machine vision-based surface roughness detection method increased from 80.6 to 96.5%, thus validating the feasibility of the proposed method and providing a theoretical basis for on-site detection of small-sample surface roughness. This method has potential for practical engineering applications. [ABSTRACT FROM AUTHOR]

Surface roughness measurement is an integral part of the characterization of microtextured surfaces. Multiple established software packages offer the calculation of roughness parameters according to ISO 25178. However, these packages lack a specific set of features, which we hope to address in this work. Firstly, they often lack or have limited capabilities for automated and batch analysis, making it hard to integrate into other applications. Secondly, they are often proprietary and therefore restrict access to some potential users. Lastly, they lack some capabilities when it comes to the analysis of periodic microtextured surfaces. Namely, common parameters such as the peak-to-valley depth, spatial period and homogeneity cannot be calculated automatically. This work aims to address these challenges by introducing a novel Python library, Surfalize, which intends to fill in the gaps regarding this functionality. The functionality is described and the algorithms are validated against established software packages or manual measurements. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the effects of different surface preparation techniques on the surface microstructure, the shear bond strength (SBS) between zirconia and an MDP-containing light-cured veneer adhesive system, and the adhesive failure mode. Sixty-four zirconia specimens were divided into four groups based on surface preparation methods (n = 16), including zirconia sandblasting (ZSB), zirconia vitrification or glaze-on (ZVG), zirconia surface architecture technique (ZSAT), and ZSAT-ZVG combined technique (ZSATVG) groups. Sixteen lithium disilicate specimens prepared by etching with hydrofluoric acid (HF) were used as a positive control group (LDE). Surface roughness measurement and scanning electron microscopy (SEM) evaluation were performed before and after surface preparation. All specimens were then bonded with an MDP-containing light-cured adhesive system, followed by SBS testing and adhesive failure mode analysis. The ZVG and ZSATVG groups showed the greatest differential roughness value and microscopic irregularities, while the ZSAT and LDE groups had the least surface change but the most micromechanical retentive structures for resin infiltration. SBS values were significantly different among groups (p < 0.001) with the highest SBS observed in the ZSAT group, followed by the ZSB group, LDE group, ZSATVG group, and lastly, the ZVG group. There was a statistically significant difference in failure types among the surface preparation groups (p < 0.001). The ZSAT group had the highest frequency of mixed failure, followed by the ZSB group, LDE group, and the ZSATVG and ZVG groups. Establishing direct micromechanical retention within zirconia itself yields a higher bond strength than indirect micromechanical retention within a glass ceramic layer. [ABSTRACT FROM AUTHOR]

There is limited information on the repairability of prostheses produced with digital technology. This study aims to evaluate various surface treatments on flexural bond strength of repaired dentured base resins produced by digital and conventional methods. A total of 360 samples were prepared from one heat-polymerized, one CAD/CAM milled and one 3D printed denture base materials. All of the test samples were subjected to thermocycling (5–55 °C, 5000 cycles) before and after repair with auto-polymerizing acrylic resin. The test samples were divided into five subgroups according to the surface treatment: grinding with silicon carbide (SC), sandblasting with Al2O3 (SB), Er:YAG laser (L), plasma (P) and negative control (NC) group (no treatment). In addition, the positive control (PC) group consisted of intact samples for the flexural strength test. Surface roughness measurements were performed with a profilometer. After repairing the test samples, a universal test device determined the flexural strength values. Both the surface topography and the fractured surfaces of samples were examined by SEM analysis. The elemental composition of the tested samples was analyzed by EDS. Kruskal–Wallis and Mann–Whitney U tests were performed for statistical analysis of data. SB and L surface treatments statistically significantly increased the surface roughness values of all three materials compared to NC subgroups (p < 0.001). The flexural strength values of the PC groups in all three test materials were significantly higher than those of the other groups (p < 0.001). The repair flexural strength values were statistically different between the SC–SB, L–SB, and NC–SB subgroups for the CAD/CAM groups, and the L–SC and L–NC subgroups for the 3D groups (p < 0.001). The surface treatments applied to the CAD/CAM and heat-polymerized groups did not result in a statistically significant difference in the repair flexural strength values compared to the NC groups (p > 0.05). Laser surface treatment has been the most powerful repair method for 3D printing technique. Surface treatments led to similar repair flexural strengths to untreated groups for CAD/CAM milled and heat-polymerized test samples. [ABSTRACT FROM AUTHOR]

This work presents issues related to selected errors accompanying spatial measurements of surface roughness using contact profilometry. The influence of internal heat sources, such as engines or control electronics, on the thermal expansion of the drive responsible for the measurement probe's movement in the X-axis direction was investigated. In terms of starting measurements on a thermally unstable device, the synchronization error of individual profile paths was 16.1 µm. Based on thermographic studies, the time required for full thermal stabilization of this drive was determined to be 6–12 h from when the device was turned on. It was demonstrated that thermal stabilization of the profilometer significantly reduced positioning errors of the measurement probe on the X-axis. Thermal stabilization time should be determined individually for a specific device variant. This research also determined how changes in the center of gravity caused by the measurement probe's movement affected the overall rigidity of the profilometer structure and the leveling of the tested surface. Laser interferometry was used for this purpose. The determined vulnerability of the profilometer structure was 0.8 µm for a measurement section of 25 mm. Understanding the described relationships will reduce errors associated with conducting measurements and preparing equipment for tests. Additionally, it will enable the correct evaluation of surface geometry. [ABSTRACT FROM AUTHOR]

The mechanical properties of textile materials play a crucial role in determining their comfort, functionality, performance, safety, and aesthetics. Understanding and optimizing these properties is essential to meet consumer demands. Key aspects of mechanical properties, such as surface roughness, abrasion resistance, and compression, have a significant impact on the touch and durability of the material, as demonstrated by various research studies. This study focuses on analyzing the mechanical properties of materials produced of different polymer yarns and their changes under combined aging factors. The findings emphasize the significance of textile abrasion resistance and surface roughness measurement, particularly for aged materials. Although the use of recycled polyester yarn is sustainable and offers advantages such as higher tensile strength, the results have shown that the use of conventional polyester yarn is more advantageous overall as it has higher abrasion resistance, a smoother surface texture, and better elasticity retention after aging. The insights presented are vital for designing high-performance sportswear, which is crucial in today's competitive environment. [ABSTRACT FROM AUTHOR]

Control of surface texture in strip steel is essential to meet customer requirements during galvanizing and temper rolling processes. Traditional methods rely on post-production stylus measurements, while on-line techniques offer non-contact and real-time measurements of the entire strip. However, ensuring accurate measurement is imperative for their effective utilization in the manufacturing pipeline. Moreover, accurate on-line measurements enable real-time adjustments of manufacturing processing parameters during production, ensuring consistent quality and the possibility of closed-loop control of the temper mill. In this study, we formulate the manufacturing issue into a Time Series Extrinsic Regression problem and a Machine Vission problem and leverage state-of-the-art machine learning models to enhance the transformation of on-line measurements into a significantly more accurate Ra surface roughness metric. By comparing a selection of data-driven approaches, including both deep learning such as convolutional, recurrent, and transformer networks and non-deep learning methods such as Rocket and XGBoost, to the close-form transformation, we evaluate their potential using Root Mean Squared Error (RMSE) and correlation for improving surface texture control in temper strip steel manufacturing. [ABSTRACT FROM AUTHOR]

In recent years, the number of studies focusing on the additive manufacturing has increased seriously to elucidate the critical points such as physical, chemical, and mechanical properties. Contrary to common trends and for the first time in the literature, this experimental endeavor aims to comprehend the combined impact of reinforcement type and heat treatment on the wear features of additively manufactured polyamide 6 (PA6) composites. As reinforcement materials, glass, and carbon fibers were utilized and all samples were created through the fused filament fabrication. Half of the samples were subjected to annealing treatment after the main production, and characterization works were performed using a fused emission scanning electron microscope, differential scanning calorimetry, and dynamic mechanic analysis. From the outcomes, it is seen that heat treatment has a positive effect on the hardness, and wear resistance of the composites. Besides, glass fiber‐reinforced samples display lower friction coefficient and lower volume loss results than other samples. For all samples, secondary annealing causes a positive impact on wear endurance in most cases. On the other side, the wear mechanism of the tested samples changes with the test force level and reinforcement type. At lower test forces, abrasive wear‐induced debris parts are detected on the deformed surfaces of PA6 and carbon‐added samples, but this case is opposite for the highest force of 40 N. Highlights: Additive manufacturing was underlined as a promising way to create polymer composites with high dimensional accuracy.The combined effect of secondary annealing and reinforcement type on the wear resistance of 3D‐printed PA6 composites was examined for the first time in the literature.Carbon and glass fibers were compared to explore their effect on friction coefficient and wear behavior of polymer composite samples produced via FFF technology.Hardness and surface roughness measurements were used to comprehend the dry sliding wear results.Depending on the increasing test force levels and reinforcement type, deformation, and abrasion mechanisms were analyzed. [ABSTRACT FROM AUTHOR]

WC-based coatings are found efficient in providing excellent tribological properties to the structures and components subjected to harsh wear and erosion environments. High-velocity oxy-fuel (HVOF) spraying is known as one of the best techniques to deposit such coatings. However, there still exists scope for further microstructural refinement and improvement in the mechanical properties of the as-sprayed HVOF coatings. Laser remelting has proven to be an appropriate process to achieve such improvement in as-sprayed WC-based coatings. In the current investigation, laser remelting at two different power levels was done on the HVOF-sprayed WC-NiCr coating on stainless steel specimens. The post-processed coatings were analyzed using a scanning electron microscope, x-ray diffraction, x-ray photoelectron spectroscopy, and ImageJ software to study the microstructural changes. Microhardness and surface roughness measurements were also performed to study the mechanical changes. The laser remelting resulted in a smoother coating surface, having lower porosity, lower surface roughness, and higher microhardness as compared to the as-sprayed HVOF coatings. The highest reduction in the porosity was found to be around 72%, whereas, an increment of around 21% in the microhardness was witnessed. These two parameters are crucial for the tribological performance of the coatings. The current study also gives direction to further study these remelted coatings in tribological conditions. [ABSTRACT FROM AUTHOR]

SiC p /Al composites are suitable for satisfying the lightweight requirements of terahertz wave-reflecting components. In this paper, diamond-turned surfaces of 60 % high volume fraction SiC p /Al composites are characterized in terms of surface roughness and terahertz reflectivity. The finished surfaces of SiC p /Al composites are obtained using single-point diamond turning with different process parameters, and surface roughness measurements as well as SEM and EDS analyses are conducted on the surfaces. The theoretical relationship between surface roughness and terahertz reflectivity is analyzed, and terahertz reflectivity testing experiments are conducted and validated. The surface roughness evaluation system and prediction model for SiC p /Al composites with a volume fraction of 60 % are established, and the errors between the experimental results and the predicted results are verified within 10 % by random experiments. Finally, the turning process parameters are optimized using a genetic algorithm, and the optimized turning process parameters are obtained as the spindle speed of 750 r/min, the feeding speed of 1 mm/min and the turning depth of 6 μm. • Spindle speed and feeding speed have a significant impact on surface roughness. • The relationship between roughness and reflectivity was analyzed and experimented. • Roughness prediction model is established, and the model error is verified. • A genetic algorithm is adopted to optimize the turning process parameters. [ABSTRACT FROM AUTHOR]

Purpose: The use of additive manufacturing in many branches of industry is increasing significantly because of its many advantages, such as being able to produce complex parts that cannot be produced by classical methods, using fewer materials, easing the supply chain with on-site production, being able to produce with all kinds of materials and producing lighter parts. The binder jetting technique, one of the additive manufacturing methods researched within the scope of this work, is predicted to be the additive manufacturing method that will grow the most in the next decade, according to many economic reports. Although additive manufacturing methods have many advantages, they can be slower than classical manufacturing methods regarding production speed. For this reason, this study aims to increase the manufacturing speed in the binder jetting method. Design/methodology/approach: Adaptive slicing and variable binder amount algorithm (VBAA) were used to increase manufacturing speed in binder jetting. Taguchi method was used to optimize the layer thickness and saturation ratio in VBAA. According to the Taguchi experimental design, 27 samples were produced in nine different conditions, three replicates each. The width of the samples in their raw form was measured. Afterward, the samples were sintered at 1,500 °C for 2 h. After sintering, surface roughness and density tests were performed. Therefore, the methods used have been proven to be successful. In addition, measurement possibilities with image processing were investigated to make surface roughness measurements more accessible and more economical. Findings: As a result of the tests, the optimum printing condition was decided to be 180–250 µm for layer thickness and 50% for saturation. A separate test sample was then designed to implement adaptive slicing. This test sample was produced in three pieces: adaptive (180–250 µm), thin layer (180 µm) and thick layer (250 µm) with the determined parameters. The roughness values of the adaptive sliced sample and the thin layer sample were similar and better than the thick layer sample. A similar result was obtained using 12.31% fewer layers in the adaptive sample than in the thin layer sample. Originality/value: The use of adaptive slicing in binder jetting has become more efficient. In this way, it will increase the use of adaptive slicing in binder jetting. In addition, a cheap and straightforward image processing method has been developed to calculate the surface roughness of the parts. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the effect of air abrasion and polishing procedures on roughness and color stability of ceramic and composite materials after artificial accelerated aging. Methods: In this study, six restorative materials were tested: feldspathic ceramic (CEREC Blocks), glass ceramic UPS e.max CAD), resin-based hybrid ceramic (Cerasmart), microhybrid composite (Charisma Classic), nanohybrid composite (Charisma Diamond) and nanoceramic composite (CeramXOne). Forty square-shaped composite specimens were fabricated from each composite and CAD-CAM ceramic material. Initial surface roughness measurements were performed using a profilometer and color measurements of each specimen with a spectrophotometer. Ten control specimens for each group did not receive air abrasion. The other specimens were treated by an air abrasion device and then were randomly divided into three subgroups of 10 specimens (n= 10). After air abrasion, 10 specimens of each group did not receive polishing (Air abrasion group) and others were repolished with Sof-Lex kit (Sof-Lex group) or a rubber kit (Rubber group). Surface roughness and color measurements were repeated before and after 300 hours of artificial accelerated aging (AAA). The univariate test and then three-way ANOVA and two-way ANOVA were performed for comparison of groups (a= 0.05). Results: The univariate statistical analysis revealed that the restorative materials were differently affected after air abrasion, polishing methods and AAA (P< 0.001). Three-way ANOVA showed that the surface roughness of the restorative materials increased after air abrasion and AAA (P< 0.001). Two-way ANOVA showed statistically significant differences between color changes of ceramic (CEREC and IPS e. max CAD) and composite based restorative materials (P < 0.001). [ABSTRACT FROM AUTHOR]

In cutting processing, the mechanical properties of the material are very important, and the optimal cutting conditions, depending on strength, hardness, and elongation, affect the quality of the machined surface. Therefore, this study was conducted to obtain optimized cutting conditions such as the tool depth of the cut, cutting speed, and feed rate, considering the mechanical properties of the material. AISI 1045 cold-drawn (CD) bars showed an average tensile strength of 695.31 MPa in the tensile test and an average value of 308.6 HV in the Vickers hardness measurement. AISI 1020 CD bars showed a 22.66% lower average tensile strength of 537.74 MPa and an average of 198.77 HV in the hardness measurement. Therefore, AISI 1020 showed a 32.62% higher elongation than AISI 1045. In the measurement results for surface roughness after cutting, different results were observed depending on the strength and elongation at a feed rate of 0.05 mm/rev. AISI 1045 exhibited the highest machining quality, with a surface roughness of approximately 0.374 µm at a cutting speed of 150 m/min, and the cutting depth was 0.4 mm at a feed rate of 0.05 mm/rev. Alternatively, AISI 1020, which had relatively low strength and hardness with high elongation, exhibited the highest machining quality with a roughness of 0.383 µm with similar cutting parameters as AISI 1045. [ABSTRACT FROM AUTHOR]

We investigated the paraglacial evolution and permafrost degradation of Val Viola (Upper Valtellina, Central Italian Alps) through a geomorphologic survey, cosmogenic dating, Schmidt's Hammer, and surface roughness measurements. Our results reveal that the previously mapped Val Viola rock avalanche is probably derived by three different events that occurred 7.7 ± 0.2 ka (Orthogneiss_ 1), 7.0 ± 0.2 ka (Paragneiss), and 5.0 ± 0.3 ka (Orthogneiss_2). Because the main valley bottom has been ice free since at least 12.6 ka, it is unlikely that the triggering factor of these events was the debutressing stress caused by the melting of local valley glaciers. Therefore, permafrost that formed in this area down to 2525 m a.s.l. at 9.3–8 ka and degraded successively between 7.8 and 6.5 ka was likely the main triggering factor of the first two rock avalanche events, as well as for the third event that happened during the warm and wet period of the Holocene Thermal Maximum around 5 ka. [ABSTRACT FROM AUTHOR]

The surface‐roughness machine vision measurement method requires training numerous samples with uniform roughness values to construct a prediction model. Insufficient actual sample size will make the model lack generalization ability. So, a grinding surface‐roughness measurement method combined with simulation data and transfer learning is proposed. First, through surface simulation, inverse fitting, and three‐dimensional (3D) modeling, more realistic simulation samples are obtained, real samples are prepared, and a simulation imaging system and an actual imaging experiment to acquire surface images are designed. Second, the data distribution difference between the simulation domain and the actual domain through transfer component analysis and the use of the adjusted simulation‐domain data and its label to train a support vector regression model is adjusted. Finally, the model predicts the surface roughness of the uncalibrated actual‐domain sample. For shared features of transferable simulation images and actual images, using the high sensitivity of color information, image features are enhanced and a proportion of pure color region index is designed, strongly correlated within the domain but less differentiated between domains. The results show that the transfer learning prediction accuracy based on this index exceeds 90%, verifying the feasibility of the proposed method and providing a new improvement strategy for sample expansion in visual roughness measurement. [ABSTRACT FROM AUTHOR]

Surface structuring by ultrafast lasers is a promising technique to modify surface-related properties of materials to tailor them for specific applications. In the present study, we experimentally investigated the laser structuring of commercially pure titanium (CP Ti) using ultrafast pulses to understand the role of the laser input parameters on the development of surface morphology, optical properties, surface chemistry, and wettability behaviour. The processed surfaces were characterized by a scanning electron microscope, energy-dispersive X-ray spectroscopy (EDX), Raman microscope, optical microscope, and sessile drop method. Laser-induced periodic surface structures decorated with nanodroplets were noted to be formed on the surface of the laser-structured CP Ti. The surface roughness measurements showed that the laser-structured surfaces had nanoscale roughness values. The EDX and the Raman analyses show that laser-structured surfaces of CP Ti have a thin oxide film. Different colours on different surfaces processed by different laser parameters were observed. The wettability assessment shows that CP Ti can transition from hydrophilic–hydrophobic and vice versa depending on the environmental conditions. This study shows that laser structuring can be utilized to modify CP Ti surfaces to obtain desirable surface properties that can find potential applications in different fields. [ABSTRACT FROM AUTHOR]

Manufacturing processes in industry applications are often controlled by the evaluation of surface topography. Topography, in its overall performance, includes form, waviness, and roughness. Methods of measurement of surface roughness can be roughly divided into tactile and contactless techniques. The latter ones are much faster but sensitive to external disturbances from the environment. One type of external source error, while the measurement of surface topography occurs, is a high-frequency noise. This noise originates from the vibration of the measuring system. In this study, the methods for reducing high-frequency errors from the results of contactless roughness measurements of turned surfaces were supported by machine learning methods. This research delves into optimizing filtration methods for surface topography measurements through the application of machine learning models, focusing on enhancing the accuracy of surface roughness assessments. By examining turned surfaces under specific machining conditions and employing a variety of digital filters, the study identifies the Gaussian regression filter and spline filter as the most effective methods at a 22.5 µm cut-off. Utilizing neural networks, support vector machines, and decision trees, the research demonstrates the superior performance of SVMs, achieving remarkable accuracy and sensitivity in predicting optimal filtration methods. [ABSTRACT FROM AUTHOR]

Over the past three decades, 3D printing technologies have undergone significant advancements, revolutionizing various industries, such as automotive. Additive manufacturing has played a crucial role in reducing product development time and enabling the direct printing of functional parts. One of the key advantages of additive manufacturing is its ability to provide greater design freedom compared to traditional manufacturing methods. This means that complex geometries and varying material properties can be easily printed. In this research paper, the author focused on investigating the impact of layer thickness and part orientation on the surface roughness and accuracy of printed parts. The main objective was to identify the optimal combination of layer thickness and part orientation that would yield the best results in terms of surface roughness and accuracy, considering printing time as a variable. The results from printing time, accuracy and surface roughness measurements showed that the vertical orientation is the superior for cylindrical orientation. [ABSTRACT FROM AUTHOR]

The surface roughness of the workpiece is one of the important indicators to measure the quality of the workpiece. Vision-based detection methods are mainly based on human-designed image feature indicators for detection, while the self-extraction method of milling surface features based on deep learning has problems such as poor perception of details, and will be affected by surface rust. In order to solve these problems, this paper proposes a visual inspection method for surface roughness of milling rusted workpieces combined with local equilibrium histogram and CBB-yolo network. Experimental results show that local equilibrium histogram can enhance the milling texture and improve the accuracy of model detection when different degrees of rust appear on the surface of the milled workpiece. The detection accuracy of the model can reach 97.9%, and the Map can reach 99.3. The inference speed can reach 29.04 frames per second. And the inspection of workpieces without rust, this method also has high detection accuracy, can provide automatic visual online measurement of milling surface roughness Theoretical basis. [ABSTRACT FROM AUTHOR]

The hybridisation of injection moulding (IM) and additive manufacturing (AM) offers the opportunity to combine the high productivity of IM and the high flexibility of AM into a single process. IM parts can be overprinted through fused filament fabrication (FFF) to allow for the customisation of parts or to add new functionalities. However, the right material pair must be chosen, and processing parameters must be optimised to achieve suitable adhesion between the components. The present study dealt with the investigation of the influence of the interfacial area, substrate surface roughness and overprinting processing parameters on the adhesion between the polyamide 6 (PA6) substrate and thermoplastic polyurethane (TPU) rib overprinted via FFF. PA6 substrates were produced through the IM of plates into a mould with different textures to obtain substrates with three different surface roughnesses. The ribs with varied interfacial areas were overprinted onto produced substrates using a desktop FFF 3D printer. To study the effect of overprinting processing parameters, the ribs were overprinted under varying printing and substrate temperatures and printing speeds according to the Box–Behnken design of experiments (DoE). The chemical composition and thermal properties of used materials were determined via attenuated total reflectance–Fourier transform infrared spectroscopy (ATR-FTIR), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA). The surface properties of prepared substrates were studied via digital optical microscopy (OM), through surface roughness measurements using a confocal microscope, through contact angle (CA) measurements and through the determination of free surface energy (SFE). The adhesion between the components was determined by evaluating the tear-off strength using a universal testing machine (UTM). With an increasing interfacial area, the tear-off strength decreased, while substrate surface roughness had no statistically significant effect. Overprinting parameters influenced the tear-off strength in the order of printing speed > printing temperature > substrate temperature. High values of tear-off strength were found for the lowest printing speed, while there were no important differences found between the middle and upper values. With increasing printing and substrate temperatures, the tear-off strength increased linearly. The highest value of tear-off strength (0.84 MPa) was observed at a printing temperature, substrate temperature and printing speed of 250 °C, 80 °C and 2 mm/s, respectively. [ABSTRACT FROM AUTHOR]

The strength of the bond between concretes is attributed to surface roughness. Therefore, it is necessary to quantify the roughness of concrete surfaces. In the traditional method, concrete surface roughness is measured using the sand filling method, which is contacting, inefficient, and destructive. Accordingly, this paper proposes an edge detection-based method for measuring concrete surface roughness. By combining pixel and sub-pixel edge detection, aggregate edges are extracted and a relationship curve between edge frequency and concrete surface roughness is fitted using the least squares method to achieve a non-contact, stable and non-destructive measurement. Experimental outcomes indicate that the accuracy of the method for measuring concrete surface roughness can reach 94.7%. Additionally, a single-input, single-output neural network model based on calculated edge frequencies is constructed with a measurement accuracy of 95.4% for concrete surface roughness detection. [ABSTRACT FROM AUTHOR]

Accurate measurement of the stress in steel structures is crucial for structural health monitoring. To achieve this goal, a novel technique, the laser ultrasonic technique, was used in absolute stress measurement in this study. The feasibility of this technique has been verified through theoretical analysis and finite element (FE) analysis. A stress measurement experiment in steel specimens was conducted and the relationship between ultrasonic relative wave velocity and stress was explored. The results revealed that there is a similar linear correlation between the ultrasonic relative wave velocity and absolute stress. The stress can be obtained based on ultrasonic relative wave velocity. According to the stress measurement results, it was found that the absolute error between the measured stress and theoretical stress was largest when the stress level was low, and that the measured error of stress gradually decreased with increases in the applied stress. The relative error between the measured stress and the theoretical stress was within 10% when the stress was higher than 100 MPa. This further verifies the reliability of the laser ultrasonic technique under high-stress conditions. Additionally, the impact of temperature and surface roughness on stress measurement was analyzed. The stress error in stress measurement increased similarly linearly with the increase in temperature and increased non-linearly with the increase in roughness. The corresponding compensation methods were proposed to effectively improve the accuracy of measurement. [ABSTRACT FROM AUTHOR]

With the development of optics, light section method has become a feasible measurement for surface roughness, while the short sampling length is negative to the accuracy. To overcome this defect, this article proposed a measurement under ResNet-based roughness classification and light section with seam-driven image stitching (RCLS). First, the images were classified with ResNet neural network, then stitched and enhanced by scale invariant feature transform (SIFT) and optimized random sample consensus (RANSAC) algorithm for the best visual effect. After this, images were processed by Nobuyuki Otsu method and Freeman chain code tracking algorithm. Least square was also adopted to calculate the optical band edge curve and contour midline. Finally, the roughness contour arithmetic mean deviation model was established to evaluate the surface roughness. The experiments were conducted with vertical milled, planned, and turned samples that self-machined. The light section method had a reduction of 2.75% on the mean relative error compared to stylus and RCLS could further reduce the mean relative error by 1.42%, especially in planned sample. The RCLS could achieve a more accurate surface roughness by overcoming the disadvantages of small sample length and low precision of the light section method, and is more convenient than stylus.

A widespread problem of manufacturing processes is represented by the occurrence of tool wear that can lead to both poor surface finish and poor mechanical properties in the workpiece. This issue affects also additive manufacturing technologies such as the material extrusion technique. In this process, the wear mechanisms of the extrusion nozzle can be severe, in particular when materials with a high abrasive capacity, such as carbon fiber-reinforced polymers, are 3D printed. Despite the significance of this problem, scientific literature lacks systematic evaluations of nozzle wear and its correlation with parts mechanical properties. In this framework, the present paper aims at investigating the effect of the nozzle wear evolution on the mechanical properties of additively manufactured parts in short carbon fiber-reinforced polyamide. To this purpose, 3D printing processes were performed. The time dependence of the nozzle wear was analyzed by interrupting the additive manufacturing process at fixed time intervals. To analyze the effect of nozzle wear on the mechanical performances of printed parts, tensile specimens were 3D printed and tested at room temperature. A reduction in mechanical performances of the printed samples and a worsening in the surface quality were observed with increasing the nozzle wear. Optical microscopy investigation and X-ray computed tomography were used to monitor the external and internal nozzle wear evolution. The surface roughness measurements were performed to evaluate the surface quality of the 3D printed parts. Furthermore, the scanning electron microscopy was used to observe the three-dimensional topography of the longitudinal sections of filament in Carbon PA, at different printing time values, and fractured surfaces of tensile samples. This study can help to better understand nozzle wear and to predict tool service life for industrial applications. In addition, it can prompt future studies focused on the reduction of tool wear. [ABSTRACT FROM AUTHOR]

Six different composites were used in the study. From each material, 40 cylinder-shaped samples were made. All samples were polymerized and polished using three different methods. To evaluate surface roughness a confocal laser microscope was used, and microhardness was determined using a universal Vickers hardness tester. The data were analysed using the one-way ANOVA test at a significance level of 0.05 for both tests. The smoothest surfaces in all groups of composites were obtained for control samples. Also in all groups of composite samples no statistically significant differences were found between the Sof-Lex and Enhance+PoGo. The measurement of surface roughness obtained for the Kenda system showed significantly lower values than for the other two methods. The surfaces of the control samples showed statistically significantly lower microhardness values compared to all polishing systems for all six tested resin composites, additionally no statistically significant differences were found between all finishing and polishing methods. Regardless of the finishing and polishing method used, the lowest microhardness values among microhybrid materials were found for Charisma Flow, while among nanohybrid materials the lowest values were obtained for Herculite HRV Ultra. Finishing and polishing increases the microhardness of microhybrid and nanohybrid composite resin. The use of Kenda three step polishing system resulted in smoother surface for all tested composite materials compared to the Sof-Lex and Enhance+PoGo systems, while the finishing and polishing method had little effect on the microhardness of the surface. [ABSTRACT FROM AUTHOR]