Nanofluid Minimum Quantity Lubrication Research Articles

Tribological performance of the micro-textured ceramic/superalloy interface under nanofluid minimum quantity lubrication considering electroosmotic effect

Tribological performance of the micro-textured ceramic/superalloy interface under nanofluid minimum quantity lubrication considering electroosmotic effect

Steady and periodical heat-mass transfer behavior of mixed convection nanofluid with reduced gravity, radiation and activation energy effects

Significance of this study is to explore Arrhenius activation energy, microgravity, chemical reaction and porous medium effects on Darcy nanofluid over a stretching sheet with nonlinear thermal radiations. Purpose of this study is to enhance the lubrication efficiency, excessive heat reduction, surface roughness and tool wear in drilling, milling, grinding and cutting tools of machining procedures. Use of Brownian and thermophoretic nanoparticles in base liquid is very effective to reduce friction in tool-chip and tool-work interfaces, tool life ability and cooling ability through nanofluid minimum quantity lubrication in machining operations. A refined mathematical model is solved using dimensionless variables; oscillatory stokes conditions and primitive variables. The implicit form of finite difference method is applied for numerical results using Gaussian elimination approach. The numerical and physical outputs are secured using Gaussian elimination methodology in FORTRAN tool and TecPlot-360. Graphs are displayed by using numerical data in Tecplot-360 program. Impact of activation energy (AE), solar radiation (Rd), microgravity (RG), porosity (Ω), thermophoresis (NT), chemical reaction (Kr), Prandtl (Pr) and Schmidt factor (Sc) on oscillating frequency of heat and mass transport is depicted. Amplitude in fluid velocity, surface temperature and volume of concentration is enhanced as radiation, microgravity and activation energy increases. It is noted that the increasing amplitude in fluid velocity, temperature and fluid concentration is found with activation energy, radiation and buoyancy force effects. Steady behavior of skin friction and mass transport decreases as Darcy porous medium and reaction rate decreases. Frequency of oscillating skin friction and oscillating heat transfer increases as Schmidt and Prandtl coefficient increases. Fluctuations and amplitude in the frequency of heat and mass transport enhances as thermophoretic nanoparticle enhances.

Investigation of Tribological Properties of Inconel 601 under Environmentally Friendly MQL and Nano-Fluid MQL with Pack Boronizing

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.

Sustainable hard machining under zirconia nano-cutting fluid: A step towards a green and cleaner manufacturing process

The present study deals with the machinability (flank wear, surface integrity, cutting temperature and power consumption) and sustainability (Carbon emission and noise emission) investigations during hard machining under dual nozzle assisted novel ZrO2 based nano fluid MQL condition considering Taguchi L27 OA design of experiment. 0.3 % wt. ZrO2 nanofluid MQL medium effectively reduce cutting temperature and found as 65 °C, which shows the effective cooling and lubrication properties of zirconia nanofluid. Improvement in surface quality has been observed with lower rate of flank wear. Depth of cut and feed are found to be the most influential factor affecting power consumption and carbon emission with contribution of 47.213 % and 60.861 % respectively. Noise emission mostly affected by the depth of cut with a contribution of 43.40 %. Optimal parametric condition yields d: 0.1 mm, f: 0.1 mm/rev and v: 80 m/min through WASPAS and sustainable towards manufacturing industries for cleaner hard machining.

A study on mechanisms of saw-tooth chip formation in hard turning under hybrid nanofluid-assisted MQL environment

Saw-tooth chip generated from hard turning is one of the most distinguishing features with conventional turning process. The presented work aims to contribute an extensive understanding the formation mechanism and main parameters of saw-tooth chips in oblique hard turning of 90CrSi hardened tool steel (60–62 HRC). The effects of dry, Al2O3 nanofluid MQL, Al2O3/MoS2 hybrid nanofluid MQL conditions on the serrated chip formation were experimentally investigated in terms of chip morphology, chip color, segment spacing, serrated segmentation frequency, and shear angle. The obtained experimental results indicated that, due to the better cooling and lubricating performance of nanofluid and hybrid nanofluid, the shear angles ϕ increase about 91.73% and 94.88% respectively when compared to dry cutting, which makes the formation of saw-tooth chip more favorable. Moreover, the analysis of microstructure image of the back side of chip proves the better lubrication from ball roller and tribo-film formation of Al2O3 and MoS2 nanoparticles. Based on the chip morphology analysis, the shear angle ϕ, the degree of chip segmentation on the top side in the chip’s transverse section K2, and the chip deformation coefficient in the transverse section K3 should be used as the additional criterions to evaluate the frictional improvement in cutting zone.

Synthesis and characterization of carbon-based MWCNT combined with CaO to improve the surface characteristics of DED-processed Ti64 alloy machined under MQL conditions

The capacity of additive manufacturing (AM) to create intricate geometries and minimise material waste has drawn a lot of attention. Nevertheless, post-processing steps like machining are frequently needed for AM components to improve their functional surfaces. High temperatures are produced at the tool-workpiece-chip contacts during cutting operations, which lowers tool life and efficiency. Although petroleum-based cutting fluids (CFs) are commonly used to control these temperatures, they pose environmental, health, and cost concerns. Minimum quantity lubrication (MQL) with vegetable oil (VO) has emerged as a promising alternative that offers improved machining performance and environmental friendliness. However, MQL’s effectiveness of MQL may be limited under aggressive machining conditions, necessitating the use of nanoparticles (NPs) to enhance performance. In this investigation, the wettability, dynamic viscosity, density, and thermal conductivity of multi walled carbon nanotubes (MWCNT) at varying wt. concentrations (0.25% to 1.25%) are examined. Following that, the milling tests are conducted in the following conditions: dry, flood, MQL (CaO), and nanofluid-MQL (N-MQL). The outcomes show that the addition of NPs to CaO reduces the contact angle to 15.53° at 1.00 wt%, indicating better wettability. Furthermore, the incorporation of MWCNTs results in a significant improvement in the dynamic viscosity, thermal conductivity, and density of the VO. N-MQL, on the other hand, results in an enhancement in surface quality in contrast to other cutting strategies.

Effect of hBN/MoS2 hybrid nanofluid minimum quantity lubrication on the cutting performance of self-lubricating ceramic tools when machining AISI 4340

Difficult-to-machine materials have consistently limited the improvement of machining efficiency. To address this challenge, this study proposes a strategy of combining Al2O3/SiC/G self-lubricating ceramic tools with hBN/MoS2 hybrid nanofluids. The experiment evaluates the ratio and concentration of the hBN/MoS2 hybrid nanofluid based on cutting forces, friction coefficients, cutting temperatures, surface roughness, and tool wear. Results show that better lubrication is achieved by hBN/MoS2 hybrid nanofluids compared to single nanofluids. The optimal hBN/MoS2 mixing ratio and nanofluid concentration are 2:1 and 1.5 wt%, respectively. Finally, the cutting lubrication mechanism and the synergistic mechanism of self-lubricating ceramic tools with hybrid nanofluids were proposed.

Nanofluid minimum quantity lubrication assisted grinding force model considering anisotropy of SiCf/SiC ceramic matrix composites

SiCf/SiC ceramic matrix composites with excellent thermal stability, light weight and oxidation resistance have become key components in advanced aircraft engines. Nanofluid minimal quantity lubrication (NMQL) exhibits significant potential in enhancing heat transfer and lubrication efficiency during the grinding process. The technological challenge lies in thoroughly investigating the theoretical variation rule of grinding force, assisted by nanofluid minimal quantity lubrication, and subsequently achieving low-damage machining of SiCf/SiC composites. In this study, a prediction model for the grinding force during NMQL-assisted grinding was established, integrating diverse lubrication methods, grinding wheel geometric parameters, wear degree, process parameters, the anisotropy and damage degree of SiCf/SiC composites. The model was subsequently experimentally validated through grinding tests conducted on SiCf/SiC composites under various conditions, including dry grinding (DG), flood grinding (FG), minimum quantity lubrication (MQL), and carbon nanotube nanofluids (NMQL-CNTs), across multiple grinding depths. The present investigation’s grinding force forecasting model is evidenced to possess high accuracy of precision, showcasing mean deviations of 6.64 % and 11.97 % in the perpendicular (Fn) and tangential (Ft) grinding force components, respectively. Additionally, employing NMQL-CNTs facilitates the achievement of minimal grinding force and surface finish quality. At depths of 0.4 mm and 0.6 mm during grinding, the mean Fn magnitudes under the NMQL-CNTs lubrication approach underwent a decrease of 66.7 % and 74.5 %, respectively, in contrast, the mean Ft magnitudes experienced a reduction of 55 % and 67.2 %, correspondingly, in comparison to the DG lubrication technique. Notwithstanding the consistency in the material’s brittle removal mechanism across varying lubrication strategies, the NMQL-CNTs approach effectively alleviates fiber abrasion. Concisely, the research presented herein provides foundational theoretical insights and practical technological assistance for the achievement of low damage SiCf/SiC composite processing.

Sustainable machining with LN2 in turning of super duplex steel

ABSTRACT Currently, the majority of industries rely on turning processes to manufacture mechanical products. The selection of coolant is of paramount importance in the pursuit of sustainable manufacturing. Super duplex steel’s machinability during the turning process is the subject of the present investigation. The machining characteristics, such as Flank wear (Fw) and Surface roughness (Ra), were analyzed by varying the control parameters, including cutting velocity (Vs), feed rate (f), and cutting conditions i.e. Dry, Nanofluid + MQL (NMQL), LN2 + MQL (LMQL), through a constant depth of cut (d) using a Taguchi L27 orthogonal array. The results demonstrated that the LMQL approach is more efficient as it reduces the Ra by 77%, 54%, and Fw by 83%, and 93%, respectively, in comparison to the dry and NMQL conditions. Additional research on microstructure revealed that the character of the grains is improved when the surface is machined with LMQL in comparison to other cutting conditions.

Machinability investigation of grinding 2.5D-SiCf/SiC composites under nanofluid minimum quantity lubrication

SiCf/SiC composites are now the preferred option for the thermal structures of next-generation advanced aero-engines, owing to their high-temperature strength, and creep resistance. Grinding is currently a highly reliable and mature method for SiCf/SiC processing. However, the harsh, dry machining conditions lead to degradation of surface quality, and the dust generated can harm both humans and the environment. Nanofluid Minimum Quantity Lubrication (NMQL) maximizes heat transfer and lubrication in grinding and is environmentally and human-friendly. Based on this, this study thoroughly investigates the effects of dry, flood grinding, minimum quantity lubrication, and different nanofluids (MoS2 and carbon nanotubes (CNTs)) on grinding performance at different grinding depths. Compared with dry grinding, the results show that the normal grinding component force Fn is reduced by 56.9 %, 56.8 %, and 71.6 %, and the tangential grinding component force Ft is reduced by 48.4 %, 50.5 %, and 57.5 % for NMQL-CNTs lubrication condition at grinding depths of 0.2 mm, 0.4 mm, and 0.6 mm, respectively. Meanwhile, NMQL-CNTs can significantly improve the surface quality and help to obtain a surface morphology with fewer surface defects, and the stabilized lubricant film formed by NMQL-CNTs can significantly reduce the specific grinding energy. Although brittle removal was observed in different lubrication methods, NMQL-CNTs could significantly reduce surface damage due to their filling and friction reduction effects. Due to the high viscosity of NMQL-CNTs and the low intermolecular forces, they have strong lubrication stability and wear resistance. This study provides theoretical guidance for the green processing of SiCf/SiC composites.

Critical cutting thickness model considering subsurface damage of zirconia grinding and friction–wear performance evaluation applied in simulated oral environment

Ductile mode removal is always a popular topic in zirconia ceramic cutting and grinding. The completely undamaged ductile mode grinding is extremely inefficient and difficult to control, which limits the clinical application of dental zirconia ceramics. Hence, considering the effect of subsurface damage, this paper redefines the ductile mode grinding removal of ceramic materials and establishes a critical cutting thickness model for zirconia ceramic grinding. Results show that the better the lubrication condition, the smaller the subsurface damage degree and the larger the removal range of ductile zone. To verify the model, grinding experiments of zirconia ceramic under different lubrication conditions are conducted. The results show that grinding under nanofluid minimum quantity lubrication obtains the lowest friction coefficient, which is reduced by 58.54 % and 18 % compared with dry grinding and minimum quantity lubrication (MQL), respectively. Under nanofluid minimum quantity lubrication (NMQL) condition, the critical cutting thickness is 2.27 µm, which is 160.92 % larger than that under dry grinding. The error between the theoretical model and the experimental results is 10.67 %, which verifies the correctness of the theoretical model. Furthermore, using the workpiece material obtained from grinding experiments, friction–wear experiments are conducted on dental zirconia ceramics under different loads in a simulated oral environment. The results show that zirconia ceramics obtained by NMQL grinding achieve better anti-friction and anti-wear performance than that of MQL. When the maximum cutting thickness of zirconia ceramics processed by NMQL grinding is 2.27 µm, the wear rate of the workpiece is 3.06 × 10−5 mm3/N·m, and at 2.6418 µm, the wear rate of the workpiece is 2.01 × 10−3 mm3/N·m. This paper aims to provide theoretical guidance and technical support for the ductile mode removal of hard, brittle materials.

Machining with Minimum Quantity Lubrication and Nano-Fluid MQL: A Review

Machining with Minimum Quantity Lubrication and Nano-Fluid MQL: A Review

Investigation of nanofluid minimum quantity lubrication on micro-grinding quality of SiCf/SiC ceramic matrix composites

Investigation of nanofluid minimum quantity lubrication on micro-grinding quality of SiCf/SiC ceramic matrix composites

Investigation of Surface Integrity of 304 Stainless Steel in Turning Process with Nanofluid Minimum-Quantity Lubrication Using h-BN Nanoparticles

This paper investigates the influence of the concentration and particle size of h-BN nanoparticles in a nanofluid on the surface integrity of 304 austenitic stainless steel during turning, focusing on the cutting force, friction coefficient, cutting temperature, surface roughness, surface residual stress, work hardening capacity, and 3D surface topography. The results show that, compared to dry cutting, the addition of 3 wt.% h-BN nanofluid can reduce the friction coefficient on the rake face by 38.9%, lower the cutting temperature by 43.5%, decrease the surface roughness by 53.8%, decrease the surface residual stress by 61.6%, and reduce the work hardening degree by 27.5%. Two-dimensional profiles and the 3D surface topography display a more balanced peak–valley distribution. Furthermore, by studying the effect of different h-BN particle sizes in nanofluids on the surface integrity of the machined workpiece, it was found that nanoscale particles have a greater tendency to penetrate the tool–chip interface than submicron particles. Moreover, the h-BN particles in the nanofluid play a “rolling effect” and “microsphere” effect, and the sesame oil will also form a lubricating oil film in the knife-chip contact area, thereby reducing the friction coefficient, reducing the cutting force, and improving the machining surface quality.

PERFORMANCE OPTIMIZATION OF BS970 MILD STEEL TURNING PARAMETERS UNDER SiC-MoS2 HYBRID NANOFLUID USING HYBRID DEEP BELIEF NETWORK BASED COOT OPTIMIZATION

In the modern world of competitive manufacturing, turning is a basic and important process that needs to be optimized for the fast-evolving industrial nature. It has its application in various fields involving numerous materials. This research study deals with modeling with optimization on the turning process parameters of turning E2-BS970 mild steel with cryogenically treated tungsten carbide tool under NFMQL having [Formula: see text] nanofluid. The parameters considered as the input factors are spindle speed and depth of cut along with feed rate and lubrication condition. The design of the experiment is done based on Box–Behnken design for 27 trials in the response surface method. The Deep Neural Network (DBN) and the Coot optimization algorithm are employed using MATLAB software for the prediction modeling. The prediction model developed by the DBN sigmoid function gave minimal error with prediction regression values of 0.99988 for MRR, 0.99516 for Cutting temperature, and 0.99545 for Tool life. The optimized result by CO shows a value of 188.89 rpm for spindle speed, 0.2318[Formula: see text]mm/rev for feed rate, Doc of 1.45[Formula: see text]mm, and 0.5015[Formula: see text]vol.% nanofluid MQL condition. The optimized values of MRR are 3.35[Formula: see text]mm3/min, [Formula: see text]C cutting temperature, and 1543.12[Formula: see text]s of tool life. The DBN model combined with the Coot algorithm shows minimal deviation compared to the experimental results validation and confirmatory analysis and is deemed suitable for efficient prediction.

Enhancing machining efficiency of Ti-6Al-4V through multi-axial ultrasonic vibration-assisted machining and hybrid nanofluid minimum quantity lubrication

Ti-6Al-4V offers a balance of good strength with lightweight properties. Yet, Ti-6Al-4V poses machining challenges, including low thermal conductivity, chemical adhesion to cutting tools, and chip removal difficulties. To improve machining efficiency, Ultrasonic Vibration-Assisted Machining (UVAM) has emerged as a promising approach. UVAM has demonstrated reduced tool wear, cutting forces, and improved surface quality compared to Conventional Machining (CM). Additionally, Minimum Quantity Lubrication (MQL) methods offer sustainable coolant alternatives, with recent research focusing on Nanofluid-MQL (NMQL) and Hybrid Nanofluid-MQL (HNMQL) for enhanced performance. Although there exists a body of literature showcasing the promising effects of UVAM and MQL methods individually, comprehensive investigations into the synergistic effects of these methodologies remain limited. This study addresses these critical research gaps by conducting a systematic examination of combined application of multi-axial UVAM and HNMQL. Specifically, it delves into the comparison of different vibration directions within UVAM, evaluates the effectiveness of UVAM when combined with cutting fluids incorporating Al2O3 and CuO nanoparticles in NMQLs and HNMQLs, and contrasts these novel approaches with conventional machining methods. The study unfolds in three distinct stages. The first stage examines the ultrasonic cutting mechanism and its combined application with the MQL technique. In the second stage, the study investigates the physical properties of the cutting fluids, including contact angle and surface tension. The final stage encompasses slot milling operations, where an array of parameters such as cutting forces, surface roughness, surface topography, surface texture, and the occurrence of burr formations are rigorously analyzed. The results demonstrate that the combination of multi-axial UVAM with HNMQL yields substantial advantages over traditional machining methods. Notably, it leads to a remarkable reduction in cutting forces (up to 37.6 %) and surface roughness (up to 37.4 %). Additionally, this combination engenders the production of highly homogeneous and uniform surface textures, characterized by minimal surface defects and a significantly diminished occurrence of burr formations. These findings underscore the potential of multi-axial UVAM combined with HNMQL as a promising approach in enhancing the machining of Ti-6Al-4V, thus offering a pathway to enhance the efficiency and precision of aerospace component manufacturing processes.

Multi-objective optimization for balancing surface roughness and material removal rate in milling hardened SKD11 alloy steel with SIO2 nanofluid MQL

In manufacturing practice, manufacturers always strive to achieve both quality and productivity targets simultaneously. In the first part, this study examines the relationship between input factors, including cutting speed, depth of cut, and feed rate, and the output response, which is surface roughness, when milling hardened SKD11 alloy steel under minimum coolant lubrication conditions using SiO2 nanofluid. The input parameters are divided into four levels to determine their influence on surface roughness and to find the optimal conditions for achieving the minimum surface roughness. The experimental design was conducted using an L16 array. A second-order regression model was developed to describe the relationship between the input variables and the output response. In the second part, multi-objective optimization was performed to simultaneously achieve the minimum surface roughness and the maximum material removal rate (MRR). The Response Surface Methodology (RSM) was employed in this study. The results indicated that to achieve the minimum surface roughness, machining should be performed at a cutting speed of 100 m/min, a cutting depth of 0.2 mm, and a feed rate of 0.01 mm/tooth. With these settings, the predicted surface roughness could reach 0.0451 µm. On the other hand, for the multi-objective optimization, to achieve the minimum surface roughness and the maximum MRR simultaneously, machining should be carried out at a cutting speed of 100 m/min, a cutting depth of 0.36 mm, and a feed rate of 0.0168 mm/tooth. With this cutting condition, the predicted surface roughness could reach 0.1069 µm, and the predicted MRR could reach 775.06 mm3/min

Optimizing SKD-61 steel machining for marine component manufacture: A grey-Taguchi study on nanofluid minimum quantity lubrication

SKD-61 steel finds extensive application in various sectors, including the marine industry where materials must withstand harsh aquatic conditions. In this study, we employ the Grey-Taguchi approach to optimize surface roughness (Ra), cutting force (Fc), and material removal rate (MRR) when hard-milling SKD-61 steel in pure minimum quantity lubrication (MQL) and nanofluid MQL environments, aligning with the demands of marine engineering. The orthogonal array method generates a set of experiments based on four input parameters: cutting speed, depth of cut, feed per tooth, and cutting condition, which are essential factors in marine component manufacturing. Our approach combines Grey relational analysis (GRA) with the Taguchi method to enhance multi-objective outcomes in machining. The results of this marine-focused study reveal that the lowest surface roughness, cutting force, and highest material removal rates are attained when the cutting conditions align with the principles of nanofluid MQL at a cutting velocity of 80 m/min, a depth of cut of 0.2 mm, and a feed per tooth of 0.01 mm/tooth. Keywords: hard milling, nanofluid MQL, optimization machining parameters; Grey relational analysis; Taguchi

Investigation of a green nanofluid added with graphene and Al2O3 nano-additives for grinding hard-to-cut materials

This study investigates Nanofluid Minimum Quantity Lubrication (NMQL) efficiency in grinding hard-to-cut materials by incorporating graphene and Al2O3 nano-additives into oleic acid-based nanofluids. Varied concentrations and ratios were examined, analyzing thermal conductivity, viscosity, and contact angle. NMQL assessment covered grinding force, specific grinding energy, temperature, surface quality, wear rate, and friction coefficient. Hybrid nanofluids displayed superior lubrication. At 1 wt% nano additives concentration, minimum specific grinding energies, friction coefficients, and friction test temperature increments were reduced by 73.92 %, 46.57 %, and 65.69 %, respectively in comparison with dry conditions. Optimal surface quality for ZrO2 and Ti-6Al-4V workpieces emerged at 2 wt% and 3 wt% nano additives concentrations, reducing surface roughness by 60.53 % and 48.66 %, respectively compared to dry cutting.

Parametric optimization to establish eco-friendly nanofluid minimum quantity lubrication (NMQL) practice for turning superalloy Inconel 718

Purpose The purpose of this paper, an experimental study, is to investigate the optimal machining parameters for turning of nickel-based superalloy Inconel 718 under eco-friendly nanofluid minimum quantity lubrication (NMQL) environment to minimize cutting tool flank wear (Vb) and machined surface roughness (Ra). Design/methodology/approach The central composite rotatable design approach under response surface methodology (RSM) is adopted to prepare a design of experiments plan for conducting turning experiments. Findings The optimum value of input turning parameters: cutting speed (A), feed rate (B) and depth of cut (C) is found as 79.88 m/min, 0.1 mm/rev and 0.2 mm, respectively, with optimal output response parameters: Vb = 138.633 µm and Ra = 0.462 µm at the desirability level of 0.766. Feed rate: B and cutting speed: A2 are the leading model variables affecting Vb, with a percentage contribution rate of 12.06% and 43.69%, respectively, while cutting speed: A and feed rate: B are the significant factors for Ra, having a percentage contribution of 38.25% and 18.03%, respectively. Results of validation experiments confirm that the error between RSM predicted and experimental observed values for Vb and Ra is 3.28% and 3.75%, respectively, which is less than 5%, thus validating that the formed RSM models have a high degree of conformity with the obtained experimental results. Practical implications The outcomes of this research can be used as a reference machining database for various metal cutting industries to establish eco-friendly NMQL practices during the turning of superalloy Inconel 718 to enhance cutting tool performance and machined surface integrity. Originality/value No study has been communicated till now on the turning of Inconel 718 under NMQL conditions using olive oil blended with multi-walled carbon nanotubes-based nanofluid. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2023-0317/