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The integration of artificial intelligence, machine learning, and deep learning algorithms into machining processes has made them more intelligent, significantly reducing costs, improving production rates, and enhancing product quality by accurately predicting machining responses. In this study, a Bayesian neural network (BNN) is employed to predict tool wear during the milling of Al6061 T6 alloy, showcasing the novelty of BNN in handling uncertainty and providing reliable predictions. Milling experiments were conducted at three different spindle speeds under dry, flood, and minimum quantity lubrication (MQL) strategies. Machinability was evaluated by considering tool wear, milling forces, and surface quality. Unique to this study is the use of force and current signals as input to the BNN model, capturing real-time data to estimate tool wear. The signals were trained and tested to predict tool wear under varying cutting conditions. The results indicated that tool wear in dry conditions was primarily due to adhesion, leading to higher milling forces and poorer surface quality. In comparison, the wet and MQL conditions resulted in 11–21% and 9–13% less tool wear, respectively, than dry conditions, alongside improved surface roughness and reduced machining forces. The BNN model demonstrated its ability to avoid overfitting, providing highly accurate predictions with an error margin of 2–15% when compared to experimental results. Unlike conventional models, the BNN accounts for prediction uncertainty, making it more robust and reliable across different datasets. Thus, the proposed BNN model proves its effectiveness and generalizability in predicting tool wear under various machining conditions, setting a new benchmark for the application of artificial intelligence in machining processes. [ABSTRACT FROM AUTHOR]

Nickel-based superalloy GH4169 is widely demanded in the aerospace industry due to its superior properties. However, there are some problems such as serious tool wear and poor surface quality in the cutting process of GH4169. In this study, in order to improve the machinability of GH4169, GnP-ZrO2 hybrid nanofluids (NFs) were prepared and applied to cutting machining. Thermophysical properties of the prepared hybrid NFs such as dynamic viscosity, thermal conductivity, and contact angle were tested. Meanwhile, a series of wear tests and turning processes of GH4169 under Dry, MQL, GnPNMQL (GNMQL), GnP-ZrO2 hybrid NMQL (GZNMQL) conditions were conducted to evaluate the performance of NFs. The results showed that the thermophysical property of NFs was improved and the coefficient of friction was significantly reduced with the addition of GnP and ZrO2 hybrid nanoparticles. The machined surface roughness and cutting temperatures under the GZNMQL cooling condition were reduced by 53.53% and 54.06% compared to those under the Dry condition, respectively. Additionally, the tool life was significantly improved. The "flake-spheres-flake" structure of the GnP and ZrO2 improved the lubricity, cooling effect, and friction properties of the cutting fluids, which resulted in a better performance in terms of machined surface roughness, cutting temperatures, and further improved tool life. [ABSTRACT FROM AUTHOR]

This work uses an alumina wheel to investigate the eco-benign grinding for better surface integrity of Inconel 625 (IN 625). To achieve this, applying nanofluids (NFs) with the minimum quantity lubrication (MQL) principle has been adopted, aiming at eco-benign grinding practices. In this work, MoS 2 NFs, MWCNTs NFs and hybrid NFs (prepared by mixing MoS 2 and MWCNTs in a 1:1 ratio) prepared using deionized water as the base fluid have been used. An in-house developed MQL setup is used to aim the NFs inside the grinding zone. The first attempt has been made to grind IN 625 in these environments. The characterisation of NFs in terms of nanofluid stability, dynamic viscosity, thermal conductivity and surface wettability have been performed before their utilization in grinding operations. A comparison has been made between the results obtained from NFs grinding and those from dry and soluble oil-based MQL grinding. It has been found that hybrid NFs provide excellent lubrication and cooling effects, reducing grinding forces and improving surface quality. Moreover, scanning electron microscopy, energy-dispersive spectroscopy and X-ray photon spectroscopy are applied to investigate the ground surfaces under different grinding conditions. Also, residual stress (with the help of X-ray diffraction and electron backscattered diffraction) and microhardness have been determined to gain further insights into the grinding behaviour. The wheel and chip morphology analyses have been performed to support the findings. The findings from this investigation lead to the conclusion that applying nano-MQL improves grinding effectiveness and promotes cleaner grinding outcomes. Hybrid NFs prove especially effective, as the physical synergistic effect enhances and safeguards the surface integrity of the produced ground components. [Display omitted] • This work endorses the grindability improvement of Inconel 625 using nano-MQL. • Thermos-physical and tribological characteristics of developed nanofluids have been investigated. • Ground surfaces have been investigated using SEM, EDS, EBSD, XRD and microhardness techniques. • Findings have been corroborated with the wheel and chip morphology investigations. • Nano-MQL has shown promising results in grindability improvement of Inconel 625. [ABSTRACT FROM AUTHOR]

Friction and high temperatures greatly affect the hardness and processing efficiency of superalloys. Therefore, it is important to provide a coating on their surfaces with a hard layer. In this study, pack boronizing was applied on Inconel 601 to improve its microstructure and tribological properties. In this regard, tribological tests were performed under MQL, nano-MQL1 (MQL + CuO), and nano-MQL2 (MQL + TiO2) environments. The research results showed that the lowest wear depth, friction force, coefficient of friction (CoF), and volume loss values were obtained in pack-boronized Inconel 601 in a nano-MQL2 environment. In the nano-MQL2 environment, the wear depth decreased by 17.81% (from 57.922 µm to 47.605 µm) with package-boronized Inconel 601 compared to as-received Inconel 601 at a 45 N load. Pack-boronized Inconel 601 experienced an average reduction of 30.23%, 41.60%, and 52.32% in friction force when switching from dry to MQL, nano-MQL1, and nano-MQL2 environments, respectively. It was also observed that the coefficient of friction (CoF) and volume loss values decreased with pack boronizing in an MQL/nano-MQL environment. In a nano-MQL2 environment at 15 N load, volume losses for as-received and boron-coated Inconel 601 were determined as 0.288 mm3 and 0.249 mm3, respectively (13.54% decrease). The findings of this study demonstrate that pack boronizing and MQL and nano-MQL techniques enhance the tribological characteristics of Inconel 601 alloys. [ABSTRACT FROM AUTHOR]

This paper investigates the potential of utilizing lubricated liquid carbon dioxide (LCO2 + MQL) as an alternative to conventional flood cooling in grinding operations. This approach could facilitate a transition towards fossil-free production, which is a significant challenge in industry. The alternative cooling–lubrication method relies on pre-mixed LCO2 and oil and a single-channel minimum quantity lubrication (MQL) delivery method, which has already demonstrated potential in machining with geometrically defined cutting edges. However, this method has been less explored in grinding. This study primarily evaluates the grindability of AISI 4140 steel, examining surface roughness, residual stresses, microhardness, grinding forces, and specific energy for different cooling–lubrication methods. The results indicate that LCO2 + MQL is capable of attaining surface roughness and microhardness that is comparable to that of conventional flood cooling, especially in the case of less aggressive, finish grinding. Nevertheless, the presence of higher tensile residual stresses in rough grinding suggests that the cooling capability may be insufficient. While the primary objective was to evaluate the technological viability of LCO2 + MQL in terms of grindability, a supplementary cost-effectiveness analysis (CEA) was also conducted to assess the economic feasibility of LCO2 + MQL in comparison to conventional flood cooling. The CEA showed that the costs of both the cooling–lubrication methods are very similar. In conclusion, this study offers insights into the technological and economic viability of LCO2 + MQL as a sustainable cooling–lubrication method for industrial grinding processes. [ABSTRACT FROM AUTHOR]

In recent times, manufacturing sectors are endeavouring to achieve optimal product quality while minimizing costs. For the accomplishment of this objective, they are focusing on the elimination of the surface finishing and heat treatment processes up to an extent and, opting for concurrent optimization of multiple output responses related to product qualities and machining cost. In machining output optimizations, especially in concurrent optimizations, assigning an equal weightage to all responses leads to substandard results. Keeping in mind, this research work is carried out to eliminate the inadequacy of such optimizations by coupling the multi-response optimization technique Grey Relational Analysis (GRA) with the Analytical Hierarchy Process (AHP) for assigning the different weight fractions to the selected output responses which are tool flank wear, surface roughness and surface microhardness. Face milling experiments on EN-31 steel are conducted engaging hBN nanoparticles-based minimum quantity lubrication system. Employing subjective method-based multi-response optimization, the selected output responses are successfully optimized as per their relative priority and the best parametric conditions are obtained as LFR = 150 ml/h, SD = 40 mm, and 0.5 wt% of hBN nanoparticles in lubricant. Also, it has been noted that the presence of hBN nanoparticles provides effective cooling and lubrication at the cutting zone. [ABSTRACT FROM AUTHOR]

This study concentrates on the utility of the newly formulated machining fluid used for turning AISI 4340 steel under the near dry machining method. The preparation of the novel machining fluid involves a blending of vegetable oils and conventional lubricant in a 50:50 ratio. Three distinct compositions were investigated within this work. The biodegradability tests confirms that the novel lubricantaligns with the ethos of "Green Machining." The study's focal points include an analysis of the following crucial metrics – machining force, machining temperature, and surface finish. From the analysis, the best-formulated blend was identified. To evaluate its performance, the variance analysis on the dataset (ANOVA) and Weighted Entropy decision-making method that ranks the best option along with alternatives was executed. Further, the optimal process parameters were determined using Dragon Fly Algorithm (DFO) and Particle Swarm Algorithm (PSO) to enhance the efficacy and quality of machining. [ABSTRACT FROM AUTHOR]

Sustainable machining is an approach that aims to minimize environmental impacts and optimize resource use in industrial production processes. The basis of this approach lies in reducing the environmental and economic impacts associated with the use of machining methods. Machining is a widely used method for shaping metal parts, and this process is often energy-intensive and wasteful. Sustainable machining involves various strategies. These include methods such as the use of renewable energy resources, increasing energy and material efficiency, improving recycling and waste management, and selecting materials to reduce cutting fluids and environmental impacts in production processes. In this study, the machinability properties of Nimonic-60 superalloy, which is an important material in the field of industry, were examined. In order to conduct machinability trials, three different cutting speeds (Vc, 40-50-60 m/min), three different feed rates per tooth (fn, 0.050-0.075-0.100 mm/rev), and three different cooling/lubrication conditions (dry-air-MQL) were used. The trials were conducted using a computer-controlled three-axis milling machine. Additionally, Taguchi analysis was performed to reduce the number of experiments and costs. Consequently, it was concluded that the most optimal choice for surface roughness, flank wear, and cutting temperature was the Minimum Quantity Lubrication (MQL) environment. Minimum surface roughness, tool wear and cutting temperature in the MQL environment were measured as 0.499µm, 0.201mm and 66.4 C˚ respectively. The Taguchi study findings revealed that cooling/lubrication had the most impact on surface roughness (56.66%), flank wear (87.96%), and cutting temperature (78.68%). [ABSTRACT FROM AUTHOR]

V-active VCI® is a new class of corrosion inhibitors that utilize water as a propagation medium, enabling the development of cutting fluids with the addition of such inhibitor. Consequently, in addition to the necessary characteristics of a cutting fluid, they are capable of providing corrosion protection for both the metal workpiece and the machine, thereby avoiding the use of intermediate protective oils and subsequent degreasing, reducing the number of process steps, and lowering environmental impact. Additionally, the fluids in question pose no risks to humans and are biodegradable. Furthermore, the minimum quantity lubrication technique combined with wheel cleaning has been yielding excellent results for the grinding process. These results stem from various factors: quality of the produced workpiece, reduced environmental impact, preservation of operator health, and reduction of production costs. Therefore, in the present study, it was found that incorporating the benefits of V-active VCI® into the minimum quantity lubrication technique with cleaning brings excellent results for the grinding process. The performance of a base fluid and two fluids with corrosion inhibitor was compared in the grinding process of AISI 4340 steel with aluminum oxide wheel using the MQL technique (with and without wheel cleaning), comparing with the results obtained by the same fluids in conventional lubri-cooling. The tests evaluated: surface roughness, roundness errors, wheel diametral wear, power consumption, acoustic emission, cost analysis, and pollution. The results show that grinding using cutting fluids with volatile corrosion inhibitors was beneficial to the process for all three lubri-cooling conditions. [ABSTRACT FROM AUTHOR]

The present study is focused on the investigation and simultaneous optimisation of MQL-turning parameters with the application of the weighted Mayfly algorithm for sustainable machining of Nimonic 75. The nanofluid used for the experimental work is graphene oxide dispersed rice bran oil. The parameters of cutting velocity, feed rate, nozzle angle, and nozzle distance were considered for processing characteristics of force, roughness, and residual stress. The weight in the Mayfly algorithm is determined using a grey relational coefficient (GRC). The weight importance calculated for each response is compared with the different schemes in the algorithm. The result showed that the parameters with these schemes had different optimal values. At optimal factor levels determined using GRC in the Mayfly, the algorithm improved 'F-value = 0.40' compared to factor levels in other methods. Compared to experimental results, the optimised value reduces the surface roughness, cutting force, and residual stress by 30%, 3%, and 10%, respectively. The feed rate, cutting velocity, and nozzle distance are the most vital parameters for optimising the output response with the GRC-Mayfly process. [ABSTRACT FROM AUTHOR]

The current work presents an approach for the optimization of machining parameters on the turning of Al7075-T6 aerospace alloy. The alloy was turned on a lathe machine equipped with four different metalworking fluid (MF) setups: minimum quantity lubrication (MQL), Ranque–Hilsch vortex tube (RHVT), compressed air, and dry cutting using coated carbide tools. Taguchi technique was considered for the design of the L16 experimental array with three variable factors and four levels, and S/N ratios were obtained. The turning parameters feed rate and cutting speed are optimized in the experiment, taking into account responses such as surface roughness and tool wear. ANOVA determined the significant parameters that majorly influenced the responses. The results demonstrated that the condition of machining (<99% probability) was the most influential parameter followed by cutting speed (<95% probability) which affects the surface roughness and tool wear. Moreover, turning with MQL at a low cutting speed represented the optimum machining setup for reducing surface roughness and tool wear of this alloy. It was due to the fact that MQL decreases the friction between the tool and the workpiece which reduce the mechanical and thermal stresses on the cutting tool, resulting in lessened tool flank wear and effectively improving the surface quality. [ABSTRACT FROM AUTHOR]

Machining difficult-to-cut materials involves challenging machining conditions, including higher temperatures in the cutting zone, cutting forces and friction. Another important phenomenon is vibration, which is undesirable when manufacturing high quality workpieces. One way to reduce vibration in the cutting zone is to use cooling methods. Due to its environmentally friendly nature, the minimum quantity lubrication (MQL) method has already been widely used in metalworking. However, when combined with nanofluids, it improves the ability of the aerosol to dissipate more heat and increase lubrication in the cutting zone. This paper presents the effect of a polyol ester-based Al2O3 nanofluid due to the varying mass concentration of nanoparticles on the vibration during turning of Ti6Al4V alloy and compares the results with dry cutting and the MQL method without nanoparticles. Four concentrations (0.25−1 wt%), variable nanofluid flow rate E = 0.388−1.182 g/min and air flow rate P = 10−40 l/min were considered. According to the statistical analysis, the most important factor influencing tool vibration was the mass concentration of nanoparticles in the cutting fluid. By combining the MQL method with 0.5 wt% Al2O3, the vibration acceleration RMS values were found to be the lowest. When compared to the MQL method without nanoparticles, the RMS values for dry cutting ranged from 17.8% to 24.9%, and for wet cutting they were reduced by about 10.9-18.5%.

Minimizing the drilling-induced damage on the walls and sub-surfaces of the drilled holes is a challenging but demanding task, especially on hard-to-machine materials such as CFRP/Ti-6Al-4 V stacks. In general, these stacks are highly preferred in aerospace structural applications. This paper analyzes the surface integrity of the drilled CFRP holes when they are stacked above the Ti-6Al-4 V alloy, by incorporating the laser-based marking of micro-textures on the flank and rake faces of the drill, which enables the micro-pool lubrication between the cutting-edges and work material. Comparative experimentations were conducted under MQL conditions. Considering the flank face micro-grooved drill, consistently lower thrust forces were observed across the entire range of cutting speeds and feeds, achieving reductions of up to 17 to 20%. Furthermore, the tool life study was performed, which reveals a substantial 26% enhancement in tool life with the flank face grooved drill, emphasizing its significant advantages for enhanced machining performance. [ABSTRACT FROM AUTHOR]

AISI 4340 is a medium-carbon low-alloy steel that has gained distinctive attention due to its advanced properties including high strength, high toughness, and heat resistance. This has led to its commercial usage in a wide variety of industries such as construction, automotive, and aerospace. AISI 4340 is usually machined in a hardened state through a hard-turning process, which results in high heat generation, accelerated tool wear, low productivity, and poor surface quality. The application of high-speed machining helps improve the material removal rate and surface finish quality, yet the elevated temperature at the cutting zone still poses problems to the tool's lifespan. Apart from using advanced cutting tool materials, which is costly, researchers have also explored various cooling methods to tackle the heat problem. This paper presents a review of a sustainable cooling method known as minimum quantity lubrication (MQL) for its application in the high-speed turning of AISI 4340 steel. This study is centered on high-speed turning and the application of MQL systems in machining AISI 4340 steel. It has been observed that the hard part turning of materials with a hardness exceeding 45 HRC offers advantages such as improved accuracy and tighter tolerances compared to traditional grinding methods. However, this process leads to increased temperatures, and MQL proves to be a viable alternative to dry conditions. Challenges in optimizing MQL performance include fluid penetration and lubrication effectiveness. [ABSTRACT FROM AUTHOR]

The nickel-based high-temperature alloy GH4169 is the material of choice for manufacturing critical components in aeroengines, and electrostatic atomization minimum quantity lubrication (EMQL) milling represents a fundamental machining process for GH4169. However, the effects of electric field parameters, jet parameters, nozzle position, and milling parameters on milling performance remain unclear, which constrains the broad application of EMQL in aerospace manufacturing. This study evaluated the milling performance of EMQL on nickel-based alloys using soybean oil as the lubrication medium. Results revealed that compared with conventional pneumatic atomization MQL milling, EMQL reduced the milling force by 15.2%–15.9%, lowered the surface roughness by 30.9%–54.2%, decreased the average roughness spacing by 47.4%–58.3%, and decreased the coefficient of friction and the specific energy of cutting by 55% and 19.6%, respectively. Subsequent optimization experiments using orthogonal arrays demonstrated that air pressure most significantly affected the milling force and specific energy of cutting, with a contribution rate of 22%, whereas voltage had the greatest effect on workpiece surface roughness, contributing 36.71%. Considering the workpiece surface morphology and the potential impact of droplet drift on environmental and health safety, the optimal parameter combination identified were a flow rate of 80 mL/h, an air pressure of 0.1 MPa, a voltage of 30 kV, a nozzle incidence angle of 35°, an elevation angle of 30°, and a target distance of 40 mm. This research aimed to provide technical insights for improving the surface integrity of aerospace materials that are difficult to machine during cutting operations. [ABSTRACT FROM AUTHOR]

Cutting temperature is the most crucial quality character in the machining process. By prudently controlling this factor, high precision workpiece can be produced. Determination of cutting temperature in milling operation is challenging, time consuming and expensive process. These cost and time losses can be eliminated by predicted cutting temperature with machine learning models. The present study deals with the prediction of the cutting temperature on end milling of H11 steel with coated cemented carbide tool under three cooling environments, such as dry Machining, Minimum Quantity Lubrication (MQL) and Nano Fluid Minimum Quantity Lubrication (NMQL). In this study, various machine learning models such as Regularized Linear Regression Model (RLRM), Decision Tree (DT), XGB Regression (XGBR), Support Vector Machine (SVM), K-Nearest Neighbors (KNN) and Gaussian Process Regression (GPR) were developed. These models use speed, feed, and lubrication conditions as input parameters. Among all the models, GPR yielded the best performance, achieving the highest evaluation metric scores of mean absolute error (MAE), root mean squared error (RMSE), mean absolute percentage error (MAPE), determination coefficient (R2) and accuracy as of 14.04, 18.79, 14%, 0.9 and 85% respectively. [ABSTRACT FROM AUTHOR]

The cutting fluid plays an important role in lubrication, cooling, chip removal, and rust protection in mechanical manufacturing. The waste-cutting fluid can pose a threat to the water environment and even human health. The minimum quantity lubrication (MQL) technology can meet the requirements of clean manufacturing, and it has been widely recognized as a replacement for traditional flood-cutting technology. As an emerging green cutting technology, it has broad application prospects. The latest progress in MQL machining technology is reviewed, and the cutting performance of MQL is elaborated in this article. Firstly, the composition and implementation form of the MQL system were elaborated. The impact of the MQL system parameters on cutting performance was also illustrated in this part. Secondly, the combination of MQL technology, low-temperature technology synergistic effect of additives, and the atomization and hardware improvement of MQL was introduced. Thirdly, the cutting performance of MQL technology on cutting force, cutting temperature, residual stress, tool wear, and surface quality was analyzed. Finally, the limitations of MQL technology were discussed, and its development direction was prospected. It provides suggestions for the engineering application of MQL technology. [ABSTRACT FROM AUTHOR]

The 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. [ABSTRACT FROM AUTHOR]

Titanium alloy Ti-6Al-4 V holds a prominent status within the aerospace sector owing to its remarkable strength-to-weight ratio. However, its low thermal conductivity and high tensile strength present machining obstacles, resulting in elevated tool temperatures and mechanical stress. In aircraft manufacturing, drilling is essential, yet using solid carbide drills conventionally leads to considerable tool wear. Prior investigations aimed at enhancing tool longevity have explored diverse cutting methodologies, spanning from flood cooling to minimum quantity lubrication (MQL). Despite these efforts, persistent challenges endure. Therefore, this study introduces an innovative approach, leveraging titanium aluminum nitride (TiAlN)-coated indexable centerless inserts to bore holes in Ti-6Al-4 V under three distinct cutting conditions: dry, flood cooling, and MQL. These conditions are scrutinized across varied feed rates (60 mm/min, 100 mm/min, and 120 mm/min) with a fixed spindle speed of 1200 rpm. The study's primary focus is on key output parameters, including surface roughness (SR), tool life, and cutting temperature. From the parametric and surface topographic analysis, the findings reveal that under the flood cutting approach with a 60-mm/min feed rate, the indexable inserts excelled when drilling Ti-6Al-4 V. This combination delivered a better surface quality (Ra = 1.66 µm), extended tool life (27,814.27 mm3 material removed and 18 holes drilled), and lower cutting temperature (881°F). Additionally, scanning electron microscopy (SEM) analysis corroborates that most common types of wear observed were abrasion, delamination, cracking, and edge fracture. [ABSTRACT FROM AUTHOR]

The large amount of smoke generated during minimum quantity lubrication (MQL) processing not only pollutes the ambient air but also directly endangers the health of operators. Establishing a smoke diffusion model is crucial for achieving precise control of MQL smoke. Currently, accurate smoke diffusion models in this field are lacking. In this study, a smoke diffusion model under MQL was established to predict the mass concentration of PM10. The cutting speed, depth of cut, feed rate, and nozzle injection rate were integrated into the model using an extreme learning machine (ELM) to improve the accuracy of predicting the spatial distribution of smoke particles. A nonlinear equation reflecting the variation in concentration over time was solved using a backpropagation (BP) neural network. Finally, a spatiotemporal prediction model for smoke concentration during MQL turning was established. Comparing the predicted values of oil mist concentration in the test set with the true values through validation experiments, the results show that the absolute error of the prediction model at the measurement point tends to decrease with the increase of time, and the prediction accuracies are all above 90%. The maximum and minimum errors between the predicted and true values at different times are 9.77% (at the 0th second) and 4.11% (at the 6th second), respectively, which are less than 10%. Thus, the establishment of a highly accurate MQL cutting oil mist diffusion prediction model was realized. [ABSTRACT FROM AUTHOR]

During the machining of aluminum alloys, the adhesion of chips to the tool affects the performance characteristics. Today, different cooling systems are used to eliminate these negativities. In this study, the effects of end milling using HSS and carbide cutting tools of 6061-T6 aluminum alloy on surface roughness, chip thickness ratio and tool wear were examined using different cooling techniques (dry, minimum quantity lubrication (MQL) and nanocutting fluid). Different cutting speeds (180, 200, 220 m/min) and different feed rates (0.05, 0.06, 0.07 mm/rev) were used in the experiments. According to experimental findings, tool wear and surface roughness decreased at low cutting speed and feed rate by using nanocutting fluid with carbide cutting tools. It has been observed that the chip thickness ratio increases with high cutting speeds using nanocutting fluid and decreases with dry machining and high feed rates. The best milling performance of the aluminum alloy was achieved in experiments using carbide cutting tools and nanocutting fluid. [ABSTRACT FROM AUTHOR]

This study investigates the impact of various auxiliary cooling techniques on machinability, energy consumption, carbon emissions, and economic factors in the drilling process of AA7075T6 aluminium alloy using TiO2 and C-reinforced composites. The study employed various cooling conditions (dry, MQL, CO2, and hybrid MQL+CO2), with different cutting speeds and feed rates, to evaluate their effects on drilling characteristics. The findings indicated that the combined MQL and CO2 cooling notably enhanced the drilling process by reducing cutting forces by 32% and surface roughness by 65% compared to dry cutting. This synergy between lubrication and cooling significantly improves machinability, resulting in higher-quality machining outputs with smoother surfaces and more precise circularity. Energy analysis revealed that the MQL+CO2 method reduces energy consumption to 64% observed under dry conditions, underscoring its efficiency through better heat dissipation and reduced friction. Furthermore, this method demonstrates a significant reduction in carbon emissions, contributing to environmental sustainability. Economically, although initial costs associated with the implementation of cooling systems are higher, they are offset by reduced tool wear and energy costs, making it a viable solution for sustainable manufacturing practices. [ABSTRACT FROM AUTHOR]

Industry wants materials of the highest competence that are strong and precise in their dimensions. Due to their strength even at high temperatures, these high-grade, high-strength materials are difficult to machine. The traditional methods of cooling and lubricating have been shown to be ineffective and are harming the environment and human health. Researchers have created green machining environments that can lower cutting pressures and temperatures while improving surface quality and tool life to solve this issue. An attempt has been made in this work to compile every alternate approach that may be used to manufacture materials that are challenging to cut, like titanium, toughened steels, and nickel super alloys. The results of diverse machining conditions will undoubtedly be shown in our assessment. The best green settings, according to current research, are nano fluid minimum quantity cutting fluid (NFMQL) and minimal quantity cutting fluid (MQL). [ABSTRACT FROM AUTHOR]

The concept of applying and studying the performance of new coolants is always the interest of researchers to reduce the cost and environmental impacts with improved machining performance. This study examines the impacts of factors like spindle speed, feed rate, and depth of cut under dry, wet, and minimum quantity lubrication (MQL) condition on the surface roughness (Ra) during end milling of EN31 in a CNC vertical milling machine. The experimental strategy is based on Taguchi's L9 orthogonal array technique, with three factors and three levels for each variable, and an analysis is done to determine the influence of each factor on surface roughness. Experimental surface roughness values are used to construct the contour plots, and the impacts of the parameter changes are investigated. In comparison to dry and wet conditions, the surface roughness is lower in MQL conditions. For MQL conditions, rice bran oil is applied as lubricant. ANOVA is used to determine factor's influences on surface roughness. It is found that the spindle speed is the most influencing factor for surface roughness. The MQL is considered to be one of the best alternatives for wet machining and is very effective. [ABSTRACT FROM AUTHOR]

The demand for Nitinol alloy machined parts in the automotive and aerospace industries necessitates the optimization of machining parameters to enhance process performance in terms of product quality and cost. Specifically, the spindle speed (S), feed (f), and depth of cut (t) are crucial process variables in machining. Output performance indices, such as material removal rate (MRR), tool wear (TW), and surface roughness (Ra), are important measures of process effectiveness. This study focuses on evaluating process performance in machining Nitinol 56 alloy, utilizing the Taguchi method to assess the impact of the aforementioned process variables on the output performance indices. It has been noticed that the feed was the most influential variable for surface roughness and material removal rate whereas spindle speed for the tool wear. Subsequently, multiple multi-attribute decision-making optimization methods (MADM), including Grey, Utility, and TOPSIS, are employed to identify the optimal combination of process variables that satisfy the conflicting performance indices. The optimal process variable combination determined across all methods is S = 835, f = 0.111, and d = 0.6. A Moreover, a confirmatory test was conducted to validate the optimal conditions, revealing an increase of 5% in the overall value of utility, 5.98% in grey coefficient, and 1.23% in the closeness coefficient. [ABSTRACT FROM AUTHOR]

This study aims to investigate the impact of parameters associated with minimum quantity lubrication (MQL) in CNC turning of DIN 1.2738 plastic mold steel. The independent parameters considered include flow rate ( F r ), nozzle distance ( N d ), and nozzle angle ( N a ), with the objective of ensuring effective lubrication. The study focuses on evaluating surface roughness, cutting temperature, and specific cutting energy (SCE) to assess machinability. Experiments were conducted using coated carbide inserts SNMG 120,412-km and a commercially available vegetable oil-based cutting fluid, Eraoil KT/2000. Constant cutting parameters, such as cutting speed (220 m/min), feed rate (0.05 mm/rev), depth of cut (0.5 mm), nose radius (1.2 mm), working pressure (0.5 MPa), and nozzle radius (1 mm), were maintained. The methodology employed various analytical approaches, including analysis of variance (ANOVA), response surface methodology (RSM), gray relational analysis (GRA), and desirability function (DF). The results indicate that the MQL system effectively provided lubrication over a short nozzle distance of 10 mm by employing a high flow rate of 51 ml/h and a significant nozzle angle of 60°. These conditions resulted in satisfactory performance for machinability-related parameters. Consequently, surface roughness ( R a ) remained between 0.15 and 0.18 μm, cutting temperature ( T c ) ranged from 130 to 135 °C, and SCE consumption ( E cs ) was reduced to 3.37 J/mm3. [ABSTRACT FROM AUTHOR]

A study of a hole-making experiment for AFRP was carried out using two cutting methods, drilling, and milling, respectively, to analyze the surface morphology, cutting force, hole wall morphology, and tool wear, as well as to conduct the test under MQL conditions, and to compare the situation with that in dry cutting. It was found that the drilling of holes had more burrs on the inlet surface, surface roughness and poor roundness, and fewer burrs on the outlet surface and better quality, and the opposite was true for milling, with fewer burrs on the inlet surface, good surface quality and roundness, and more burrs on the outlet surface and poor roundness. After the use of MQL, the cutting surface edge bulge expansion, free resin block, and resin smearing phenomenon significantly reduced or even disappeared, but the surface burr inhibition effect is limited. At the same time, the observation of the hole wall found that the MQL conditions of the shear effect are apparent, the fiber fracture surface is neat, and we can see the orthogonal weaving intersection of the upper and lower layers of fibers. By establishing the response surface model of cutting force, the drilling cutting force achieves the minimum value in the interval, and the milling cutting force achieves the maximum value in the interval. The study shows that the cutting force of AFRP hole-making shows a laminar solid nature, and its laminated structure has a strong reflection, especially the axial force signal; the cutting surface morphology has a great relationship with the cutting mode and the system stiffness/strength; the increase of the feed speed makes the single cutting fiber volume increase, and the extrusion of the cutting surface is enhanced, which inhibits the surface burr to a certain degree. After the weighting analysis, it was found that the interaction between cutting speed and feed rate was reduced, and the individual effect of each influencing factor was enhanced, which was conducive to exerting the cutting efficiency of the tool itself. In addition, the study also found that the contact point between the tool and workpiece is also one of the influencing factors of the cutting surface morphology and makes the surface burr problem more complicated. [ABSTRACT FROM AUTHOR]

Cutting fluids play a vital role in machining operations by reducing friction and heat, facilitating chip removal, and enhancing both tool life and product quality. Although mineral-based oils are commonly used in flood lubrication, their toxicity and environmental impact have raised concerns. As a result, alternative methods like dry machining and Minimum Quantity Lubrication (MQL) have gained attention for reducing oil consumption. This study investigates the use of vegetable oils as MQL cutting fluids in the turning of AISI 4130 steel, revealing that vegetable-based fluids outperform conventional options. MQL significantly improves machining efficiency compared to flood and dry conditions. The study also examines chip formation dynamics, especially in hardened AISI 4340 steel, where high temperatures and tool wear pose challenges that can be mitigated through sustainable practices like MQL with bio-based fluids. Among the oils tested, coconut oil proved to be the most effective, producing thinner chips and larger shear angles at higher cutting speeds. The findings indicate that coconut oil excels at reducing chip thickness and increasing shear angles during high-speed cutting. Future research will further compare biobased fluids with synthetic oils and dry machining to optimize processes for greater sustainability and performance. Under MQL, vegetable oils show significant performance improvements over blasocut oil, with soybean oil achieving the lowest cutting forces, reducing them by 9% compared to blasocut. It also improves surface roughness by 4.23%, 8.56%, 15.24%, and 16.98% compared to other oils. Temperature and power consumption are also reduced by 3% to 19% compared to other oils. The study emphasizes the benefits of bio-based cutting fluids in MQL, highlighting their superiority over conventional methods in terms of surface quality, tool longevity, and environmental impact. [ABSTRACT FROM AUTHOR]

With escalating demand for machinability, economical production, health, and environment-related aspects are pushing the present industrial units to drop the usage of harmful-cutting fluid in machining. However, the adaption of this approach for machining difficult-to-cut materials does not ensure favourable outcomes of the tool performance, surface qualities, etc., as friction and heat seriously disturb machining efficiency. This study is focused on near-dry machining employing recently developed hybrid nanofluids-based lubrication in the machining of AISI 52,100 steel. Hexagonal boron nitride (hBN) and silicon carbide (SiC) nanoparticles are added to the lubrication oil to enhance the performance of the Minimum Quantity Lubrication (MQL) system. Taguchi's method-based Grey relational analysis (GRA) is used for the concurrent optimisation of the tool flank wear and surface roughness. The best parametric setting for the multi-response is achieved as: a lubricant flow rate of 150 ml/h, depth of cut of 0.2 mm, and nanofluid with 0.8 wt % of hBN and 0.2 wt % of SiC nanoparticles. The confirmation experimentation concluded that the multi-response factor is enhanced by 2.48% at the optimum setting with the mean values of TFW and SR as 84 and 0.36 µm, respectively. [ABSTRACT FROM AUTHOR]

Cobalt- and nickel-based superalloys are being extensively used in aerospace, automotive and medical applications due to their specific properties, which include working at high temperatures and stresses, good corrosion and oxidation resistance. This paper incorporates a review on the machinability aspects of nickel- and cobalt-based superalloys in turning operations. The machinability aspects like tool wear and surface integrity are critically reviewed for turning operation. Also, the effect of parameters, such as coating, cooling methods, cutting speeds and feed rate on tool wear, is reviewed critically. The different tool wear mechanisms that occur during machining of these superalloys are studied along with surface integrity, which include surface roughness and microstructures. Lastly, conclusions drawn are based on parameters that need to be improved for sustainable machining of nickel- and cobalt-based superalloys. This review will guide researchers and manufacturers for proper understanding of parameters selection. [ABSTRACT FROM AUTHOR]

A variety of simple and complex components made of metal, as well as non-metals, can be fabricated by machining. Generally, the machining process produces enormous heat at the metal cutting interface. Coolants are more often used to lessen the amount of heat generated during machining. However, it has been found that cutting fluid produces environmental risks and health risks to the operators such as skin cancer, respiratory diseases, cough, etc. and it also increases machining costs. Therefore, several researchers are working in this field to mitigate these problems without compromising the quality of machined parts produced. Manufacturing processes should be optimised without affecting the environment. Researchers are shifting towards environmental sustainability and adopting various novel machining processes like dry machining, MQL, cryogenic machining, etc. thereby curtailing the usage of cutting fluid up to certain extent. Micro-nano textured surfaces eventually reduces wear, and it will also help in reducing the cutting temperature through effective lubrication and cooling. This article aims to provide comprehensive information on different prospects of surface textured cutting tools in the field of machining. [ABSTRACT FROM AUTHOR]

Tool flank wear, owing to its direct interaction with the machined surface, can have detrimental effects on the workpiece surface integrity. This study investigates the impact of tool flank wear on surface integrity characteristics, particularly white layer thickness (WLT) and chemical corrosion resistance, during high-speed milling of AISI 4340 steel. Twenty-one experiments, ranging in 7 levels of flank wear widths (0–0.6 mm), were carried out under consistent cutting conditions in the presence of a minimum quantity lubrication (MQL) system. The results illustrate that up to a flank wear width of 0.4 mm, there is a modest increase in surface roughness, microhardness, and WLT. However, beyond this threshold, a significant escalation in these parameters is observed. Notably, a wear width of 0.6 mm induces non-uniform material flow, impacting microhardness up to 120 mm beneath the surface and causing a sudden increase in WLT. According to open-circuit potential analysis, the surface's tendency to electrochemical reactions increases slightly as the wear width increases up to 0.5 mm. The electrochemical impedance spectroscopy of the machined surfaces also revealed that utilizing tools worn to 0.4 and 0.6 mm, respectively, led to a decrease in Rcorr values by 35 % and 75 % compared to the specimen machined with a new tool. These insights underscore the critical importance of managing tool wear to maintain surface integrity in high-speed milling operations.

Machining processes hold a pivotal place in the sphere of modern manufacturing. Thus, constant advancements to enhance their efficiency and sustainability are warranted. This review paper discusses the recent advancements in machining with Minimum Quantity Lubrication and a combination of Nano-Fluids with Minimum quantity lubrication (Nano-Fluid MQL). Recent developments are assessed with particular emphasis on critical parameters such as cutting temperatures, tool wear, and surface quality. In addition, the environmental and economic aspects of using MQL in combination with nano-fluids are discussed. This combinatory approach is evaluated as a sustainable solution in machining. This paper also presents the literature survey of nano-fluids and the application of nano-fluids in MQL.

Ti–6Al–4V, an alloy of titanium has recently gained focus of research to overcome its machinability challenges. Miniaturization in devices has forced a shift towards micro and meso-scale machining. Sustainability and green manufacturing concepts have shifted focus in machining from cutting fluids towards modern cooling approaches to minimize or eliminate them. In present research, cutting forces & tool wear in Ultrasonic Vibrations Assisted End Milling of Ti–6Al–4V at meso-scale under Dry, Flooded, Minimum Quantity Lubrication & Cryogenic cooling have been analyzed to develop optimum machining parameters. Taguchi L16 orthogonal array was designed to perform experiments keeping Cutting Speed, Feed per tooth, Depth of cut, Ultrasonic vibrations amplitude & Cooling environment as inputs. ANOVA was used to analyze contribution ratios by these parameters towards cutting forces & tool wear. Results indicated that machining conditions, cooling environment and Ultrasonic Vibrations influence cutting forces & tool wear. Depth of cut had the highest influence with 63.41% contribution towards cutting forces while cutting speed remained the highest influencing factor with 39.86% contribution towards tool wear. Cutting forces were reduced by 33.49%, 16.93% and 4.91% while tool wear was reduced by 26.43%, 9.48% and 5.17% under Minimum Quantity Lubrication environment compared to dry, flooded and cryogenic cooling respectively. Cutting forces and tool wear under ultrasonic vibrations were reduced by 24.52% and 13.16% respectively as compared to Conventional Machining (CM). For optimum results, Minimum Quantity Lubrication with low Cutting Speed, Depth of cut, Feed per tooth and high amplitude of ultrasonic vibrations is recommended to machine Ti–6Al–4V.

With the increased use of polymeric products and, consequently, steel molds, the growth in grinding applications and the use of lubricoolant fluids is inevitable. As a result, studying different process configurations is of great interest to both the industry and society in general, by making it more economical and sustainable. This work focuses on evaluating the application of different lubricooling methods (conventional, MQL, and MQL + WCJ), cutting tools (green silicon carbide, black silicon carbide, and alumina), and cutting speeds (0.25 mm/min, 0.5 mm/min, and 0.75 mm/min) in the grinding of VP50IM. The goal is to identify the combination with the lowest cost and CO2 production, while assessing its performance through output parameters such as surface roughness, roundness error, G ratio, grinding power, cost analysis, and CO2 emission. Furthermore, SEM images were taken to analyze the machined surface of the workpiece. Based on this data, it was determined that the conventional method still achieved the highest machining efficiency, even though it was more expensive and more polluting. However, the MQL + WCJ technique significantly reduced costs, up to 45%, and CO2 emissions by 67.5%, even though it presented slightly lower performance compared to the conventional method. On the other hand, the MQL system obtained the worst results due to its deficiency in wheel cleaning and heat removal from the cutting zone. It was also observed that increasing the process speed reduces costs and gas emissions, but directly affects performance since machining intensity increases, resulting in lower quality. Finally, the tool with the best heat conduction capacity, green silicon carbide, led to the best process performance, while the alumina tool, with lower thermal conductivity, achieved the poorest results. [ABSTRACT FROM AUTHOR]