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Öğe Abrasive Wear Behavior of Nano-Sized Steel Scale on Soft CuZn35Ni2 Material(Springer, 2023) Demirsoz, Recep; Ugur, Abdullah; Erdogdu, Ahmet Emrah; Korkmaz, Mehmet Erdi; Gupta, Munish KumarThis study examines the abrasive wear behavior of nano-sized steel scale on the CuZn35Ni2 Soft material. CuZn35Ni2 Soft material was used as a sample, and the three-body wear mechanism formed by nanoscale particles mixed with lubricating oil was investigated using a ball-on-flat tester. Three different loads, three different sliding speeds and three different environment variables were used in the experiments. A lubricant containing 0.15 and 0.3 wt.% nanoscale and a non-abrasive lubricant was used to form the medium. The experimental results were obtained as mass loss, wear depth and friction coefficient and the wear surfaces were examined using scanning electron microscopy/energy-dispersive x-ray spectroscopy (SEM/EDX). The analysis of variance method was used to determine the effect of independent variables on the results. As a result of the study, it was concluded that the most effective parameter for mass loss and CoF was the environment, and the most effective parameter for the depth of wear was the load. It was concluded that there might be a difference of up to 10% in the coefficient of friction between the experiments and the predicted values. Still, in general, the predicted values and the experimental results agree.Öğe Analytical Modeling Methods in Machining: A State of the Art on Application, Recent Challenges, and Future Trends(Springer Heidelberg, 2024) Korkmaz, Mehmet Erdi; Gupta, Munish Kumar; Sarikaya, Murat; Gunay, Mustafa; Boy, Mehmet; Yasar, Nafiz; Demirsoz, RecepInformation technology applications are crucial to the proper utilization of manufacturing equipment in the new industrial age, i.e., Industry 4.0. There are certain fundamental conditions that users must meet to adapt the manufacturing processes to Industry 4.0. For this, as in the past, there is a major need for modeling and simulation tools in this industrial age. In the creation of industry-driven predictive models for machining processes, substantial progress has recently been made. This paper includes a comprehensive review of predictive performance models for machining (particularly analytical models), as well as a list of existing models' strengths and drawbacks. It contains a review of available modeling tools, as well as their usability and/or limits in the monitoring of industrial machining operations. The goal of process models is to forecast principal variables such as stress, strain, force, and temperature. These factors, however, should be connected to performance outcomes, i.e., product quality and manufacturing efficiency, to be valuable to the industry (dimensional accuracy, surface quality, surface integrity, tool life, energy consumption, etc.). Industry adoption of cutting models depends on a model's ability to make this connection and predict the performance of process outputs. Therefore, this review article organizes and summarizes a variety of critical research themes connected to well-established analytical models for machining processes.Öğe Effect of Impact Angle and Speed, and Weight Abrasive Concentration on AISI 1015 and 304 Steel Exposed to Erosive Wear(Springer, 2024) Gul, M. Salih; Demirsoz, Recep; Kilincarslan, Sena Kabave; Polat, Refik; Cetin, M. HuseyinThis study investigated parametrically the erosive wear behavior of AISI 1015 and 304 steel in different environmental conditions. The erosive wear tests were designed according to the L9 orthogonal array design of the Taguchi fractional factorial method. The experiments were carried out with the parameters of 3-level slurry concentration formed with silica powder (5, 15, and 25 wt.%), 3-level impact velocity (265, 397.5, and 530 rpm), and 3-level impact angle (30 degrees, 60 degrees, and 90 degrees). Surface roughness and weight loss were considered performance criteria in the experimental data assessed using the signal/noise (S/N) and analysis of variance (ANOVA) methodologies. In addition, the wear zones of the samples were examined in detail with SEM, EDX, and 3D topography analyses. According to the S/N analysis, the best wear and surface roughness parameters for AISI 1015 and 304 steel were determined as 5% by weight concentration ratio, 265 rpm for impact speed, and 90 degrees for impact angle. It was determined that low concentration, low speed, and high impact angle values affected surface roughness and weight loss parameters positively. Experimental results showed that erosive wear resistance increased with the increasing alloying elements in steel materials.Öğe Erosion characteristics on surface texture of additively manufactured AlSi10Mg alloy in SiO2 quartz added slurry environment(Emerald Group Publishing Ltd, 2022) Demirsoz, Recep; Korkmaz, Mehmet Erdl; Gupta, Munish Kumar; Collado, Alberto Garcia; Krolczyk, Grzegorz M.Purpose The main purpose of this work is to explore the erosion wear characteristics of additively manufactured aluminium alloy. Additive manufacturing (AM), also known as three-dimensional (3D) manufacturing, is the process of manufacturing a part designed in a computer environment using different types of materials such as plastic, ceramic, metal or composite. Similar to other materials, aluminum alloys are also exposed to various wear types during operation. Production efficiency needs to be aware of its reactions to wearing mechanisms. Design/methodology/approach In this study, quartz sands (SiO2) assisted with oxide ceramics were used in the slurry erosion test setup and its abrasiveness on the AlSi10Mg aluminum alloy material produced by the 3D printer as selective laser melting (SLM) technology was investigated. Quartz was sieved with an average particle size of 302.5 mu m, and a slurry environment containing 5, 10 and 15% quartz by weight was prepared. The experiments were carried out at the velocity of 1.88 (250 rpm), 3.76 (500 rpm) and 5.64 m/s (750 rpm) and the impact angles 15, 45 and 75 degrees. Findings With these experimental studies, it has been determined that the abrasiveness of quartz sand prepared in certain particle sizes is directly related to the particle concentration and particle speed, and that the wear increases with the increase of the concentration and rotational speed. Also, the variation of weight loss and surface roughness of the alloy was investigated after different wear conditions. Surface roughness values at 750 rpm speed, 10% concentration and 75 degrees impingement angle are 0.32 and 0.38 mu m for 0 and 90 degrees samples, respectively, with a difference of approximately 18%. Moreover, concerning a sample produced at 0 degrees, the weight loss at 250 rpm at 10% concentration and 45 degrees particle impact angle is 32.8 mg, while the weight loss at 500 rpm 44.4 mg, and weight loss at 750 rpm is 104 mg. Besides, the morphological structures of eroded surfaces were examined using the scanning electron microscope to understand the wear mechanisms. Originality/value The researchers verified that this specific coating condition increases the slurry wear resistance of the mentioned steel. There are many studies about slurry wear tests; however, there is no study in the literature about the quartz sand (SiO2) assisted slurry-erosive wear of AlSi10Mg alloy produced with AM by using SLM technology. This study is needed to fill this gap in the literature and to examine the erosive wear capability of this current material in different environments. The novelty of the study is the use of SiO2 quartz sands assisted by oxide ceramics in different concentrations for the slurry erosion test setup and the investigations on erosive wear resistance of AlSi10Mg alloy manufactured by AM.Öğe Evaluation of the Mechanical Properties and Drilling of Glass Bead/Fiber-Reinforced Polyamide 66 (PA66)-Based Hybrid Polymer Composites(Mdpi, 2022) Demirsoz, Recep; Yasar, Nafiz; Korkmaz, Mehmet Erdi; Gunay, Mustafa; Giasin, Khaled; Pimenov, Danil Yurievich; Aamir, MuhammadIn this study, mechanical testing of glass bead (GB), glass fiber (GF), and hybrid (GB/GF) composites was carried out. Following that, drilling tests were undertaken on glass bead/fiber-reinforced hybrid Polyamide 66 (PA66) polymer composites. The purpose of this study is to determine the mechanical properties of the cutting elements and the effect of cutting parameters (spindle speed and feed rate) and reinforcement ratios on thrust force and surface roughness (Ra). The contribution of the cutting parameters to the investigated outcomes was determined using statistical analysis. Optical microscopy and scanning electron microscopy (SEM) was used to inspect the hole quality and damage mechanisms. The results revealed that the feed rate was the most contributing factor to thrust force (96.94%) and surface roughness (63.59%). Furthermore, in comparison to other hybrid composites, the lowest R-a value was obtained as 0.95 mu m in samples containing 30% GB, while the R-a value was 1.04 mu m in samples containing 10% GF + 20% GB. Polymer PA reinforced with 30% GF had the highest strength, modulus of elasticity, impact strength, and hardness.Öğe Investigation of erosive wear behavior of granulated blast furnace slag on hard coated and uncoated steels(Gazi Univ, Fac Engineering Architecture, 2019) Demirsoz, Recep; Polat, Refik; Turk, Ahmet; Erdogan, GaripOne of the biggest problems in industrial plants is wear that directly affects equipment life. In integrated plants such as blast furnaces, many types of wear are encountered, one of which is erosive wear. Slurry erosion is one of the effective types of erosive wear. During the transfer of the slag into the liquid medium, the transport equipment is exposed to slurry erosion. The high amount of erosion seriously shortens the life of the equipment where the transportation is carried out and increases the maintenance-repair costs. In this study, blast furnace slag was used in the slurry erosive wear test system and the abrasivity of the St 37-2 reference standard pipe material, Hardox 400 and W2C-NiCrBSi coating materials was investigated. The slag was sieved to an average particle size of 505 mu m and slurry containing 10%, 20% and 30% by weight of slag was prepared. The experiments were carried out at 2 m/s and 4 m/s peripheral speed values at the partical normal impact angle (90 degrees). It has been determined by these experimental studies that the abrasivity of the slag prepared at a certain grain size is directly related to the concentration and the rotation speed (material conveyance speed) and that the wear is also increased by increasing the concentration and rotation speed. The wear values of the materials used as specimens are determined from high to low respectively as St 37-2, Hardox 400 and W2C-NiCrBSi coating material. In addition, the morphological structures of the worn surfaces were examined using SEM(Scanning Electron Microscope) in order to understand the wear mechanisms.Öğe Machine learning models for online detection of wear and friction behaviour of biomedical graded stainless steel 316L under lubricating conditions(Springer London Ltd, 2023) Korkmaz, Mehmet Erdi; Gupta, Munish Kumar; Singh, Gurminder; Kuntoglu, Mustafa; Patange, Abhishek; Demirsoz, Recep; Ross, Nimel SwornaParticularly in sectors where mechanisation is increasing, there has been persistent effort to maximise the use of existing assets. Since maintenance management is accountable for the accessibility of assets, it stands to acquire prominence in this setting. One of the most common methods for keeping equipment in good working order is predictive maintenance with machine learning methods. Failures can be spotted before they cause any downtime or extra expenses, and with this aim, the present work deals with the online detection of wear and friction characteristics of stainless steel 316L under lubricating conditions with machine learning models. Wear rate and friction forces were taken into account as reaction parameters, and biomedical-graded stainless steel 316L was chosen as the work material. With more testing, the J48 method's accuracy improves to 100% in low wear conditions and 99.27% in heavy wear situations. In addition, the graphic showed the accuracy values for several models. The J48 model is the most precise amongst all others, with a value of 100% (minimum wear) and an average of 98.92% (higher wear). Amongst all the models tested under varying machining conditions, the J48's 98.92% (low wear) and 98.92% (high wear) recall scores stand out as very impressive (higher wear). In terms of F1-score, J48 performs better than any competing model at 99.45% (low wear) and 98.92% (higher wear). As a result, the J48 improves the model's overall performance.Öğe A novel use of hybrid Cryo-MQL system in improving the tribological characteristics of additively manufactured 316 stainless steel against 100 Cr6 alloy(Elsevier Sci Ltd, 2022) Demirsoz, Recep; Korkmaz, Mehmet Erdi; Gupta, Munish KumarReflecting the broad interest in additive manufacturing (AM), this study focuses on the tribological behavior of 316 L stainless steel against 100 Cr6 alloy under various cooling environments. Tribological experiments were conducted on additively manufactured 316 stainless steel using a ball-on-flat tribometer under dry, minimum quantity lubrication (MQL), cryogenic, and hybrid cryo+MQL conditions. Subsequently, the most critical tribological variables such as friction forces, volume loss, wear depth, and micrographs were investigated. The results revealed that the combination of cryo and MQL cooling conditions are helpful in improving the tribological performance while minimizing material volume loss and wear rates. Cryo+MQL condition shows better performance based on volume loss as 2.33, 11.2 and 14.8 times than MQL, cryo and dry conditions, respectively.Öğe On tribological characteristics of TiC rollers machined under hybrid lubrication/cooling conditions(Elsevier Sci Ltd, 2022) Korkmaz, Mehmet Erdi; Gupta, Munish Kumar; Demirsoz, Recep; Boy, Mehmet; Yasar, Nafiz; Gunay, Mustafa; Ross, Nimel SwornaThe titanium carbide is considered as a hard to cut material and it is very helpful in critical applications especially in guide roller applications. This study investigated the machining based tribological characteristics of TiC rollers during hard turning under sustainable cooling/lubrication conditions. Surface quality, power consumption, tool wear, microstructural changes, microhardness after machining, and SEM-EDX analysis were evaluated under dry, minimum quantity lubrication (MQL), cryogenic and hybrid cryo+MQL environments. Although the surface quality did not meet the expectations in dry cutting, MQL improved slightly than cryo methods. However, the best surface quality, the smallest tool wear and power consumption was obtained in the hybrid cryo+MQL lubrication/cooling method.Öğe Parallel structure of crayfish optimization with arithmetic optimization for classifying the friction behaviour of Ti-6Al-4V alloy for complex machinery applications(Elsevier, 2024) Chauhan, Sumika; Vashishtha, Govind; Gupta, Munish Kumar; Korkmaz, Mehmet Erdi; Demirsoz, Recep; Noman, Khandaker; Kolesnyk, VitaliiIntelligent techniques play a vital role in predicting the friction force during the wear of Ti-6Al-4V alloy under different lubricating conditions. The effective assessment of friction forces and lubricating conditions allows for the replacement of the material before catastrophic failure. However, it remains challenging to utilise friction forces under different lubrication conditions to predict the wear through intelligent techniques. In this work, an advanced technique based on artificial intelligence has been proposed to address this issue. Intially parallel structure of crayfish optimization and arithmetic optimization algorithm (PSCOAAOA) is developed to duly address the issues of slow convergence, stucking in local optima and quality of the solution. The PSCOAAOA is further implemented for finding the optimal parameters (regularization parameter and kernel function) of the Support Vector Machine (SVM). The quantitative and qualitative analysis of PSCOAAOA is carried out on CEC2014 benchmark functions to validate its efficacy and robustness. The friction force generated during wear testing under different lubricating conditions is bifurcated into training and test data. Out of which, training data trains the SVM at an optimal combination of parameters. The overall accuracy of the built SVM model is found to be 95.85% with a computation time of 26.85 s.Öğe Performance of MQL and Nano-MQL Lubrication in Machining ER7 Steel for Train Wheel Applications(Mdpi, 2022) Camli, Kerem Yavuz; Demirsoz, Recep; Boy, Mehmet; Korkmaz, Mehmet Erdi; Yasar, Nafiz; Giasin, Khaled; Pimenov, Danil YurievichIn the rail industry, there are four types of steel grades used for monoblock wheels, namely ER6, ER7, ER8 and ER9. ER7 steel is manufactured in accordance with the EN13262 standard and is utilized in European railway lines. These train wheels are formed by pressing and rolling after which they are machined using turning process to achieve their final dimensions. However, machining ER7 steels can be challenging due to their high mechanical properties, which can facilitate rapid tool wear and thermal cracking. Therefore, while the use of coolants is critical to improving their machinability, using conventional flood coolants adds extra operational costs, energy and waste. An alternative is to use minimum quantity lubrication (MQL) cooling technology, which applies small amounts of coolant mixed with air to the cutting zone, leaving a near-dry machined surface. In the current study, preliminary tests were undertaken under dry conditions and using coated carbide inserts to determine the optimal cutting parameters for machining ER7 steel. The impact of the cutting speed and feed rate on surface roughness (R-a), energy consumption and cutting temperature were investigated and used as a benchmark to determine the optimal cutting parameters. Next, additional machining tests were conducted using MQL and nano-MQL cooling technologies to determine their impact on the aforementioned machining outputs. According to preliminary tests, and within the tested range of the cutting parameters, using a cutting speed of 300 m/min and a feed rate of 0.15 mm/rev resulted in minimal surface roughness. As a result, using these optimal cutting parameters with MQL and Nano-MQL (NMQL) cooling technologies, the surface roughness was further reduced by 24% and 34%, respectively, in comparison to dry conditions. Additionally, tool wear was reduced by 34.1% and 37.6%, respectively. The overall results from this study demonstrated the feasibility of using MQL coolants as a sustainable machining alternative for steel parts for rail wheel applications. In addition, the current study highlight the enhanced performance of MQL cooling technology with the addition of nano additives.Öğe Studies on energy consumption and other important machining characteristics in sustainable turning of EA1N railway axle steel(Springer London Ltd, 2024) Dincsoy, Mehmet; Korkmaz, Mehmet Erdi; Gupta, Munish Kumar; Ozdemir, Mehmet Tayyip; Gunay, Mustafa; Demirsoz, RecepThe present research focuses on comprehensively evaluating energy consumption and other vital machining characteristics during the turning process, aiming to optimize efficiency while minimizing environmental impact. The experimental data is collected through a series of machining tests on EA1N railway axle steel under dry, minimum quantity lubrication (MQL), and cryogenic cooling conditions. Under these cutting conditions, the machinability criteria (energy consumption, tool wear, surface quality, chip morphology) of train wheel axle steel were tried to be improved. As a result, cryogenic cooling at constant cutting speed gave 40% and 53% better results in terms of energy consumption than MQL and dry environment, respectively. When the same situation was examined in terms of tool wear and surface quality, 10-18% and 8-14% gave better results, respectively. In other words, it is worthy to mention that the research findings not only benefit the manufacturing industry by optimizing resource utilization but also align with global efforts to promote environmentally conscious practices in the engineering and transportation sectors.Öğe Studies on newly developed hBN/graphene-based nano-fluids supported by cryogenic cooling conditions in improving the tribological performance of Ti6Al4V alloy(Elsevier, 2024) Korkmaz, Mehmet Erdi; Rai, Ritu; Demirsoz, Recep; Picak, Sezer; Vashishtha, Govind; Gunay, MustafaHexagonal Boron Nitride (hBN) is often referred to as a soft material due to its layered structure and properties that distinguish it from conventional hard materials like ceramics. The layered structure of hBN imparts lamellar lubrication characteristics and the weak van der Waals forces between adjacent layers allow for easy sliding, leading to low frictional resistance. The softness of hBN allows for ease of processing into various forms, facilitating its incorporation into lubricants, coatings, and composite materials. Therefore, the aim of this work is to enhance the lubricating capabilities of the nano-fluids and optimize the frictional behavior of Ti6Al4V alloy against tungsten carbide (WC) abrasive ball for potential biomedical applications, especially for combination of Ti6Al4V femoral stem and carbide femoral head. The newly formulated nano-fluids combine the unique properties of hBN and graphene to create a synergistic lubricating environment. The tribology and advanced characterization techniques were used to analyze the wear behavior of Ti6Al4V alloy surfaces. The results demonstrated that the applciaiton of cryogenically cooled lubricants with nanoparticles exhibited the lowest wear depth and friction forces, as a result of their increased viscosity.Öğe A study on friction induced tribological characteristics of steel 316 L against 100 cr6 alloy under different lubricating conditions with machine learning model(Elsevier Sci Ltd, 2024) Gupta, Munish Kumar; Korkmaz, Mehmet Erdi; Karolczuk, Aleksander; Ross, Nimel Sworna; Vashishtha, Govind; Krolczyk, Jolanta B.; Demirsoz, RecepThe material steadily wears away from touching surfaces when two solid entities are constantly moving against one other. When more parameters and extreme materials are involved in tribological testing, then it is very difficult to analyze and observe the working phenomena. With this aim, this study uses the gaussian process regression (GPR) approach to estimate friction forces when testing SS 316 L against 100 Cr6 alloy under cryogenic and cryo + minimum amount lubrication conditions. The friction forces from ball -on test experiments were used to develop the prediction models. Then, the wear surfaces and surface morphology are analyzed under cryo and cryo +MQL conditions. The results demonstrated that the combination of MQL and CRYO cooling reduced the friction forces more than 10 times for sliding distances above -30 m and loads below -25 n. Hence, the cryo +MQL conditions are beneficial in enhancing the tribological features due to the dual cooling and lubricating effects.Öğe Tribological characteristics of additively manufactured 316 stainless steel against 100 cr6 alloy using deep learning(Elsevier Sci Ltd, 2023) Gupta, Munish Kumar; Korkmaz, Mehmet Erdi; Shibi, C. Sherin; Ross, Nimel Sworna; Singh, Gurminder; Demirsoz, Recep; Jamil, MuhammadUnder different working conditions, the tribological characteristics of materials show a complicated and nonlinear relation. As a result, it is crucial to advance tribology by prioritising a data-driven strategy to estimate service capability in order to expedite the material design and preparation. With this aim, the present work firstly deals with the implementation of novel deep learning technologies in predicting tribological characteristics of additively manufactured and casted 316 stainless steel against 100 cr6 alloy. The coefficient of friction and frictional forces data from ball-on-flat experiments were used to develop the different deep learning models i.e., CNN, CNN-LSTM, and ATTENTION based CNN. Then, the wear tracks of tested samples were analysed with the SEM analysis. According to the findings of the wear rate, the AM material wears with an average of 58% less intensity than the casted material. In addition, the performance of the CNN Attention model demonstrated higher levels of accuracy and lower loss metrics in comparison to the CNN and CNN-LSTM classifiers.Öğe Understanding the lubrication regime phenomenon and its influence on tribological characteristics of additively manufactured 316 Steel under novel lubrication environment(Elsevier Sci Ltd, 2022) Korkmaz, Mehmet Erdi; Gupta, Munish Kumar; Demirsoz, RecepThe degree of surface separation is generally used to determine the lubrication regimes. The smooth functioning of components are possible by providing the lubrication at intermediate zone, which reduces the wear and prevents severe stresses or bearing arrests. This work is also focus on lubrication regime phenomena and its influence on tribological characteristics of additively manufactured 316 steel under novel lubrication environment. The tribology tests were performed on ball-on flat machine under dry, minimum quantity lubrication (MQL), cryogenic and hybrid cryo+MQL conditions. The 100Cr6 ball has been used against additively manufactured 316 steel and the theoretical exploration of lubrication regimes has been discussed along with other tribological characteristics such as wear rate, surface roughness and coefficient of friction etc. The outcome demonstrated that the hybrid cryo+MQL is helpful in providing the good lubrication film and consequently improves the tribological properties.Öğe Understanding the slurry erosion behaviour of iron-based chromium carbide coating material during deposition via arc spray coating method(Sage Publications Ltd, 2023) Demirsoz, Recep; Singla, Anil Kumar; Ugur, Abdullah; Erdogdu, Ahmet Emrah; Korkmaz, Mehmet Erdi; Gupta, Munish Kumar; Krolczyk, Jolanta BeataThe material S235JR was spray-coated with iron-based chromium carbide in the present study. The effects of the initial surface roughness on slurry erosion were investigated. Samples with a rough surface and polished surface were used. The impact of particle concentration, impact velocity and impact angle was studied on the slurry erosion characteristics in terms of mass loss, surface roughness and surface temperature. In addition, the surfaces were analysed using a scanning electron microscope (SEM). Further, the estimation equation has been derived using response surface method (RSM) based on the data obtained in the study. The results show that velocity and concentration are the key factors in determining the mass loss and surface temperature while the impact angle has a relatively minor role. Mass losses in rough samples ranged from 8.8 mg to 40 mg; in polished samples, the range ranged from 5.6 mg to 10.9 mg.Öğe Wear Behavior of Bronze vs. 100Cr6 Friction Pairs under Different Lubrication Conditions for Bearing Applications(Mdpi, 2022) Demirsoz, RecepDamage due to a shortage or excess of or the pollution of lubricating oil is often cited as one of the most significant issues confronted by the rolling mill sectors. Lubrication can be provided by either central lubrication systems or individual lubrication systems. In this study, the wear characteristics of the mono-block rolling plain bearing material that is utilized in wire rod rolling mills were evaluated under conditions where the lubricating oil medium included either 2.5% of scale, 5% of scale, or no scale at all. In this experimental study, a unique ball-on-flat experimental setup similar to the one used in the ASTM G133-05 standards was used. Bronze was used as the bearing material and 100Cr6 roller-bearing steel was used as a steel ball of 6 mm in diameter. The experiments were carried out at room temperature, at three different sliding speeds of 5 mm/s, 10 mm/s, and 15 mm/s, and with three different loads of 10 N, 20 N, and 30 N. The wear mechanisms were analyzed visually and elementally using Scanning Electron Microscope (SEM) and Energy-Dispersive X-ray Spectroscopy (EDX) methods. An Analysis of Variance (ANOVA) and the Response Surface Method (RSM) were used to analyze the test results, such as volumetric material loss, the coefficient of friction, and the surface profile. In this study, which was carried out in a lubricant environment containing solid particles, the most effective parameter was the environmental parameter. The increase in the number of solid particles caused an increase in volume loss and friction coefficient.Öğe Wear performance of Ti-6Al-4 V titanium alloy through nano-doped lubricants(Springernature, 2023) Etri, Hamza E. L.; Singla, Anil Kumar; Ozdemir, Mehmet Tayyip; Korkmaz, Mehmet Erdi; Demirsoz, Recep; Gupta, Munish Kumar; Krolczyk, J. B.Titanium and its alloys are widely utilized in the biomedical sector, they still exhibit poor tribological properties and low wear resistance when employed against even weaker substances. The poor hardness, instability, high coefficient of friction, low load-carrying capacity, and insufficient resistance to not only abrasive but also adhesive wear are further disadvantages of titanium alloys. The focus of this investigation is on the tribological performance of Ti-6Al-4 V alloy in contact with WC carbide abrasive balls when subjected to nanodoped cooling and lubrication conditions. Tribological experiments were executed on Ti-6Al-4 V flat samples using a ball-on-flat tribometer in dry hybrid graphene/boron nitride combination nanoparticles (MQL, nano-3), nanographene with MQL (nano-1), and boron nitride with MQL (nano-2) conditions. After that, the most significant tribological characteristics were investigated, including volume loss, friction coefficient, wear rate, and micrographic structures. The outcomes also demonstrated that the hybrid nanoparticle situation experienced the least amount of volume loss.
