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

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

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

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

First, the effect of magnetic field intensity and nano-ferrofluid concentrations on surface roughness was evaluated in magnetic minimum quantity lubrication (MMQL). Then, the effect of lubricant flow rate and nozzle position on surface roughness was investigated in MQL, MMQL, electrostatic MQL (EMQL) and electromagnetic MQL (EMMQL).

This study examined the performance of MQL under magnetic and electric fields in turning AISI 304 stainless steel in terms of surface roughness and compared the results with those obtained from wet cutting and MQL turning operations. To prepare the nano-ferrofluid used in different states of MQL, Fe₃O₄ nanoparticles were added to the base fluid.

The results showed that the surface roughness under the EMMQL technique decreased by 36% and 49.4% on average compared with wet and MQL techniques, respectively. The lubrication technique affected the surface roughness by 90.2%, whereas it was 8.3% for the lubricant flow rate. EMQL and EMMQL techniques had no significant difference in their effects on surface roughness. In the innovative MMQL technique, the nano-ferrofluid concentration of 6% and magnetic field intensity of 93 G resulted in lower surface roughness of the workpiece relative to other counterparts.

Examining previously published studies showed that using nano-ferrofluids under a magnetic field for cooling purposes in machining processes have less considered by researchers. This study applies an innovative method of lubrication under the concurrent effect of magnetic and electric fields, called EMMQL, to improve the efficiency of MQL in machining hard-to-cut materials. For comprehensively inspecting the newly presented method, the effects of several parameters, including the nano-ferrofluid concentration, magnetic field intensity, lubricant flow rate and position of lubricant spray nozzle, on the surface roughness of workpiece in turning of AISI 304 stainless steel are investigated.

In this study, experimental studies were carried out using different process parameters of the soft pneumatic gripper (SPG) fabricated by the fused deposition modeling method. In the experimental studies, the surface quality of the gripper was examined by determining four different levels and factors. The experiment was designed to estimate the surface roughness of the SPG.

The methodology consists of an experimental phase in which the SPG is fabricated and the surface roughness is measured. Thermoplastic polyurethane (TPU) flex filament material was used in the fabrication of SPG. The control factors used in the Taguchi L16 vertical array experimental design and their level values were determined. Analysis of variance (ANOVA) was performed to observe the effect of printing parameters on the surface quality. Finally, regression analysis was applied to mathematically model the surface roughness values obtained from the experimental measurements.

Based on the Taguchi signal-to-noise ratio and ANOVA, layer height is the most influential parameter for surface roughness. The best surface quality value was obtained with a surface roughness value of 18.752 µm using the combination of 100 µm layer height, 2 mm wall thickness, 200 °C nozzle temperature and 120 mm/s printing speed. The developed model predicted the surface roughness of SPG with 95% confidence intervals.

It is essential to examine the surface quality of parts fabricated in additive manufacturing using different variables. In the literature, surface roughness has been examined using different factors and levels. However, the surface roughness of a soft gripper fabricated with TPU material has not been examined previously. The surface quality of parts fabricated using flexible materials is very important.

Material extrusion is one of the most commonly used approaches within the additive manufacturing processes available. Despite its popularity and related technical advancements, process reliability and quality assurance remain only partially solved. In particular, the surface roughness caused by this process is a key concern. To solve this constraint, experimental plans have been exploited to optimize surface roughness in recent years. However, the latter empirical trial and error process is extremely time- and resource consuming. Thus, this study aims to avoid using large experimental programs to optimize surface roughness in material extrusion.

This research provides an in-depth analysis of the effect of several printing parameters: layer height, printing temperature, printing speed and wall thickness. The proposed data-driven predictive modeling approach takes advantage of Machine Learning (ML) models to automatically predict surface roughness based on the data gathered from the literature and the experimental data generated for testing.

Using ten-fold cross-validation of data gathered from the literature, the proposed ML solution attains a 0.93 correlation with a mean absolute percentage error of 13%. When testing with our own data, the correlation diminishes to 0.79 and the mean absolute percentage error reduces to 8%. Thus, the solution for predicting surface roughness in extrusion-based printing offers competitive results regarding the variability of the analyzed factors.

There are limitations in obtaining large volumes of reliable data, and the variability of the material extrusion process is relatively high.

Although ML is not a novel methodology in additive manufacturing, the use of published data from multiple sources has barely been exploited to train predictive models. As available manufacturing data continue to increase on a daily basis, the ability to learn from these large volumes of data is critical in future manufacturing and science. Specifically, the power of ML helps model surface roughness with limited experimental tests.

This study aims to comparatively analyze the cut parts obtained as a result of cutting the Ni-based Inconel 625 alloy, which is widely used in the aerospace industry, with the wire electro-discharge machining (WEDM) and abrasive water jet machining (AWJM) methods in terms of macro- and microanalyses.

In this study, calipers, Mitutoyo SJ-210, Nikon SMZ 745 T, scanning electron microscope and energy dispersive X-ray were used to determine kerf, surface roughness and macro- and microanalyses.

Considering the applications in the turbine industry, it has been determined that the WEDM method is suitable to meet the standards for the machinability of Inconel 625 alloy. In contrast, the AWJM method does not meet the standards. Namely, while the kerf angle was formed because the hole entrance diameters of the holes obtained with AWJM were larger than the hole exit diameters, the equalization of the hole entry and exit dimensions, thanks to the perpendicularity and tension sensitivity of the wire electrode used in the holes drilled with WEDM ensured that the kerf angle was not formed.

It is known that the surface roughness of the parts used in the turbine industry is accepted at Ra = 0.8 µm. In this study, the average roughness value obtained from the successful drilling of Inconel 625 alloy with the WEDM method was 0.799 µm, and the kerf angle was obtained as zero. In the cuts made with the AWJM method, thermal effects such as debris, microcracks and melted materials were not observed; an average surface roughness of 2.293 µm and a kerf of 0.976° were obtained.

The goal of this study is to determine the values of the process parameters that should be used during the machining of ceramic tile using the abrasive water jet (AWJ) process in order to achieve the lowest possible values for surface roughness and kerf taper angle.

In the present work, ceramic tile is processed by the AWJ process and experimental data were recorded using the RSM approach based Box–Behnken design matrix. The input process factors were water jet pressure, jet traverse speed, abrasive flow rate and standoff distance, to determine the surface roughness and kerf taper angle. ANOVA was used to check the adequacy of model and significance of process parameters. Further, the elite opposition-based learning grasshopper optimization (EOBL-GOA) algorithm was implemented to identify the simultaneous optimization of multiple responses of surface roughness and kerf taper angle in AWJ.

The suggested EOBL-GOA algorithm is suitable for AWJ of ceramic tile, as evidenced by the error rate of ±2 percent between experimental and predicted solutions. The surfaces were evaluated with an SEM to assess the quality of the surface generated with the optimal settings. As compared with initial setting of the SEM image, it was noticed that the bottom cut surface was nearly smooth, with less cracks, striations and pits in the improved optimal results of the SEM image. The results of the analysis can be used to control machining parameters and increase the accuracy of AWJed components.

The findings of this study present an innovative method for assessing the characteristics of the nontraditional machining processes that are most suited for use in industrial and commercial applications.

This study aims to reveal the influences of three-dimensional (3D) printing parameters such as layer heights (0.1 mm, 0.2 mm and 0.4 mm), infill rates (40, 70 and 100%) and geometrical property as tapered angle (0, 0.25 and 0.50) on vibrational behavior of 3D-printed polyethylene terephthalate glycol (PET-G) tapered beams with fused filament fabrication (FFF) method.

In this performance, all test specimens were modeled in AutoCAD 2020 software and then 3D-printed by FFF. The effects of printing parameters on the natural frequencies of 3D-printed PET-G beams with different tapered angles were also analyzed experimentally, and numerically (finite element analysis) via Ansys APDL 16 program. In addition to vibrational properties, tensile strength, elasticity modulus, hardness, and surface roughness of the 3D-printed PET-G parts were examined.

It can be stated that average surface roughness values ranged between 1.63 and 6.91 µm. In addition, the highest and lowest hardness values were found as 68.6 and 58.4 Shore D. Tensile strength and elasticity modulus increased with the increase of infill rate and decrease of the layer height. In conclusion, natural frequency of the 3D-printed PET-G beams went up with higher infill rate values though no critical change was observed for layer height and a change in tapered angle fluctuated the natural frequency values significantly.

The influence of printing parameters on the vibrational properties of 3D-printed PET-G beams with different tapered angles was carried out and the determination of these effects is quite important. On the other hand, with the addition of glass or carbon fiber reinforcements to the PET-G filaments, the material and vibrational properties of the parts can be examined in future works.

As a result of this study, it was shown that natural frequencies of the 3D-printed tapered beams from PET-G material can be predicted via finite element analysis after obtaining material data with the help of mechanical/physical tests. In addition, the outcome of this study can be used as a reference during the design of parts that are subjected to vibration such as turbine blades, drone arms, propellers, orthopedic implants, scaffolds and gears.

It is believed that determination of the effect of the most used 3D printing parameters (layer height and infill rate) and geometrical property of tapered angle on natural frequencies of the 3D-printed parts will be very useful for researchers and engineers; especially when the importance of resonance is known well.

When the literature efforts are scanned in depth, it can be seen that there are many studies about mechanical or wear properties of the 3D-printed parts. However, this is the first study which focuses on the influences of the both 3D printing parameters and tapered angles on the vibrational behaviors of the tapered PET-G beams produced with material extrusion based FFF method. In addition, obtained experimental results were also supported with the performed finite element analysis.

When processing 11Cr-3Co-3W martensitic heat-resistant steel, the traditional pouring cooling method often appears large cutting force, high cutting temperature, serious tool wear and poor surface quality. This paper aims to use new cooling methods for processing this problem.

Different performance indicators such as cutting force, tool wear and surface quality were measured and analysed under different continuous milling times. The relationship between liquid nitrogen flow and cutting force and surface roughness was analysed and measured.

The results show that with the increase of liquid nitrogen flow, the cutting force decreases, especially the Fx component, which decreases by 10%. When the liquid nitrogen flow reaches 8 L/min, the effect of increasing the liquid nitrogen flow on reducing the cutting force becomes smaller. The cutting force reduced by up to 15%, and the tool life increased up to 20% using liquid nitrogen cryogenic cooling than in cutting liquids cooling. When minimal quantities of lubricant (MQL) was added, the cutting force was reduced by 23%, and the tool life increased by 25%. When the cutting speed increases from 100 m/min to 250 m/min, the cutting force with cutting liquid cooling does not change significantly while the cutting force with liquid nitrogen cooling decreases with the cutting speed increasing. It shows that liquid nitrogen cooling is more suitable for high-speed machining. After the cutting length reaches 66 m, the surface roughness of the workpiece using liquid nitrogen cooling method larger than that of the cutting liquid cooling method. When MQL is added into liquid nitrogen, the lubrication performance is improved, and the surface roughness of the workpiece is reduced about 8%.

Many studies had focused on the improvement of tool life and surface quality by different cooling methods, or on the injection process and chip mechanism. However, there are few relevant studies on the variation of cooling and lubrication properties with the change of cutting length in liquid nitrogen cryogenic processing. In this research, different performance indicators such as cutting force, tool wear and surface quality were measured and analysed under different continuous milling times. The relationship between liquid nitrogen flow and cutting force and surface roughness was analysed and measured.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2023-0053/

This paper aims to investigate the influence of “BroncoCut-X” (copper core-ZnCu50 coating) electrode on the machining of Ti-3Al-2.5V in view of its extensive use in aerospace and medical applications. The machining parameters are selected as Spark-off Time (ST_off), Spark-on Time (ST_on), Wire-speed (S_w), Wire-Tension (WT) and Servo-Voltage (S_v) to explore the machining outcomes. The response characteristics are measured in terms of material removal rate (MRR), average kerf width (KW) and average-surface roughness (SA).

Taguchi’s approach is used to design the experiment. The “AC Progress V2 high precision CNC-WEDM” is used to conduct the experiments with ϕ 0.25 mm diameter wire electrode. The machining performance characteristics are examined using main effect plots and analysis of variance. The grey-relation analysis and fuzzy interference system techniques have been developed to combine (called grey-fuzzy reasoning grade) the experimental response while Rao-Algorithm is used to calculate the optimal performance.

The hybrid optimization result is obtained as ST_off = 50µs, ST_on = 105µs, S_w = 7 m/min, WT = 12N and S_v=20V. Additionally, the result is compared with the firefly algorithm and improved gray-wolf optimizer to check the efficacy of the intended approach. The confirmatory test has been further conducted to verify optimization results and recorded 8.14% overall machinability enhancement. Moreover, the scanning electron microscopy analysis further demonstrated effectiveness in the WEDMed surface with a maximum 4.32 µm recast layer.

The adopted methodology helped to attain the highest machinability level. To the best of the authors’ knowledge, this work is the first investigation within the considered parametric range and adopted optimization technique for Ti-3Al-2.5V using the wire-electro discharge machining.

The purpose of this study is to design and process the optimal V-shaped microstructure for 7075 aluminum alloy and reveal its wear resistance mechanism and performance.

The hydrodynamic pressure lubrication models of the nontextured, V-shaped, circular and square microtextures are established. The corresponding oil film pressure distributions are explored. The friction and wear experiments are conducted on a rotating device. The effects of the microstructure shapes and sizes on the wear mechanisms are investigated via the friction coefficients and surface morphologies.

In comparison, the V-shaped microtexture has the largest oil film carrying capacity and the lowest friction coefficient. The wear mechanism of the V-shaped microtexture is dominated by abrasive and adhesive wear. The V-shaped microtexture has excellent wear resistance under a side length of 300 µm, an interval of 300 µm and a depth of 20 µm.

This study is conductive to the design of wear-resistant surfaces for friction components.