Surface Roughness Values Research Articles

Level-Set Method Based Predictive Modeling to Track the Evolution of Surface During Pulsed Laser Surface Melting

Abstract The objective of this study is to investigate the evolution of surface geometry during pulsed laser surface melting (pLSM) via level-set method-based interface tracking numerical framework. Existing models to track surface geometry are inaccurate and computationally expensive. Therefore, they have limited use in gaining understanding of the surface evolution during pLSM. A numerical model, integrating the level-set approach, fluid flow, and heat transfer dynamics, is detailed in this paper. The multi-phase numerical model achieves accurate tracking of interface for a single pulse by implementing the volumetric laser heat source on the moving interface by modifying Beer–Lambert's law. The accuracy of the single pulse model is confirmed by comparing its peak-to-valley height (PVH) to the experimental data. The deviation in PVH is limited to about 15%, with a maximum root mean square error of ∼0.24 µm, highlighting the model's reliability. Additionally, the evolved surface of a single pulse from the model is replicated over an area with dedicated overlaps to generate the predicted textured surface with reasonable accuracy. Some inaccuracies in the predicted surface roughness values were observed because the textures were generated based on a single pulse geometry computed on an initially flat surface. Nonetheless, the results highlight a significant development in numerical frameworks for pLSM and can be used as a tool to gain deeper insights into the process and for process optimization.

Effect of different polishing systems on surface roughness and gloss values of single-shade resin composites.

The aim of this study was to evaluate variations in the surface roughness and gloss of different single-shade resin composites after polishing with a range of systems. In total, 120 specimens were prepared from three different types of single-shade resin composites (supra-nanospherical-Omnichroma, nanohybrid-Charisma Diamond One, and microhybrid- Essentia Universal). The specimens were placed in distilled water and stored at 37°C for 24h. Each resin composite (n = 40) was divided into four groups (n = 10) according to the finishing/polishing (F/P) system: Mylar strip (control), Sof-Lex (multi-step), Twist Dia (two-step), and OneGloss (one-step). Surface roughness and gloss were measured. Surface characteristics were evaluated by atomic force microscopy (AFM) and a scanning electron microscope (SEM). A two-way analysis of variance (ANOVA) and Tukey's honestly significant difference test were used for statistical analysis (p < 0.05). Among all the composites, both the highest surface roughness and lowest gloss values were obtained in the groups treated with the OneGloss polishing system (p < 0.05). Compared with all the composites, Omnichroma had the lowest surface roughness and highest gloss values (except Twist Dia) both unpolished and after polishing with all the F/P systems (p < 0.05). All composites treated with the Twist Dia F/P system had similar gloss values. The results of the AFM and SEM analyses were consistent with the surface roughness measurements. The gloss values of both the microhybrid and nanohybrid composites after F/P using the two-step system was superior to that of the traditional multistep system. The surface of the supra-nanofilled resin-based composite was smoother than that of both the microhybrid and nanohybrid composites.

STYLUS BASED EVALUATION OF THE SURFACE ROUGHNESS

This paper deals with problems in determining surface roughness values. The process of determining surface roughness values is a relatively difficult task. In this process, it is necessary to set the measurement conditions, which have a huge impact on the measurement uncertainty, and neglecting this process can cause a complete degradation of the measurement and evaluation result. Certain changes in this process are defined by new standards that have been approved to guide this process. The development of the methodology is very necessary in this area in order to obtain reliable data on surface roughness values.

The Machinability of Different Albromet W130 Plates Thicknesses by WEDM to the Required Surface Roughness Value

Wire Electrical Discharge Machining (WEDM) technology represents an unconventional but vital manufacturing technology in many different industrial branches. The automotive industry and its many significant requirements bring the need to manufacture inserts and mould segments for plastic injections from Albromet W130 material, with a required roughness, Ra, from 4.5 to 5 µm so that subsequent profile etching can be eliminated. A planned experiment of 60 rounds was carried out to discover the optimal machining parameters, namely, the pulse-off time, gap voltage, discharge current, pulse-on time, and wire speed in order for the thickness of 10 to 100 mm (after 10 mm) to demonstrate the required roughness. The goal was to evaluate the surface roughness, maximise the cutting speed, and manufacture it without surface or subsurface defects. The evaluation of the planned experiment led to the establishment of optimised WEDM machining parameters with which thicknesses of 10–100 mm will always be produced with the required roughness, Ra, from 4.5 to 5 µm and with the highest possible cutting speed. It was also proven that the machining does not lead to surface or subsurface defects, and thus, the service life of the manufactured parts will not be affected.

The effect of various denture cleansers on the physical and mechanical properties of CAD/CAM and heat-polymerized denture base materials: an in vitro study.

To investigate the effects of denture cleansers on the various properties of CAD/CAM and heat-polymerized polymethyl methacrylate (PMMA). Two different brands of heat-polymerized and two of milled PMMA were fabricated (n = 50), in total 200. Each group was randomly divided into five subgroups (n = 10): control groups (D1) kept in distilled water, cleaning tablets (D2, D3), neutral (D4) and acidic electrolyzed acid water (EAW) (D5). Surface roughness, hardness and flexural strength values were evaluated. Data were statistically analyzed with two-way ANOVA and Tukey post hoc test for comparison (p<0.05). The milled group showed significantly lower surface roughness, greater surface hardness, and higher flexural strength values than heat polymerized denture bases (p<0.05). The denture cleansers had no significant effect on the surface roughness values of the milled specimens (p>0.05), whereas the specimens in the heat-polymerized groups and treated with D5 showed greater surface roughness values compared with the other cleaning agents (p > 0.05). The denture cleansers had no significant effect on surface hardness and flexural strength of heat polymerize groups (p > 0.05). However, D2, D3 and D5 cleaning agent decreased the hardness values of the milled group (p<0.05) and D5 cleaning agent decreased the flexural strength of the milled group (p<0.05). It was observed that the applied denture cleansers affected the surface roughness, surface hardness, and flexural strength values of both denture bases but within a clinically acceptable value. CAD/CAM denture bases showed significantly higher physical and mechanical properties than to heat-polymerized base materials. Although the applied neutral EAW cleaners give desired results for denture bases, clinical studies are needed for biological compatibility.

Analysis of FS and Surface Roughness in Heat-Polymerized Poly Methyl Methacrylate Acrylic Resin Reinforced with Different Concentrations of Glass Fibers and Polypropylene Fibers: A Laboratory Study Using EDX and SEM

This study aimed to evaluate the flexural strength (FS) and surface roughness (Ra) of heat-polymerized poly methyl methacrylate (PMMA) acrylic resin reinforced with glass fibers (GF) and polypropylene fibers (PPF) in different concentrations. One hundred heat-cured PMMA resin samples were prepared and randomly allocated into five groups based on fiber reinforcement (n = 20). Group 1 had no fiber reinforcement, Group 2 had 0.5% silanized GF reinforcement, Group 3 had 1% silanized GF reinforcement, Group 4 had 0.5% silanized PPF reinforcement, and Group 5 had 1% silanized PPF reinforcement. Fatigue load was applied through artificial aging. FS testing of fifty samples was performed using a universal testing machine, and Ra was analyzed using an optical interferometric profilometer. Specimens were selected for SEM and EDX analysis. To find the differences among the studied groups, one-way analysis of variance and post hoc Tukey’s test were utilized. The results showed that Group 5 (1% PPF reinforcement) presented the highest fracture resistance (90.1±9.8 MPa), while the minimum FS scores were observed in Group 1 (no reinforcement) (59.2±7.1 MPa). Group 3 (1% GF reinforcement) exhibited the highest values of surface roughness (1.99±0.1992), whereas the lowest roughness scores were observed in Group 1. The study concluded that incorporating 0.5% PPF into the resin denture is a viable option for reinforcing the prosthesis without increasing surface roughness.

Surface characteristics, cytotoxicity, and microbial adhesion of 3D-printed hybrid resin-ceramic materials for definitive restoration

ObjectiveThis study investigated the surface properties, cytotoxicity, and microbial adhesion of 3D-printed specimens made from hybrid resin-ceramic materials intended for use in definitive crowns. MethodsDisc-shaped specimens were 3D-printed using six different hybrid resin-ceramic materials recommended for definitive restorations: Crowntec (CT), VarseoSmile Crown Plus (VS), Tera Harz TC-80DP Graphy (TH), C&B Permanent ODS (CB), Formlabs Permanent Crown (FP), and HeyGears (HG). Surface topography, surface roughness, and water contact angle values were measured for each material (n = 6). Cytotoxicity was assessed using direct contact and extract tests on human gingival fibroblasts (n = 4). Additionally, the adhesion of mixed oral bacteria to the surfaces of the specimens was evaluated by counting colony-forming units (CFUs) after a 2-hour incubation period (n=6). ResultsThe TH group exhibited significantly lower surface roughness (Ra: 0.28 ± 0.13 μm) compared to the other materials (CT: 1.87 ± 0.34 μm; VS: 1.13 ± 0.09 μm; CB: 2.91 ± 0.27 μm; FP: 2.50 ± 0.08 μm; HG: 1.50 ± 0.55 μm). The VS group had the highest water contact angle (129.5 ± 1.1°), indicating greater hydrophobicity, in contrast to the other groups (CT: 72.6 ± 2.1°; TH: 75.0 ± 0.3°; CB: 69.1 ± 0.2°; FP: 93.0 ± 1.6°; HG: 77.7 ± 0.3°). Cytotoxicity testing showed no harmful effects, as relative cell viability exceeded 70%, and lactate dehydrogenase (LDH) release remained below 30% for all materials. The TH specimens also demonstrated the lowest bacterial adhesion. ConclusionsThe surface characteristics of the tested resin-ceramic materials varied significantly, with TH showing the smoothest surface and the least bacterial adhesion. All materials were found to be non-toxic. Therefore, TH material has the potential to provide definitive restorations with less microbial adhesion. Clinical SignificanceThe type of resin-ceramic material significantly affects the surface properties of 3D-printed specimens. These findings are crucial for selecting the appropriate resin-ceramic material for definitive restorations.

A process parameters decision approach considering spindle vibration in helical surface milling for minimising energy consumption and surface roughness value

A process parameters decision approach considering spindle vibration in helical surface milling for minimising energy consumption and surface roughness value

The effect of whitening toothpastes on the surface properties and color stability of different ceramic materials

ObjectivesThis study aimed to evaluate the effect of whitening toothpastes on the surface roughness and colour change of CAD-CAM materials.Materials and methodsA total of 96 samples (2 × 10 × 12 mm3) were prepared from Cerasmart (CS) and Celtra Duo blocks. Celtra Duo samples were divided into two groups. One group was fired with glaze paste (CDG) and the other was not treated (CD). All groups were then divided into 4 subgroups (n = 8). The groups were brushed with conventional (Colgate™ Max Fresh), silica (Opalescence™), charcoal (Curaprox™ Black in White) and blue covarine (Signal™ White Now) toothpastes for 30,000 brushing cycles. The initial and final surface roughness values were measured with contact profilometer and a dental spectrophotometer used for obtaining colour values. One sample from each brushed group was analyzed using a scanning electron microscope. Data was analyzed with Kruskal-Wallis and Mann-Whitney tests (p = 0.05).ResultsThe surface roughness of CS samples brushed with Opalescence™ and Curaprox™ was significantly higher than CD and CDG. Surface roughness change values of CS samples brushed with Curaprox™ were significantly higher than the CD and CDG. Curaprox™ brushed samples showed significant difference in colour change values for all materials.ConclusionsBrushing increases the surface roughness of CAD-CAM ceramic materials. The roughness of resin-based materials is higher than zirconia-reinforced lithium silicates. Silica-contained toothpastes may cause discoloration of nanoceramic and zirconia-reinforced glass ceramic restorations.Clinical relevanceIt should be clinically considered that whitening toothpastes may cause roughness in ceramic materials and change the desired color.

A comparative study of polishing systems on optical properties and surface roughness of additively manufactured and conventional resin based composites

This study aimed to compare polishing systems on color stability, surface roughness, and gloss of additively manufactured permanent and conventional resin composites. Totally 250 disc specimens (6 mm*2 mm) were prepared from resin-based materials [G-ænial Posterior (GP), Clearfil Majesty Esthetic (CME), SonicFill-2 (SF), Tescera (Tes), and Crowntec (CT)]. Following baseline color (ΔE00), gloss (GU), and surface roughness (Ra) measurements, the specimens were randomly divided into 5 groups (n = 10/group) according to polishing systems: Control (mylar strips); OneGloss; OneGloss + Platina Hi-Gloss; OptiDisc; and OptiDisc + Platina Hi-Gloss. Specimens were immersed in coffee for 144 h following polishing. ΔE00, GU, and Ra measurements were repeated. Atomic force microscopy images were taken in all groups. Spearman’s rho correlation coefficient, Robust ANOVA, and Bonferroni correction were used for statistical analysis. Significance level was taken as p < 0.050. Significant differences in ΔE00 values were found among resin-based materials, polishing systems, and their interactions (p < 0.001,p < 0.01, and p = 0.001). Regardless of polishing system, the lowest ΔE00 values were observed in CT, while lowest gloss (GU) values were found in Tes. The lowest surface roughness (Ra) values were detected at OptiDisc group (p < 0.001). A single type of polishing system may not be sufficient to achieve optimal results in resin-based materials.

A comparative experimental study on abrasive flow machining vs flow peening GOV processes on Inconel 718

Inconel 718, a nickel-based super alloy, has a broad applications area from aerospace, medical and defence to traditional industries because of its high durability, corrosion resistance and elevated temperature performance. Unconventional surface treatment methods of abrasive flow machining (AFM) and shot peening (SP) are applied to improve the mechanical performance of Inconel 718. In this work, a new surface treatment process known as flow peening (GOV) already developed by combining the advantages of abrasive flow machining (AFM) and shot peening methods such as surface finishing and residual compressive stress generation respectively was applied experimentally for Inconel 718. The effects of process parameters for GOV and AFM processes on the surface quality of the specimens were experimentally investigated. White layer decrease, surface roughness decrease and material removal amount were discussed for both processes. The best surface quality with 0.56 μm Ra surface roughness value and material removal amount of 7.2 mg were obtained by GOV process while similar level of surface roughness value of 0.52 μm was obtained by removing 6648.03 mg material for AFM. When the AFM process was continued, the best values of 0.24 μm Ra was obtained removing excess material of 17,385.60 mg compared to the GOV process. Also, all these results were supported by SEM images.

Effect of surface roughness on the liquid bridge between two rigid spheres

We aimed to investigate the impact of surface roughness on liquid bridges between spherical particles. Sandblasting was used to control the particle size and produce glass beads and plates with different surface roughness. First, by measuring the advancing and receding contact angles of droplets on different rough surfaces, we analyzed the effects of surface roughness on wettability and hysteresis. Next, we used a custom-made liquid-bridge stretching device to measure the capillary forces of the liquid bridges between spherical particles with different surface roughness values. A charge-coupled device camera acquisition system was set up to capture the morphological changes of the liquid bridge during stretching, and Image View software was used to extract the morphological parameters of the liquid bridge. Theoretically, we reasonably simplified and solved the differential equations for the liquid bridge morphology and used the Young–Laplace equation to calculate the theoretical capillary force of the liquid bridge, providing an in-depth analysis of the influence of surface roughness on the capillary force. Finally, we studied the impact of surface roughness on the volume ratio of the liquid bridge during static stretching and the residual liquid remaining after the liquid bridge breaks. Experimental results indicated that, as the surface roughness increased, the hydrophobicity and wettability hysteresis of the solid surface also increased. The increased hydrophobicity of the surface reduces the solid-liquid contact area of the liquid bridges between the particles, making it easier to form “columnar” or “convex” liquid bridges. Additionally, the enhanced wettability hysteresis causes the solid-liquid contact boundary to lag during the stretching of the liquid bridge, resulting in a decrease in the solid-liquid contact angle. These factors directly alter the geometric shape of liquid bridges during static stretching, thereby affecting capillary forces. Meanwhile, the increase in surface roughness weakens the effect of gravity on the morphology of the liquid bridge, resulting in less liquid mass remaining on the lower sphere after the liquid bridge breaks as the surface becomes rougher.

The Application of ImageJ Software for Roughness Analysis of Dental Implants.

ImageJ software is a versatile, open-source software for visualizing, processing, and analyzing images, which has contributed to its widespread adoption in the scientific community. A notable application of this software is its integration with scanning electron microscope images, where surface roughness can be quantified. This study aims to highlight the need for knowledge and standardization of the technique selected for analysis to ensure the viability of ImageJ software as a reliable alternative for evaluating the surface roughness of dental implants. Images obtained by scanning electron microscopy, depending on the plugin used or the researcher's standardization, yielded different surface roughness values, which were assessed via ImageJ. Thirty grade 4 titanium osseointegrated dental implants via all treated with similar surface treatment methods were studied. Two groups were formed for analysis via ImageJ: Group 1 assessed surface roughness using only the SurfCharJ plugin (n = 12), and Group 2 assessed surface roughness using both the roughness/waviness and SurfCharJ plugin (n = 18). The results showed that the use of different plugins can lead to different outcomes, potentially affecting the quality of the study. This study concluded that a standardized methodology is necessary to ensure consistency in results obtained via ImageJ.

Machining performance analysis of wire-EDM for machining of titanium alloy using multi-objective optimization and machine learning approach

This study investigates the multi-objective optimization of process parameters in wire electrical discharge machining (WEDM) using titanium alloy grade 5 and zinc-coated brass microwire. The novelty lies in the comprehensive investigation of the effects of varying pulse on time (Ton), wire tension (WT), and wire feed rate (WF) on output responses, including surface roughness (SR), surface crack density (SCD), corner diameter (CD), and kerf width (KW). The Box-Behnken design, a sophisticated response surface methodology (RSM) technique, is employed to efficiently explore the complex relationships and interdependencies between these input and output parameters. The study's novel approach incorporates machine learning algorithms, including decision tree, light gradient boosting machine (LightGBM) and random forest, to predict the characteristics of the laser-cut components based on the input parameters. The contour plots generated provide valuable insights into the underlying patterns and associations between input and output features, aiding in the understanding of the WEDM process. The results reveal that the optimized values for SR, SCD, CD, and KW are obtained at specific machining conditions: Ton of 10 μs, WF of 3.79 m/min, and WT of 8 gf. Among the machine learning algorithms employed, random forest outperforms the others in predicting KW, SR, SCD and CD, exhibiting significantly lower mean squared error (MSE) and mean absolute error (MAE) values. This study contributes to the field of WEDM by providing a comprehensive analysis, incorporating advanced experimental design techniques and machine learning algorithms, which can aid in process optimization and quality control in manufacturing applications.

Intelligent prediction of surface roughness of PSZ ceramic grinding based on correlation analysis and CNN-BiLSTM neural network

Partially stabilized zirconia (PSZ) ceramics are widely used in aerospace industry and other fields due to their superior performance. Surface roughness is a key indicator for evaluating the grinding level of PSZ ceramics. In order to reduce the prediction error of grinding surface roughness, an acoustic emission prediction model for PSZ ceramic grinding surface roughness based on correlation analysis and convolution-bidirectional long short term memory neural network (CNN-BiLSTM) was proposed. By analyzing the correlation between the eigenvalues of grinding acoustic emission signals and the grinding surface roughness values, the most relevant frequency bands and feature matrices between the grinding acoustic emission signals and the grinding surface roughness were selected as the input parameters of the CNN-BiLSTM neural network to reduce the error of acoustic emission prediction of grinding surface roughness. The research results show that the average prediction error of PSZ ceramic grinding surface roughness based on correlation analysis and CNN-BiLSTM neural network is less than 3.92%.

Influences of size effect and workpiece temperature during cryogenic micro milling of soft viscoelastic polymer: an experimental assessment

Application of tool-based micromachining in soft polymer has been limited due to high adhesion and low elastic modulus of this material at room temperature. This study aims to evaluate the machinability of a typical viscoelastic soft polymer and understand the effect of material and process parameters on machining performances. In this study, a micro-milling process using cryogenic-assisted cooling is proposed and the importance of temperature control toward glass transition zone was particularly addressed. To identify insight of machinability in micro domain, this article also determines minimum uncut chip thickness (MUCT) and size effects by considering the variations of cutting force and surface integrity with the ratio of h/re (uncut chip thickness (h) to cutting edge radius (re)). The experimental results reveal that consideration of size effect during micromilling of soft viscoelastic polymer helps in reduction of machined surface roughness (Sa) value. Based on the cutting force pattern, it is evaluated that higher machining stability can be achieved during cryogenic machining by reduction of specific cutting force value. Moreover, temperature range around glass transition zone yields more promising experimental outcomes, outperforming other cooling zones.

Surface Roughness Evaluation of Blast-Cleaned Structural Steel Plates Considering Measurement Deviation

AbstractSurface roughness is an important characteristic of blast-cleaned structural steel plates. This is because the adhesion of the coating and the frictional grip of the bolted connections are related to surface roughness. Surface roughness is usually measured using a surface roughness meter. Because the roughness of blast-cleaned surfaces is not uniform, it varies from position to position. The surface roughness test results obtained from a broad area are more valuable than those obtained from a narrow area. Because the measured values contain deviations, they are measured multiple times and averaged to reduce the influence of deviations. However, to evaluate roughness, it is necessary to clarify the measurement conditions to obtain accurate results. Consider combining these sentences as follows: In this study, the surface roughness of the blast-cleaned structural steel sample was measured at multiple locations to obtain its distribution characteristics. During each sample measurement, the detection sensor of the surface roughness meter was lifted and placed on the steel sample to determine deviations from the actual results. The surface roughness distributions of five blast-cleaned samples were the same under the identical measurement conditions. This indicates that accurate results can be obtained by measuring representative samples, without the need for measuring all samples; actually, 17 measurements were adequate to obtain a mean surface roughness value with a 95% confidence level and a 5% acceptable error rate.

Can wheel polishers improve surface properties and color stability of monochromatic resin composites?

BackgroundTo overcome the color layering procedure, monochromatic resin composites have been introduced. However, little is known about their polishability, gloss and color stability. This study aimed to investigate the surface roughness, gloss, and color change of monochromatic resin composites polished with wheel systems after being immersed in coffee.Materials and methodsOmnichroma, Zenchroma, Essentia Universal, Charisma Diamond One and NeoSpectra ST were used to obtain 120-disc samples of 8 × 2 mm. Only one side of the sample was polished with Twist Dia (TWD) or Nova Twist (NOV). The samples were examined for surface roughness, gloss, and color (ΔE and ΔE00) before and after 7 days of immersion in coffee and subsequent repolishing. The discs were examined via SEM. Surface roughness and gloss values were analyzed using ANOVA, Tukey and Pearson correlation tests. ΔE and ΔE00 values were evaluated using T tests, multivariate ANOVA, and Dunnett’s post-hoc tests.ResultsFor TWD groups, the smoothest material was Omnichroma (p < 0.05), while for NOV groups, it was Omnichroma and Zenchroma. Omnichroma was the glossiest, while Charisma Diamond One was the least glossy. In TWD groups, Charisma Diamond One and Essentia Universal were the most discolored, while Zenchroma and Omnichroma were the least. For NOV groups, Essentia Universal and Charisma Diamond One were the most discolored, while NeoSpectra ST, Omnichroma and Zenchroma were the least. After repolishing, Charisma Diamond One did not reach the level of ΔE < 2, while the other groups showed values below. Color evaluation with the CIELab and CIEDE2000 systems revealed similar results for the TWD groups after post-staining.ConclusionsSmooth and glossy surfaces could be achieved with the wheel system regardless of the composite resin. Repolishing after discoloration ensures that the color recovery is below the acceptable limit. Color evaluations with CIELab and CIEDE2000 yielded similar results.

Experimental Study and Random Forest Machine Learning of Surface Roughness for a Typical Laser Powder Bed Fusion Al Alloy

Surface quality represents a critical challenge in additive manufacturing (AM), with surface roughness serving as a key parameter that influences this aspect. In the aerospace industry, the surface roughness of the aviation components is a very important parameter. In this study, a typical Al alloy, AlSi10Mg, was selected to study its surface roughness when using Laser Powder Bed Fusion (LPBF). Two Random Forest (RF) models were established to predict the upper surface roughness of printed samples based on laser power, laser scanning speed, and hatch distance. Through the study, it is found that a two-dimensional (2D) RF model is successful in predicting surface roughness values based on experimental data. The best and minimum surface roughness is 2.98 μm, which is the minimum known without remelting. More than two-thirds of the samples had a surface roughness of less than 7.7 μm. The maximum surface roughness is 11.28 μm. And the coefficient of determination (R2) of the model was 0.9, also suggesting that the surface roughness of 3D-printed Al alloys can be predicted using ML approaches such as the RF model. This study helps to understand the relationship between printing parameters and surface roughness and helps print components with better surface quality.

Wear and roughness analysis of two highly filled flowable composites.

This in vitro study aimed to evaluate surface roughness and wear of highly filled flowables and traditional packable composites. Additionally, the effect of polymerization time on these parameters was evaluated. Two flowable higly filled composites (CMf-Clearfil Majesty ES flow-low viscosity, Kuraray and GUf-Gaenial Universal Injectable, GC) and two packable composites (CM-Clearfil Majesty ES-2, Kuraray and GU-Gaenial A'CHORD, GC) were used to create 160 specimens (n = 40;8 × 6×4mm). For each tested material, two subgroups were considered according to the polymerization time (n = 20): 10s or 80s. After setting, the specimens were subjected to chewing simulations (240.000 cycles, 20N), and wear was measured by the laser integrated in the chewing simulator. The surface roughness was measured using a rugosimeter, before and after chewing cycles. Two representative specimens per group were observed under scanning electron microscope (SEM). Data were collected and statistically analyzed (p < 0.05). Wear analysis highlighted statistically significant differences between the groups: CMf10-CMf80 (p = 0.000), CMf10-CM10 (p = 0.019), CMf10-GUf10 (p = 0.002), CM10-CM80 (p = 0.000), CM80-GUf80 (p = 0.02), GUf10-GUf80 (p = 0.000), GUf10-GU10 (p = 0.043) and GU10-GU80 (p = 0.013). Statistically significant differences in surface roughness were highlighted between the groups: CMf10-CMf80 (p = 0.038), CMf80-CM80 (p = 0.019), CMf80-GU80 (p = 0.010), CM80-GUf80 (p = 0.34) and GUf80-GU80 (p = 0.003). Surface roughness and wear of highly filled flowable composites were comparable to that of traditional paste composites. Furthermore, a longer curing time leads to an improvement in the mechanical properties of the composites. Highly filled flowables can be a valid alternative to paste composites in occlusal areas due to its similar surface roughness and wear values, especially when overcured.