Surface Roughness Measurements Research Articles

Effective use of adaptive slicing in binder jetting using Taguchi method and surface roughness measurement with image processing

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.

PERFORMANCE ENHANCEMENT OF BRASS EDM ELECTRODES WITH CRYOGENIC TREATMENT WHILE MACHINING THE COLD WORK STEEL AISI D2

This study investigates the performance of deep cryogenically treated brass (CuZn25Al5) electrodes in the die-sink EDM process. Two different cryogenic treatment durations, 6 h and 12 h, were applied to 8 mm diameter electrodes, and their effects were compared to untreated electrodes. The machining tests were conducted under moderate and aggressive conditions. In the machining tests, the 6-h cryo-treated electrode exhibited a 16.8% increase in material removal rate (MRR) under moderate conditions and a 19.7% increase under aggressive conditions compared to the reference electrode. The 12-h cryo-treated electrode showed similar MRR values to the reference electrode but improved tool wear resistance by 9.4% under moderate conditions. The kerf angle was minimized, indicating better hole verticality, in the 6-h cryo-treated electrode group. The improvement in machining performance was attributed to the enhancement in electrical conductivity of the electrodes, which increased by 28% for the 6-h cryo-treated electrode and 20% for the 12-h cryo-treated electrode. X-ray diffraction (XRD) analysis revealed shifts in peak positions and possible phase transformations due to cryogenic treatment. Surface roughness measurements showed improved surface conditions in the cryo-treated electrodes under aggressive conditions. The results indicate that cryogenic treatment enhances MRR, reduces tool wear, and improves surface quality in die-sink EDM. These improvements are attributed to increased electrical conductivity and changes in the internal structure of the brass electrode.

Optimization of the extrusion rate for different layer thicknesses to achieve controlled mechanical properties in MEX 3D printing of low-alloy steel

Composite extrusion modeling is an advanced material extrusion additive manufacturing process that requires fine-tuning of printing parameters for printing injection molding feedstocks. In order to achieve comparable high-quality parts at different layer thicknesses, the parameters must be optimized for the respective layer thicknesses. In this work, the printing parameters for AISI 8740 low-alloy steel injection molding material are optimized for four different layer thicknesses. The extrusion multiplier values for each layer thickness are tuned, allowing fine adjustment of the printer's screw rotation speed at every layer thickness, resulting in all final parts' maximum densities (≥ 98 %) with high accuracies. Scanning electron microscope images, surface roughness measurements, and printing precision tests proved the good and comparable high-quality of all optimized printed parts. Young's modulus, tensile and yield strengths also raised by ∼24 %, ∼16 % and ∼15 %, respectively, compared to the non-optimized printed sintered part. The achieved tensile strength range of (∼888–947) MPa and yield strength range of (∼574–586) MPa of all optimized printed sintered parts were also higher than those provided by the feedstock manufacturer. This promising approach significantly reduces printing time and manufacturing costs without compromising the printed final parts' quality and mechanical properties. The adjusting screw rotation speed methodology allows broader applicability across diverse material extrusion processes.

Determining Riverine Surface Roughness at Fluvial Mesohabitat Level and Its Influence on UAV-Based Thermal Imaging Accuracy

Water surface roughness (SR) is a highly relevant parameter governing data reliability in remote sensing applications, yet lacking appropriate methodology in riverine habitats. In order to assess thermal accuracy linked to SR of thermal imaging derived from an unmanned aerial vehicle (UAV), we developed the SR Measurement Device (SRMD). The SRMD uses the concept of in situ quantification of wave frequency and wave amplitude. Data of nine installed SRMDs in four different fluvial mesohabitat classes presented a range of 0 to 47 waves per 30 s and an amplitude range of 0 to 6 cm. Even subtle differences between mesohabitat classes run, riffle, and no-/low-flow still and pool areas could be detected with the SRMD. However, SR revealed no significant influence on the accuracy of thermal infrared (TIR) imagery data in our study case. Overall, the presented device expands existing methods of riverine habitat assessments and has the potential to produce highly relevant data of SR for various ecological and technical applications, ranging from remote sensing of surface water and habitat quality characterizations to bank stability and erosion risk assessments.

Influence of Cations on Direct CO2 Capture and Mineral Film Formation: The Role of KCl and MgCl2 at the Air/Electrolyte/Iron Interface.

Uncovering the mechanisms associated with CO2 capture through mineralization is vital for addressing rising CO2 levels. Iron in planetary soils, the mineral cycle, and atmospheric dust react with CO2 through complex surface chemistry. Here, the effect of cations on the growth of carbonate films on iron surfaces was investigated. In situ polarized modulated infrared reflection absorption spectroscopy was used to measure CO2 adsorption and oxidation of iron in MgCl2(aq) and KCl(aq), compared to FeCl2(aq) at the air/electrolyte/iron interface. The cation was found to influence the film composition and growth rates, as corroborated by infrared and photoelectron spectroscopy. In MgCl2(aq), a mixture of hydromagnesite, magnesite, and a Mg hydroxy carbonate film was grown on iron, while in KCl(aq), a potassium-rich bicarbonate film was grown. The cations were found to affect the rates of hydroxylation and carbonation, confirming a specific cation effect on carbonate film growth. In the submerged region, a heterogeneous mixture of lepidocrocite and iron hydroxy carbonate was produced, suggesting that Fe2+ dominates the surface products. Surface roughness measurements from in situ atomic force microscopy indicate iron initially corrodes faster in MgCl2(aq) than KCl(aq), due to the Cl- ions that initiate pitting and corrosion. In this region, cations were not found to affect the morphologies. This study shows surface corrosion is necessary to provide nucleation sites for film growth and that the cations influence the carbonate film, relevant for CO2 capture and planetary processes.

Polarization-multiplexed snapshot lateral shearing interferometric sensor for surface roughness measurements

A compact optical roughness measurement sensor based on lateral shearing interferometry is theoretically described and experimentally verified. By adopting the advanced surface roughness parameter extraction methods based on statistical machine learning technique and the partial integration approach, the sensor using a polarization grating and a polarization camera can instantaneously obtain a surface gradient map and provide reliable surface roughness parameters. To verify the operation and the performance of the sensor, a flat mirror and roughness standard specimens were measured, and the results were compared with those of a white light scanning interferometer as the reference values. As a result, the roughness parameters were very close to the reference values with <5 nm accuracy and <0.1 nm repeatability.

Rapid determination of corrosion under fatigue loading based on tensile loading

This study tests the hypothesis that corrosion properties under fatigue loading can be evaluated based on simple tensile tests without the need to perform costly and time-consuming corrosion fatigue tests. Two types of stainless steel 304L specimens, i.e., smooth and compact tension (CT), are exposed to static and fatigue loading in two aqueous solutions with different NaCl concentrations. Strain analysis, surface roughness measurements, scanning electrochemical microscopy (SECM), and Tafel polarization techniques are employed to unveil the effects of mechanical stress and strain on the corrosion behavior at micro and macro scales, a phenomenon known as electro-chemo-mechanical interaction. Finite element analysis (FEA) is performed to calculate the stress and strain field in the specimens. Digital image correlation (DIC) is used to validate the FEA results. The results indicate a strong correlation between the static stress, strain, and surface roughness with the corrosion rate. In particular, the study reveals a strong correlation between corrosion current (and corrosion current density) under fatigue loading with that under static tensile loading, thereby providing a means to evaluate the corrosion properties under fatigue loading solely from static tests. Fatigue loading leads to a progressive reduction in the corrosion potential as the number of cycles increases. The corrosion current density, icorr, is linked to the stress and accumulated plastic strain by an empirical equation, shedding lights on the complex electro-chemo-mechanical interaction. Additionally, opportunities for future research are discussed.

High cycle fatigue life estimation of punched and trimmed specimens considering residual stresses and surface roughness

Shear cutting processes have a detrimental effect on fatigue of high strength metal components. The effect tends to increase with material grade, counteracting the task of reducing weight in chassis components using higher strength materials. Base material fatigue data are often available, but assessment of components with cut edges often require additional costly and time-consuming testing. This paper provides a methodology for estimation of fatigue life reduction by using residual stresses obtained from process simulations, and measured surface roughness in the cut edge. A stress relaxation criterion is applied to handle reduction of the initial local residual stresses. Two complex phase steels and one aluminum alloy are studied for validating the approach. Polished fatigue data is reduced to estimate S-N curves of trimmed and punched specimens at different load ratios. Good agreement between the model and test results are found for all cases. The needed data for the predictions are only a high cycle S-N relationship for polished material, uniaxial tensile properties, and the cut edge fracture surface residual stress and roughness without any parameter fitting, making it a convenient tool for estimating the reduction in fatigue life and for parameter studies.

Effect of surface roughness parameters on frictional properties of AlSi10Mg alloy

Experimental study of the effects of surface roughness parameters and their relationship to the coefficient of friction (COF) on AlSi10Mg alloy. The information demonstrates that the average surface roughness (Ra) does not directly correlate with COF when sliding is presented. This work is focused on the relationship and interaction between the roughness parameters (Ra), maximum profile height (Rt), average profile slope, and COF. To alter the surface roughness effect, the samples of the alloy are chemically treated with an alkaline 0, 5, 10, 15, 25, and 50 minutes and tested under different circumstances. Using a T-05 block-on-ring tribometer, the COF is calculated, and surface roughness measurements are collected utilizing an optical system for measuring three-dimensional surfaces. The program MATLAB is used to analyze the obtained data. Contrarily, the results demonstrate that there is a substantial positive association with COF under sliding conditions, while Ra and Rt can change without affecting CO significantly.

The effect of different liquids on the surface roughness and color stability of single shade and nanohybrid resin composites: An AFM and SEM analysis.

The aim of this study is to evaluate the surface roughness (SR) and color changes of single-shade and nanohybrid resin-based restorative materials (RBC) after immersion in liquids at different pH values. For RBCs, a total of 120 specimens, 30 for each material, were prepared using 10 mm diameter and 2 mm thick molds. For flowable bulk fill RBC, a total of 40 specimens, 10 for each material, were prepared using 10 mm diameter and 4 mm thick molds (n = 10). After initial color and SR measurements, samples were stored in the liquids for 14 days and all of the measurements were repeated on 14th days. Scanning electron microscopy and atomic force microscopy analyzes were performed in all groups. When SR results are examined; among all liquids, the highest SR value was observed in the Carisma Diamond One (CDO) group, while the lowest SR value was observed in the Omnichroma Flow Bulk (OMF) group (p < .05). When the color changes (ΔE) results are examined; it was observed that CDO group had highest color change and OMF group had the lowest values. It has been observed that among the liquids, the liquids that affect the ΔE values of the materials the most are coffee and cola. When the ΔE values of the subgroups of the materials were examined, there was a statistically significant difference in all subgroups of RBCs (p < .05). While acidic liquids increased the SR of RBCs, coffee more affected the color change of RBCs. RESEARCH HIGHLIGHTS: Clinicians should keep in mind that the RBCs tested may change their surface properties and colors when exposed to various liquids. People who have RBCs should pay attention to the consumption of acidic and highly pigmented liquids.

Failure Analysis of Cryogenically Treated and Gas Nitrided Die Steel in Rotating Bending Fatigue

&lt;div&gt;AISI H13 hot work tool steel is commonly used for applications such as hot forging and hot extrusion in mechanical working operations that face thermal and mechanical stress fluctuations, leading to premature failures. Cryogenic treatment was applied for AISI H13 steel to improve the surface hardness and thereby fatigue resistance. This work involves failure analysis of H13 steel specimens subjected to cryogenic treatment and gas nitriding. The specimens were heated to 1020°C, oil quenched followed by double tempering at 550°C for 2 h, and subsequently, deep cryogenically treated at −185°C in the cryochamber. Gas nitriding was carried out for 24 h at 500°C for 200 μm case depth in NH&lt;sub&gt;3&lt;/sub&gt; surroundings. The specimens were subjected to rotating bending fatigue at constant amplitude loading at room temperature. Measurement of surface roughness, hardness, and microstructural analysis indicated improved fatigue life for cryogenically treated specimens as compared to gas nitride, which could be attributed to fine carbide precipitation accountable for the delayed crack initiation and propagation.&lt;/div&gt;

Corrosion effects on axial pile capacity

Increase in surface roughness by corrosion processes has long been neglected as potential factor influencing pile setup. However, recently there has been an increasing number of studies who referred pile setups largely or solely to corrosion and sand incrustation. Only limited research has been conducted to assess the potential impacts of corrosion directly on pile capacity development. Therefore, we sampled steel and crust surfaces from a steel monopile having been aged for ∼four years in sand. Surface roughness measurements and interface direct shear testing were performed to quantify changes for friction angles. The impact of friction angle changes on pile capacity were calculated using ICP-05 and UWA-05 for a large- and small-diameter geometry and referenced by field data. We can show that corrosion can significantly contribute to temporal pile capacity gains. Evidence have been found that the maximum and critical interface friction angles evolve differently considering the same changes in roughness. Also, differences in shearing behavior to literature were observed, being potentially a result of the naturally corroded surfaces sheared in our study. A strong, maybe exaggerated sensitivity of the capacity prediction approaches to pile diameter was observed. Effects causing an increase in surface roughness, should be reconsidered as an important factor influencing pile setup.

Investigation of the effect of ball-burnishing treatment applied to Al 7075-T6 alloy on mechanical and crystallographic properties

ABSTRACT In this study, the mechanical, microstructural, and crystallographic effects of ball-burnishing applied to Al 7075-T6 alloy at 0.15–0.30 mm penetration depth, 0.15–0.30–0.60 mm/rev changing feed rates and 100–200 rpm range were investigated. After the ball-burnishing processes were carried out in different parameters, surface roughness measurements were applied to determine the surface qualities, and hardness and impact energy tests were applied to characterise the mechanical properties. Dislocation density and texture coefficient values were calculated by determining the crystallographic properties using X-ray diffraction. It has been determined that the ball-burnishing process directly affects the surface roughness, depending on the increasing rotational speed and feed rate. As a result of microstructural investigations, the average grain size decreased with increasing amount of deformation on the sample surface. At 200 rpm ball-burnishing parameter, the surface hardness of the sample increased by approximately 41% compared to the initial state and was measured as 265 HV2. It was determined that the ball-burnishing process did not positively affect the impact of the toughness of the alloy. The reason for this is that the roughness and scratches on the surface caused by the ball-burnishing process have a notch effect, increasing the crack formation and propagation speed.

Tool wear and surface roughness characteristics in sustainable machining of additively manufactured titanium alloys

Titanium is widely acknowledged as a challenging metal due to its inherent characteristics. Manufacturers often encounter challenges such as tool wear, reduced tool lifecycle, and increased cutting heat when working with Ti64. This research investigates the cutting characteristics of additively manufactured (AMed) Ti64 under dry cutting, Minimum Quantity Lubrication (MQL), Cryogenic Carbon dioxide (CO2), and a hybrid approach combining MQL and CO2 conditions. Surface roughness, flank wear, temperature, chip morphology, and microhardness were analyzed to assess the impact of cooling strategies. Results indicate that the hybrid approach outperforms individual methods, showing superior surface finish and reduced tool wear. Machined Surface roughness (Ra) measurements reveal a substantial improvement in the hybrid condition, reducing Ra values by 62.44–67.02%, 35.65–41.38%, and 18.68–27.59% compared to dry, MQL, and CO2. Tool wear assessments exhibit significantly lower flank wear values in the hybrid condition, emphasizing the synergistic benefits of lubrication and cryogenic cooling. This research provides valuable insights into tailoring cooling strategies for optimal precision in machining AMed-Ti64 material, which is crucial for achieving high-quality manufacturing outcomes.

Surface Structuring of the CP Titanium by Ultrafast Laser Pulses

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.

Investigation on surface roughness of ultrasonic assisted vapour smoothing of acrylonitrile butadiene styrene printed sample

Additive manufacturing offers many benefits, yet it is confronted with the challenge of rough surfaces resulting from the appearance of seam lines on the printed parts due to the layer-by-layer printing process. This study investigates the effect of ultrasonic-assisted vapor smoothing on the surface roughness of 3D-printed ABS samples. The ABS samples were printed with an open-source FDM printer. The vapour smoothing process was conducted by applying acetone and altering the ultrasonic frequencies and times to 0 kHz, 10 kHz, and 20 kHz for the frequencies and 10 min, 20 min, and 30 min for the times. The surface roughness measurements were performed using a Mitutoyo SJ-301 surface roughness tester. The findings demonstrated enhancements in the quality of the surface, reduction in the visibility of layer lines, and improved surface smoothness for all the samples. From the ANOVA analysis, the average value of Ra for 30 kHz frequency is 2.57 μm, which is better than 3.19 μm for 10 kHz frequency. The manipulation of ultrasonic frequencies and exposure durations decreased surface roughness parameters, suggesting enhancement of the time to attain smoother surfaces. This work demonstrates the effectiveness of ultrasonic-assisted vapour smoothing as a feasible post-processing technique for enhancing surface quality in 3D-printed ABS-printed parts.

Machinability investigation of natural fibers reinforced polymer matrix composite under drilling: Leveraging machine learning in bioengineering applications

The growing demand for fiber-reinforced polymer (FRP) in industrial applications has prompted the exploration of natural fiber-based composites as a viable alternative to synthetic fibers. Using jute–rattan fiber-reinforced composite offers the potential for environmentally sustainable waste material decomposition and cost reduction compared to conventional fiber materials. This article focuses on the impact of different machining constraints on surface roughness and delamination during the drilling process of the jute–rattan FRP composite. Inspired by this unexplored research area, this article emphasizes the influence of various machining constraints on surface roughness and delamination in drilling jute–rattan FRP composite. Response surface methodology designs the experiment using drill bit material, spindle speed, and feed rate as input variables to measure surface roughness and delamination factors. The technique of order of preference by similarity to the ideal solution method is used to optimize the machining parameters, and for predicting surface roughness and delamination, two machine learning-based models named random forest (RF) and support vector machine (SVM) are utilized. To evaluate the accuracy of the predicted values, the correlation coefficient (R2), mean absolute percentage error, and mean squared error were used. RF performed better in comparison with SVM, with a higher value of R2 for both testing and training datasets, which is 0.997, 0.981, and 0.985 for surface roughness, entry delamination, and exit delamination, respectively. Hence, this study presents an innovative methodology for predicting surface roughness and delamination through machine learning techniques.

Influence of contour processing parameters on porosity, surface roughness, and fatigue life in laser powder bed Al-10Si-0.4Mg

Additive manufacturing (AM) enables fabrication of net-shape components with high geometric complexity, however mechanical properties of parts with as-fabricated surfaces are limited by surface roughness and subsurface porosity that may initiate fatigue cracks. This study aims to improve the utility of parts with as-fabricated surfaces by quantifying processing-surface condition-fatigue performance relationships, optimizing surface contour parameters for fatigue performance, and investigating the application of surface profilometry as a non-destructive quality control method. Eleven contour parameter sets of varying energy densities were produced in three classifications: no contour passes, single contour passes, and contours with secondary healing passes. Surface roughness was evaluated using line scan profilometry and subsurface porosity by optical microscopy. Contouring reduced the average surface roughness from Ra ≅ 25 μm to Ra ≅ 5 μm, and the layer of subsurface porosity introduced by this process could be partially eliminated by a secondary healing pass. One set of processing conditions from each contour class was selected for fatigue studies (R = -1), and their results were compared with the fatigue data from machined and polished specimens to evaluate the relative influence of surface condition. Relative to machined and polished specimens, fatigue lives are approximately five times lower for contoured specimens (with and without a healing pass) and twenty times lower for non-contoured specimens at equivalent stress levels up to 107 cycles to failure. Fractographic measurements of initial defect √area of all specimens reveal that fatigue behavior is well characterized by stress intensity factor amplitude across all surface conditions. An extreme value statistical method is developed using profilometry data to predict S-N curves, and it is concluded that non-destructive surface roughness measurements may be suitable for estimating the fatigue lives of components with as-fabricated surfaces as a rapid method for quality control.

Evaluation of High-Frequency Measurement Errors from Turned Surface Topography Data Using Machine Learning Methods.

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.

Experimental investigation and optimization of the effect garnet vibratory tumbling as a post-process on the surface quality of 3D printed PLA parts

The method known as additive manufacturing causes high surface roughness between layers depending on the technique used at the end of the product development process. This can be an important problem in three-dimensional (3D) manufacturing depending on the usage area. To solve this problem, in this experimental study, the effect of vibratory tumbling (VT) on surface roughness in 3D printing was investigated using garnet abrasive particles. Optimization with the best parameters was also performed and the results were analyzed. This experimental study investigated the effect of vibratory tumbling on surface roughness in 3D printing produced from Polylactic acid (PLA) material using garnet abrasive particles. The surface roughness (Ra) values were measured at different vibration durations for each mesh size. The results provide insights into the impact of vibratory tumbling on surface roughness in 3D-printed parts. The study involved subjecting the printed parts to vibratory tumbling using garnet abrasive particles of various mesh sizes (80, 90, 100, 120, 150, 180, and 220 mesh). Surface roughness measurements were taken at different vibration durations (2, 4, 6, 8, 10, and 12 hours) for each mesh size. A surface roughness measuring device was used to obtain the roughness values. The findings reveal that vibratory tumbling with garnet abrasive particles effectively reduces surface roughness in 3D printed parts. As the vibration duration increased, smoother surfaces were achieved. The data collected for each mesh size and vibration duration offer valuable insights into the relationship between vibratory tumbling and surface roughness in 3D printing. The surface roughness of the printed samples was reduced by 60% on average by using the optimum values after post-process. This research highlights the potential of vibratory tumbling as a viable method for improving surface roughness in 3D printing applications. Emphasis is placed on optimizing the vibration duration and selecting the appropriate mesh size to achieve the desired surface quality. Overall, this study contributes to our understanding of the effect of vibratory tumbling on surface roughness in 3D printing and provides considerable insights for enhancing surface quality in additive manufacturing processes.