Material Surface Roughness Research Articles

COMPARATIVE EVALUATION OF HARDNESS AND SURFACE ROUGHNESS AFTER DIFFERENT COOLING PROCEDURES OF HEAT CURE DENTURE BASE MATERIALS

Aim: To evaluate the influence of different cooling procedures on mechanical properties of DPI & LUCITONE heat cure poly methyl methacrylate denturebase materials before andafter 1year of brushing simulation. Materials And Methods: A total of 100 specimens were prepared using two heat cure denture base materials i.e, DPI and LUCITONE. The specimens in each group were subdivided into five groups (n=10 ) based on the cooling procedure followed: A: Flask remains in water bath till room temperature B: Remove flask from water bath, bench cool for 30min and then cool under running water for 15min C: Remove flask from water bath, bench cool for 10min and then cool under running water for 15min D: Remove flask from water bath and bench cool till room temperature E: Remove the flask from water bath and cool under running water for 15 minutes.After finishing and polishing, samples were placed in a brushing machine to simulate one year of mechanical cleansing. The specimens were tested for surface roughness with profilometer and hardness with Vickers hardness tester before and after brushing. Results were statistically analysed by two and one- way Analysis of variance (ANOVA) plus Tukey post hoc tests. Results: Specimens with type C(Remove flask from water bath, bench cool for 10min and then cool under running water for 15min)cooling procedures have high hardness values, among whichLucitone showed better properties. Surface roughness did not show significant changes among different groups. Brushing did not significantly affect surface roughness and hardness of denture base materials. Conclusion: Two of the treatments tested, Treatment C: bench-cooling for 10 min and cooling under running water for 15min and Treatment A: cooling in water-bath till room temperature provided the highest hardness values.

Effect of Hydrogen Peroxide-Based Bleaching Agents on the Color Dimensions and Surface Roughness of Different Milled Restorative Dental Materials.

To compare the color dimensions, color discrepancies (ΔE00), and surface roughness of milled materials before and after application of a bleaching agent. A total of 10 extracted molars were obtained. Each tooth was cut in transverse sections to create disks (3-mm thick, 10-mm diameter; control group). Disk specimens of eight materials (n &#61; 10 per group) were fabricated: polymethyl methacrylate (PMMA) interim material (PMMA-Telio group), two resin nanoceramics (RNC-Ultimate group and RNC-Cerasmart group), two hybrid ceramics (HC-Shofu group and HC-Enamic group), lithium disilicate (LD-Emax group), zirconia-reinforced glass ceramic (ZGC-Suprinity group), and zirconia (Zr-InCeram group). Color measurements were obtained using a spectrophotometer before and after applying 35% hydrogen peroxide-based bleaching agent. Pre- and postbleaching surface roughness (Sa) analyses were completed using a profilometer. Significant L*, a*, b*, and ΔE00 value differences were found (P < .05). Color discrepancies (ΔE00) ranged from 0.30 ± 0.14 to 4.82 ± 0.10. The highest color discrepancies were measured on the PMMA-Telio group, while the lowest color discrepancies were computed for ZGC-Suprinity, RNCUltimate, and RNC-Cerasmart. Significant surface roughness differences were found (P < .05). The largest increase of surface roughness values between the pre- and postbleaching measurements was obtained in the PMMA-Telio group with a mean ΔSa value of 4.73 ± 3.02, while the largest decrease of surface roughness values between the pre- and postbleaching measurements was obtained in the Zr-InCeram group with a mean ΔSa value of -1.58 ± 0.10. The milled materials showed significant pre- and postbleaching color and surface roughness discrepancies.

Optimization and characterization of boric acid powder mixed electrical discharge machining of Ti-6Al-4V ELI

The powder mixed electrical discharge machining (PMEDM) process is used for enhancing machining efficiency and improving the surface characteristics of the workpiece compared to normal EDM. The present study evaluates the effect of boric acid powder mixed in deionized water in PMEDM of Ti-6Al-4V ELI (extra low interstitial). The PMEDM process is assessed by evaluating material removal rate (MRR) and surface roughness (SR) at varying powder concentration (PC), current and pulse duration ( Ton). Boric acid PMEDM exhibits advantageous for both MRR and SR, where MRR increases and SR decreases with an increase in PC. To simultaneously achieve higher MRR and lower SR, the grey-fuzzy logic method is employed. Initially, the raw input data is normalized into grey numbers and a single index is obtained through grey relational analysis. Subsequently, triangular membership functions are assigned to the inputs and output. Fuzzy logic rules are then formulated, and grey fuzzy relational grade (GFRG) is calculated for each condition. The optimum condition (GFRG = 0.787) is attained at 15 g/l PC, 9 A current and 106 µs Ton, resulting in a 63% improvement compared to the initial condition. At the optimum condition, MRR increased by 145% and SR decreased by 29% compared to the initial condition. The effect of boric acid in PMEDM can be visualized through the formation of smooth surfaces, exhibiting reduced SR, smaller and shallower craters, and fewer debris and globules. Additionally, the boric acid PMEDM experiments resulted in the formation of a hard TiB phase on Ti-6Al-4V, thus improving its wear resistance.

Optimizing High-Performance Predictive Modeling of the Medium-Speed WEDM Processing of Inconel 718

The purpose of this research was to create a predictive model for a medium-speed wire electrical discharge machine (WEDM) utilizing an artificial neural network (ANN). Medium-speed WEDM experiments were developed based on the I-optimal mixture design for machining, the Inconel 718 superalloy. During the experiment, the input parameters were the spark ontime, spark offtime, wire feed, and current, with the material removal rate (MRR) and surface roughness (Ra) selected as performance indicators. The ANN model was trained on experimental data and built using a feed-forward backpropagation neural network with a (4-8-2) structure and the Bayesian regularization (BR) learning approach. The model correctly predicted the relationship between the medium-speed WEDM’s primary process parameters and machining performance. An integrated ANN model and the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) were used to determine the ideal parameters for the MRR and Ra, resulting in a set of Pareto-optimal solutions. The confirmation experiment revealed that the mean prediction error between the experimental and ideal solutions had a maximum error percentage of 1% for the MRR and 2% for the Ra, which are within acceptable ranges. This showed that the best process–parameter combinations were better for the MRR and Ra.

INVESTIGATIONS ON THE MACHINABILITY CHARACTERISTICS OF Al–Zn(5.4)–Mg(2.4)–Cu(1.4) ALLOY COMPOSITE USING TOPSIS APPROACH

In this research, stir casting was used to create the aluminium alloy (AA7075) composite filled with 10[Formula: see text]wt.% zirconia (ZrO2) particles as reinforcement. Die sinking electric discharge machining (EDM) was used to examine the machining characteristics of the proposed composite. The machining experiments were executed in accordance with the [Formula: see text] orthogonal layout. Here, the material removal rate (MRR) and surface roughness (SR) were taken into account as the output responses, and the discharge current ([Formula: see text]), pulse on-time ([Formula: see text]), and pulse off-time ([Formula: see text]) were taken as the machining parameters. To determine the optimal parameter conditions for the output responses, the technique for order preference by similarity to ideal solution (TOPSIS) approach was applied. According to the experimental findings, the optimum settings of the parameters are determined at 15[Formula: see text]amps of ‘[Formula: see text]’, 750[Formula: see text][Formula: see text]s of ‘[Formula: see text]’ and 50[Formula: see text][Formula: see text]s of ‘[Formula: see text]’. ANOVA results stated that ‘[Formula: see text]’ has the most notable factor with a contribution of 90.85%. The interaction effect of parameters on the responses was shown by the contour plots. The confirmatory experiment was finally conducted at the optimum machining parameter settings, and it was found that the error only occurred in 8.4%.

Sticky feet: a tribological study of climbing shoe rubber

This study examines the tribological properties of climbing shoe rubbers, challenging the common belief in the climbing community that softer rubbers are inherently grippier. This study investigates the mechanical and wear characteristics of climbing shoe rubbers by employing a high-precision modular mechanical testing environment (Bruker UMT TriboLab) and representative granite counter-surfaces. Key parameters, including surface roughness, Shore A hardness, interfacial adhesion, static and dynamic friction coefficients, and material wear patterns, were analyzed. The mechanical properties of each rubber compound were characterized through Shore A hardness testing and ball indentation–retraction tests, measuring indentation force, energy, and adhesive properties. Sliding friction tests, simulating real climbing conditions, were conducted to understand the tribological behavior of each rubber compound under different loads, further analyzing static and dynamic friction coefficients and wear characteristics. The findings of this study indicate that rubber performance is a convolution of several factors, including material hardness, surface roughness, and interfacial adhesion. Contrary to popular belief, softer rubbers did not consistently exhibit superior tribological characteristics. The findings of this study suggest that climbing shoe selection and design should consider a broader range of material characteristics beyond hardness, emphasizing the role of surface roughness and adhesion in determining overall frictional performance. This research offers valuable insights for the climbing community, providing methodologies to benchmark climbing rubber material characteristics.

Characterization of Wear Patterns in Gun Barrel’s Throat Region Using Forensic Microscope: Insights Into Long-Term Effects of High-Pressure Gas Exposure

Objectives: This research aims to explore the damage sustained by the gun barrel's throat region over a long period of use, shedding light on the wear characteristics, and providing valuable insights into the long-term effects of high-pressure gas exposure during firing. Methods: To achieve this objective, the appearance of the gun barrel's throat region was characterized using forensic microscopy techniques. Visual and microscopic examinations were conducted on five (5) gun barrels with ten years or less of service usage and five (5) gun barrels with over ten years of service usage from the Philippine National Police to assess the degree of wear in the barrel’s throat region. Findings: The findings revealed varying degrees of wear in the barrel throat regions. Firearms with 10 years or less of service usage exhibited moderate corrosion, narrow cracks, and minimal soot particle presence while firearms with over 10 years of service usage showed severe corrosion, deep cracks, scattered potholes, superficial scraped surfaces, and heavy soot particle presence. Novelty: This research contributes to the understanding of barrel performance, maintenance, and potential hazards associated with aging firearms, thus providing novel insights into the long-term effects of high-pressure gas exposure during firing. By examining the changes in material properties and surface roughness of the gun barrel’s throat region, this study seeks to improve the understanding of how repeated firing impacts gun barrel performance and longevity. This, in turn, may aid in developing future maintenance practices to enhance firearm durability and safety. Keywords: Gun Barrels, Wear Characteristics, Gun Barrel Throat Region, High-Pressure Gas Exposure, Wear Patterns

Evaluation of nanohardness, elastic modulus, and surface roughness of fluoride-releasing tooth colored restorative materials.

Recently, interest in tooth-colored fluoride-releasing dental materials has increased. Although physical and mechanical properties such as surface hardness, elastic modulus and surface roughness of the restorative materials have been investigated, the effect of different immersion media on these properties is still controversial. The aim of this study was to evaluate the nanohardness, elastic modulus and surface roughness of the fluoride release of tooth-colored restorative materials after immersion in acidic beverages. Prepared samples of three restorative materials (a highly viscous glass ionomer (EQUIA Forte; GC, Tokyo, Japan), a compomer (Dyract XP; Dentsply, Weybridge, UK), and a bioactive restorative material (Activa BioACTIVE; Pulpdent, MA, USA)) were randomly divided and immersed in distilled water, a cola and an orange juice for one week. The HYSITRON T1 950 TriboIndenter device (Hysitron, USA) with the Berkovich diamond indenter tip was used for all measurements. The nanohardness and elastic modulus of the samples were measured by applying a force of 6000 μN to five different points on the sample surface. Surface roughness measurements were evaluated on random samples by scanning five random 40 × 40 μm areas. The properties were measured at the initial and one week after immersion. The values of nanohardness, elastic modulus and surface roughness were tested for significant differences using a two-way analysis of variance (ANOVA) with repeated measures (p < 0.05). Tukey's honest significant difference (HSD) test was used for multiple comparisons. AB (Activa BioACTIVE) had the highest initial mean values for nanohardness. After post-immersion, the highest mean value for elastic modulus was the initial AB value. The lowest mean value for roughness of 100.36 nm was obtained for the initial DX (Dyract XP) measurement. Acidic beverages had a negative effect on the nanohardness, elastic modulus and surface roughness of the restorative materials.

Effect of machining damage on the surface roughness and flexural strength of CAD-CAM materials

Computer-aided design and computer-aided manufacturing (CAD-CAM) materials are available for different types of restorations. However, the longevity of the material is affected by chipping, milling damage, flexural strength, and surface roughness, and a standard edge chipping test or standardized measurements are unavailable for monitoring edge chipping of rotary instrument-milled materials. The purpose of this in vitro study was to analyze the surface roughness and edge chipping of different CAD-CAM diamond rotary instrument-milled dental material bars, correlate the effect of machining damage with material strength, and compare the flexural strength of rotary instrument-milled and sectioned CAD-CAM blocks. Five dental CAD-CAM materials were tested: lithium disilicate glass-ceramic (IPS e.max CAD), leucite-reinforced glass-ceramic (IPS Empress CAD); feldspathic porcelain (Vitablocs Mark II); feldspar ceramic-polymer infiltrated (Enamic), and composite resin (Lava Ultimate). Rectangular bars were designed and milled for each material (n=10). The surface roughness of the bars was measured using a profilometer. All edges of 3 selected bars were analyzed with scanning electron microscopy (SEM) for the chip length, depth, and area. The 3-point bend test was used to test the flexural strength of rotary instrument-milled and saw-cut bars with the same dimensions. Analysis of variance and the Tukey honestly significant difference post hoc test were used to determine the difference among the groups (α=.05). IPS e.max CAD had the highest surface roughness and Lava Ultimate the lowest. Lava Ultimate had the smallest chipping factor and IPS Empress CAD the largest. The surface location significantly affected the chipping depth, area, and length (P<.05). A strong correlation was found between the decrease in flexural strength and the chipping length on the central tensile side of the rotary instrument-milled materials (R2=.62, P=.01), as well as the chipping depth (R2=.44, P=.01). Edge chipping was significantly associated with the material type, milling surface, and edge location and strongly correlated with a decrease in flexural strength.

In vitro evaluation of the effect of two pediatric syrups on the microhardness and surface roughness of restoration materials.

The prolonged use of pediatric syrups without adequate control of oral hygiene can cause effects on the physical characteristics of the restoration materials, which in turn can cause deterioration of the material and subsequent carious recurrence. Aim: To evaluate the effect of two long-term use syrups in children on the microhardness and surface roughness of three restorative materials. Three study groups were formed, consisting of a conventional self-curing ionomer cement, a light-curing ionomer cement, and a light-curing composite resin. Each group had 40 specimens made with the respective restorative material; in addition, these were distributed in 2 subgroups with 20 specimens each, which were immersed in Paracetamol and Ferrous Sulfate in syrup following a protocol that consisted of 2 minutes each day for 28 days. Over time (0, 7, 14, 21, and 28 days), when evaluating microhardness, the composite resin subgroup exposed to ferrous sulfate (p = 0.027) and the Ketac Molar ionomeric cement subgroup (p = 0.002) exposed to Paracetamol showed statistically significant differences; while, when evaluating surface roughness, the composite resin subgroups (p = 0.032) and Ketac Molar ionomeric cement (p = 0.01) exposed to ferrous sulfate showed a statistically significant difference. The more days of exposure to ferrous sulphate syrup, the less the microhardness of the composite resin decreases; something similar occurs with the microhardness of Ketac Molar ionomeric cement when exposed to Paracetamol syrup. Meanwhile, the surface roughness of the composite resin and Ketac Molar ionomeric cement increases considerably when exposed to ferrous sulphate. Key words:Ionomeric cement, Microhardness, Composite resins, Surface roughness.

An experimental study on material removal rate and surface roughness of Cu-Al-Mn ternary shape memory alloys using CNC end milling

Abstract This study investigates the impact of Computer Numerical Control (CNC) milling parameters on Cu-Al-Mn SMAs (Shape memory alloys) to evaluate the effects on Surface Roughness (SR) and Material Removal Rate (MRR). The primary variables examined comprise of cutting speed, feed rate, and depth of cut. Results indicate that the Shape Memory Effect (SME) is higher in Copper Aluminium Manganese (CAM 3) compared to CAM 1 and CAM 2, with SME improving from 3.5% to 5.5% as Manganese (Mn) content increases, reflecting an increase in dislocations within the metal's crystal structure. Surface roughness increases with higher feed rates and depths of cut but decreases with increased cutting speed. MRR shows a positive correlation with feed rate, depth of cut, and cutting speed, though it decreases with higher Mn content. Notably, CAM 3 exhibits lower MRR compared to CAM 1 and CAM 2. Scanning Electron Microscopy (SEM) reveals that at lower feed rates (0.10 mm/rev), the surface is smooth and free of ridges or feed marks, while at higher feed rates (0.18 mm/rev), noticeable surface imperfections and plastic deformation occur. The addition of Mn improves surface smoothness and machinability, it also affects MRR. Further suggesting that Mn content and milling parameters significantly influence both the mechanical properties and machinability of Cu-Al-Mn SMAs respectively.

Exploring the impact of epoxy coated 3D-Printed polymers on surface roughness and mechanical behavior: An experimental and numerical study

The present study used polymers such as PLA and ABS filaments for the 3D printing parts with varying layer thicknesses. The mechanical properties and surface finish of the as-printed and epoxy resin-coated samples were investigated. Noteworthy findings indicate that when the PLA material is printed at a layer thickness of 0.06 mm followed by no coating one can achieve superior tensile strength of approximately 39 MPa as compared to 20 MPa of ABS material. The ultimate tensile strength of the coated materials averaged approximately 15 MPa for both PLA and ABS. The surface roughness of PLA material printed with a 0.06 mm layer thickness showed a 95.13 % reduction after coating. Despite ABS samples being harder than PLA material, the layer thickness emerged as the most influential factor in enhancing the hardness. The dominance of lower layer thickness over other conditions is particularly evident in the modulus of elasticity. In addition to the experimental investigation, a non-linear structural analysis of the uniaxial tensile behaviour of the coated and uncoated 3D prints was also carried out. The fracture modes and deformation behaviours in numerical modelling and experimental results across various parametric conditions were found to be in good agreement. Specifically, the numerical results at lower loading conditions for a layer thickness of 0.06 mm PLA and ABS samples, in the uncoated conditions, mirrored the experimental outcomes.

Role of spark energy and frequency on wire-EDM performances of Al-2Mg alloy and Al-2Mg/20 Al3Fe composite: a comparative study

ABSTRACT The performance of wire-electric discharge machining (WEDM) method is inevitably affected by the electric spark. A comparative study is presented related to the influences of spark energy (SE, 1.68–8.40 mJ) and spark frequency (SF, 12.82–15.15 kHz) on machining responses of Al-2Mg/20 vol.% in-situ Al3Fe composite with respect to Al-2Mg alloy. Such comparison is scanty in the literature. Machining performances were measured concerning material removal rate (MRR), cutting speed (CS), and surface roughness (SR) apart from the morphological evolution of machined surfaces. Irrespective of machining condition (for instance, at SE of 5.04 mJ), composite exhibited lower CS (1.27 mm/min), MRR (4.20 mm3/min), and SR (4.42 µm) due to the insulating effect of reinforcement than alloy (i.e. 1.70 mm/min, 5.81 mm3/min, and 4.82 µm, respectively). For both alloy and composite, all three machining performances increased linearly with rising the SE and SF, although the influence of SE was more pronounced over SF. With increasing SE, the difference in the magnitudes of CS and MRR between alloy and composite widened, while the same for SR narrowed. Formations of micro-cracks, lumps of debris, craters, and re-solidified layers were observed more on alloy machining surface than composite; these features enlarged with increasing SE and SF.

AirTac: A Contactless Digital Tactile Receptor for Detecting Material and Roughness via Terahertz Sensing

Tactile sensing is an indispensable capability for humans or intelligent devices to engage in complex physical interactions. Mainstream tactile sensors are contact-based, which show limitation in measuring deformable objects and demanding high maintenance effort. As a complementary solution, a new paradigm of contactless tactile sensing is attracting much interest. While promising, they can only identify coarse-grained single tactile perception properties, either material type or surface roughness. In this paper, we propose airTac, which includes a novel contactless digital tactile receptor model, capable of simultaneously extracting these two basic tactile properties in a fine-grained resolution, by harnessing the massive bandwidth of terahertz(THz) frequency band. airTac is designed based on our key finding: while the impact of material type and surface roughness on THz signal intertwine with each other, they are actually separable, i.e., roughness manifests a certain pattern in distorting relative high-frequency components of the whole THz spectrum. Therefore, we custom-design a bio-inspired deep neural network model to decouple the intertwined THz signal, and distill the tactile perception properties embedded underlying the signal. We prototype airTac using a THz time domain spectroscopy, and perform extensive evaluation over 9 different daily material types with 39 different surface roughness. airTac achieves a material identification accuracy of 97.43% and a roughness classification accuracy of 91.46%, which demonstrates that airTac can identify common materials in daily life and exceed a fingertip spatial resolution of 1mm.

Investigation of process parameters for modeling of ceramic composite SiSiC IN dry EDM (DEDM) cutting

The manufacturing industry is currently grappling with issues related to energy dissipation and product quality, both of which significantly impact productivity. In addressing this pertinent concern, this study endeavours to identify the key indicators that contribute a crucial role in machining process. The Dry EDM (DEDM) emerges as a novel technology, wherein environmentally friendly gases serve as an alternative dielectric medium instead of liquid EDM approaches. In conventional EDM process, hydrocarbon oils release toxic emissions while the gases used in Dry EDM process don’t produce harmful emissions and hence make the DEDM process sustainable.An investigation has been carried out to observe the influence of different gases like O2, N2 and Air on Siliconized Silicon-Carbide plate (SiSiC) of ø50mm*2 mm under Dry Electrical Discharge Machining. Effect of different tools is also observed using varying shapes of electrodes like plane Cu electrode of ø6 mm diameter with 60 mm length and tubular shape with outer diameter ø6mm and inner diameter ø5.1 mm with a length of 60 mm. The three gases are one by one supplied through a nozzle in the presence of plane Cu electrode to make the holes in SiSiC plate. The same process is executed with tubular Cu electrode. Modified Taguchi Orthogonal Array is applied to analyze the effect of control factors such as gap voltage, discharge current and pulse on-time through a series of experiments. Effect of different shape of tools and different gases is observed for the material removal rate (MRR) and surface roughness (SR) of specimen.In this paper, a latest DEDM process of swirl assisted flushing is proposed which provides a new technique to solve the problems of low MRR and poor surface integrity. Swirl assisted flushing works on Decay Law and also microscopic investigation justifies its validity. It is concluded by this research that current and Pulse on time are more contributing factors about 53.3 % and 27 % respectively. Furthermore, it is noted that DEDM increases MRR 19.5 % and lowers Ra approximately 2/3 than traditional machining. The MRR of O2 is about 3.1 times more than Air and N2 comes at least position while N2 creates better quality of surface due to formation of an inert nitride layer. Empirical relations are established for SR and MRR using Minitab 18 Software to develop a robust model. Confirmation test is performed to check the validity of developed mathematical model. The Novelty of this research is also extended by introducing a new method SAF. The results are finally evaluated by ANOVA.

Effect of Different Finishing Systems on Surface Roughness and Gloss of a 3D-Printed Material for Permanent Dental Use

The object of the study was to assess the effect of different finishing and polishing systems on the roughness and gloss of a 3D-printed permanent restorative material. One 3D printable Permanent material was selected for the study. Squared-shaped specimens (14 mm2; 5 mm thickness) were obtained by designing and printing. Eighty specimens were produced and randomly assigned (n = 10) to 8 finishing and polishing methods: Sof-Lex™ Spiral Wheels (SW), Sof-Lex™ XT Pop-on Disc (SD), Identoflex Lucent no paste (Ln), Identoflex Lucent + paste (Lp), Resin Nitrogen polymerized (NG), Optiglaze (OG), Opti1Step (OS), and HiLusterPLUS (HL). Surface roughness and gloss were then measured by a roughness meter and a glossmeter, respectively. For roughness, statistically significant differences were found (p &lt; 0.001), with NG(a) &gt; SD(b) = OG(b) = Lp(b); Lp(b) = Ln(bc); Ln(bc) = OS(cd); OS(cd) = SW(de); and SW(de) = HL(e). For gloss, statistically significant differences were also identified (p &lt; 0.001) with NG(a) &gt; SD(b) &gt; Lp(c) = OS(c) = OG(cd); OG(cd) = Ln(d) &gt; HL(e) = SW(e). The nitrogen chamber polymerization showed better results for both roughness and gloss. Multi-step finishing/polishing systems were able to produce smoother surfaces than 1-step and 2-step systems.

Investigating micro-EDM machinability of Ti-35Nb-7Zr-5Ta (TNZT) alloy

ABSTRACT Titanium and its new-generation alloys are widely employed in high-end applications due to their special properties. Modern industries frequently use micro – Electro Discharge Machining (μ-EDM), a non-conventional machining technique that is especially useful for processing hard to machine materials like titanium alloys. μ-EDM can produce intricate shapes with excellent dimensional precision. The main emphasis of this work is an experimental analysis of the μ-EDM of TNZT alloy (Ti-35Nb-7Zr-5Ta) employing a tungsten carbide (WC) electrode. The results showed that with the increase in capacitance (C) 10nF to 100nF at Voltage (V) 80 V, the machining performance parameters such as material removal rate (MRR), overcut (OC), crater area, surface microhardness, and surface roughness increase by 6.38, 1.52, 4.66, 1.07, and 3.29 times, respectively. However, the circularity error of the µ-hole increases by 1.81 times. This study intends to show how the two key machining factors (C & V) influence significant machining performance parameters.

Electromagnetic wave scattering simulation from precision grinding SiC surface under the influence of suspended micro-particles

ABSTRACT In a precision machining environment, suspended particles in the air have a non-negligible effect on visual roughness measurement results. To address this issue, this paper analyzes the influence of particles on the visual roughness measurement from theoretical derivation and numerical simulation, respectively. Firstly, based on the Lambert-Beer and the light scattering principles, the propagation equation of incident light under the joint action of suspended particles and rough surfaces is derived. Then, a numerical simulation model is designed, and the theoretical equations are verified by simulation experiments. The influence of particle material, particle size (D), particle concentration (N), light wavelength (λ), and SiC surface roughness (R a ) on the average electric field magnitude of the energy-acquisition boundary are analysed based on the simulation experiments. The theoretical derivation shows that the average electric field magnitude of the energy-acquisition boundary is mainly influenced by particle state and rough surface state. The simulation experiment results show that both the particle parameters and the rough surface parameters are consistent with the theoretical derivation. As R a increases, the effect of N on the measurement results decreases. The results reveal the influence mechanism of suspended particles on the visual roughness measurement results and provide a basis for improving visual roughness measurement accuracy.

Influence of Textile Substrates on the Adhesion of PJM-Printed MED610 and Surface Morphology

The idea of 3D printing on textile fabrics was first mentioned around 10 years ago and has been investigated in detail since. Originally aimed at opening new design possibilities, combining 3D printing with textile substrates has shifted towards a new method to prepare composites with defined mechanical and other physical properties. The main problem of fused deposition modelling (FDM; also referred to as material extrusion (MEX) according to ISO/ASTM 52900) is printing on textile fabrics, where the frequently insufficient adhesion between both materials has not been fully resolved. For this reason, a few attempts have been made to combine other additive manufacturing methods with textile fabrics. While the principle possibility of using stereolithography (SLA) on textile fabrics was demonstrated a few years ago, PolyJet modelling (PJM) has only recently proven to be applicable for direct printing on textile materials. Here, we present the first study of printing MED610 medical resin on different fabrics. We show that a higher textile fabric surface roughness generally increases the adhesion of the printed material, while a higher hydrophobicity is disadvantageous. We also tested the influence of textile substrates on the porosity of the MED610 surface, as this parameter can influence a material’s potential use in tissue engineering and other biomedical applications.

Effects of current intensities on material removal rate, electrode wear rate, and surface roughness of machining high carbon high chromium steel

AbstractThe electrical discharge machining is very successful and generally recognized for producing complicated shapes and small openings with exceptional precision. The objective of this study is to assess the impact of different electrical discharge machining parameters on the attributes of the machining process. The evaluation of the machining process was conducted based on the workpiece‘s material removal rate, the rate at which the electrodes wear, and the level of surface roughness. Simultaneously achieving a high material removal rate, low electrode wear rate, and high surface roughness is not possible with a specific combination of approaches due to their contradicting nature. Frequently, it is necessary to independently apply many measures instantaneously in order to assess their impact on various responses. This research investigates the machining of high carbon high chromium steel making use of electrical discharge machining with aluminum, copper, and graphite electrodes. The study focuses on the impact of different current intensities on the rate of material removal, electrode wear, and surface roughness. The experimental results demonstrate that the highest material removal rate (mmcubicmin−1) is achieved at a current density of 12 A when using a copper electrode (54.67), as opposed to aluminum electrode (22.91) and graphite electrode (29.43).