L9 Orthogonal Array Research Articles

Optimization and tribological behavior of carbon nano tubes blended with POE oil

Over the past two decades, nano additive lubricants have become essential in manufacturing as lubricating agents. Our study examines the impact of three process parameters—carbon nanotube (CNT) (volume concentration,%), sliding velocity (m/s), and applied load (N)—on the tribological performance of polyolester oil blended with carbon nanotubes. By employing the robust Taguchi L9 orthogonal array as the design of experiment, the current study made an attempt to identify the best combination of these three factors parameters to achieve the least coefficient of friction (COF) while the study also conducted ANOVA and multivariate linear regression to determine the significant factor that determines the least COF. For this study, POE oil and varying concentrations of CNTs (such as 0.05, 0.075 and 0.1 volume concentration%) were used. For this study, the characterization of the CNTs was performed using TEM, SEM and XRD methods while its stability was validated through Zeta potential value i.e., 0.075 volume concentration% CNT concentration achieved 35 mV zeta potential value. The Taguchi L9 orthogonal array outcomes found the least COF i.e., 0.0359 was achieved from 0.075 volume concentration % of CNT with a sliding speed of 3.6 m s−1 at 50 N load. The ANOVA outcomes confirmed the major contribution (91%) of the CNT concentration towards influencing the COF outcomes. The contour plots confirmed that optimal COF can be achieved when using 0.075 volume concentration% CNT with load ranged from 75 N to 125 N and sliding velocities between 1.2 m s−1 and 3.0 m s−1. The outcomes establish that when POE oil is supplemented with CNTs, it can achieve superior performance as the nanolubricant mitigates the coefficient of friction (COF), eventually enhancing the tribological performance. Future researchers can focus on employing Taguch-grey relational analysis, artificial intelligence and machine learning models to find the optimal process parameters for other lubricants and nanoadditives.

Optimizing the drilling process parameters of AZ91 based hybrid composites using TOPSIS and grey relational analysis

AZ91 is a popular magnesium alloy that contains aluminum (Al), zinc (Zn), and small amounts of other elements that offers a good balance of mechanical properties and corrosion resistance, making it suitable for various applications such as automotive, aerospace, sports, and biomedical. The current research works focused on optimizing drilling process parameters such as cutting speed, feed rate, a set of standard tools, and biofriendly coolants against the surface roughness and axial thrust force for AZ91/ nano hBN/ micron TiB2 hybrid composites. Taguchi L18 orthogonal array was used to design the drilling experiments. The axial thrust force and surface roughness of the drilled hole were observed as response of the experiments. Based on the results from TOPSIS and GRA, the optimal conditions were determined to be a spindle speed of 65 m/min, feed rate of 1 mm/rev, using a High-Speed Steel (HSS) tool, and Liquid Nitrogen (LN) coolant for 1 wt% of nano hBN in the hybrid composite. These parameters resulted in the lowest axial thrust force and surface roughness, highlighting their effectiveness in optimizing the drilling performance of AZ91/TiB2/hBN composites.

Energy and exergy optimization of Kalina Cycle System-34 with detailed analysis of cycle parameters

This study proposes a novel methodology for optimizing the Kalina Cycle System-34, providing new insights into the existing literature on the cycle. The research highlights the cycle's key variables and identifies the most critical parameters that require improvement while proposing a practical and effective optimization method. The effects of parameters on thermal and exergy efficiency were quantified using Taguchi and ANOVA methods. The study focuses on critical parameters such as evaporator outlet temperature, turbine inlet pressure, ammonia concentration, turbine efficiency, and pump efficiency. The optimal values of these parameters were determined within specified ranges. Furthermore, the study employed the L25 orthogonal array to create case scenarios that reduced the computational cost of the Kalina cycle. The best-case scenario was not included in the 25 cases in the orthogonal array, which significantly reduced computational costs. The results showed that the system's thermal efficiency increased to 16.2 %, and exergy efficiency increased to 27.8 %, with the case conditions for the best case being an evaporator outlet temperature of 120 °C, ammonia concentration of 0.9, turbine inlet pressure of 40 bar, turbine efficiency of 0.9, and pump efficiency of 0.8.

Investigation of wear characteristics of granite dust & coconut shell ash reinforced aluminum metal matrix composite using design of experiment

Recently, one of the most important issue faced by all nations is a waste management. Therefore, it is essential to search for creative solutions to waste reduction, reuse, and recycling. This can be accomplished by adding waste materials to composite materials as a reinforcements. Reusing waste materials enhances the characteristics of existing materials, while also helping the environment by solving the disposal problem. The main aim of this paper is to study the wear characteristics of hybrid aluminum metal matrix composite reinforced with coconut shell ash (CSA) and granite dust. The hybrid composite samples were manufactured using stir casting by reinforcing CSA (ranging from 0 wt% to 12 wt%) and granite dust (maintained at 2 wt%) in Al6061 alloy. SEM and EDAX analysis were performed to investigate the microstructure and elemental composition. The wear characteristics of the hybrid composites were determined via pin-on-disc tests. Finally, the Taguchi design of experiment was performed on the specimen having the best wear characteristics by selecting the L27 orthogonal array and identified the influence of process variables on the wear rate. The results of the pin-on-disc experiment showed that the wear rate decreased with increasing CSA%. The hybrid composite composed of 02 wt% granite dust, & 12 wt% CSA indicates a lower wear rate (56.25%) as compared to the matrix alloy. The Taguchi analysis prooved that the sliding distance has a greater impact on the wear rate than the other parameters. This material can be a superior substitute where high wear resistance is required.

Investigations on the machinability performance of Al2O3/TiCN CVD coated carbide tools in sustainable high-speed hard-turning of AISI 4340 alloy steel

Abstract This study investigates the effectiveness of CVD coated carbide inserts in turning hardened AISI 4340 steel at high-machining speed V=300,350m/min under sustainable dry cutting environment. Experiments were executed in accordance to Taguchi L4 orthogonal array and crucial machinability aspects tool life, tool wear progression and mechanism, cutting force, and surface roughness were evaluated in detail. The results of this study revealed that Al2O3/TiCN coating successfully inhibited the faster progression of tool wear at low cutting speed (300m/min), feed rate (0.05mm/rev) and depth of cut (0.1mm), thus delivering the highest tool life of 19.25 min and lowest cutting force of 76.8 N. However, better surface finish of 0.305µm was obtained at high cutting speed (350m/min), low feed rate (0.05mm/rev), and high depth of cut (0.1mm). Nevertheless, at high cutting speed (350 m/min) and feed rate (0.1 mm/rev), involvement of intense thermal-mechanical effects suppressed the effectiveness of coating and tool completed its useful life at 9.24 min. Severe flaking on the cutting edge was observed at high machining parameters. Scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) analysis revealed that adhesion, oxidation, and small scale chipping and abrasion were the primary wear mechanisms attributing in competing the tool life criteria (Vb=300µm) in all cutting conditions. Furthermore, it was established that the cutting force and surface roughness increased with increasing tool flank wear due to coating delamination, material adhesion and tool chipping. This research emphasizes the significant potential of adopting Al2O3/TiCN coated carbide inserts for high-speed industrial hard-turning of AISI 4340 steel.

Production of superhydrophobic surfaces on hydrophilic AA 6063 aluminium alloy and optimisation using a Taguchi design approach

ABSTRACT In this study, superhydrophobic surfaces were fabricated on aluminium alloy plates with two different experimental procedures using the dip coating method. Each procedure was optimised using the Taguchi design to evaluate the significance of factors such as SiC abrasive paper number, etching time, and chemical modification time. By determining three levels for these factors, the L9 orthogonal array was formed. Water contact angle (WCA) measurements determined the wettability of the surfaces against the water. Scanning Electron Microscopy (SEM) was used to assess the general appearance and roughness of the surfaces. The coating thickness of the surfaces was also measured. For both experimental procedures, the most effective parameter in providing superhydrophobic coatings on the surfaces was determined as the etching time. SEM analyses demonstrated the roughness created by the clustered and protruding structures formed on the surface after the coating. The WCAs above 150° indicate that superhydrophobic surfaces were prepared.

Performance investigation of punching operation to optimize the over cut of circular hole using Design of Experiment Technique “Taguchi Method”

Current research investigates the optimization of over-cut in circular hole punching operations using a CNC turret punching machine. The study employs the Design of Experiment (DOE) technique, specifically the Taguchi method, to systematically analyze the influence of three critical factors: cutting load, hit rate, and material type. The factors were varied across three levels: cutting load (10, 12, and 14 kN), hit rate (100, 150, and 200 punches per minute), and materials (EN-8, EN-24, and EN-31). An L9 orthogonal array was used to design the experimental runs, resulting in nine unique combinations to explore the effects on over-cut (OC). Over-Cut (OC) was the key response parameter, measured using a microscopic testing machine to capture high-resolution images of the punched holes. ImageJ software was employed for image processing to accurately assess the deviations. The data were analyzed using Minitab software, focusing on signal-to-noise (S/N) ratio analysis with the criterion "smaller is better." The S/N ratio results indicated that the cutting load had the most significant impact on minimizing dimensional deviation, followed by material type and hit rate. The study revealed that the lowest dimensional deviation was achieved at a cutting load of 10 kN, hit rate of 200 punches per minute, and using EN-8 material. The mean effect and S/N ratio plots further confirmed that increasing the cutting load generally led to higher over-cut values, while higher hit rates improved precision. Interaction plots indicated that EN-31 material performed robustly across varying conditions, making it a suitable choice for diverse operational settings. ANOVA analysis supported these findings, with cutting load contributing the most to the variability in OC, followed by material type and hit rate. Current study provides valuable insights into the optimization of punching parameters to achieve minimal over-cut and enhance machining accuracy. The findings underscore the importance of selecting appropriate levels of cutting load, hit rate, and material type to optimize the performance of CNC punching operations.

Grey-Taguchi and ANN optimization in CI Engines using acetylene & biodiesel blends for Low Emissions and Better Performance

This study aimed to reduce smoke and NOx emissions in a diesel engine fuelled with a 20% blend of Calophyllum inophyllum and Prosopis juliflora biodiesel (B20) with neat diesel, supplemented with acetylene at flow rates of 1, 2, and 3 liters per minute (lpm) in dual-fuel mode. Using the Grey-Taguchi method and an L9 (3^3) orthogonal array, the effects of compression ratio, fuel type, and acetylene flow rate were examined. Regression models were developed to predict brake thermal efficiency, smoke, and NOx emissions based on these controllable factors. The study found that the optimal individual values for NOx, brake thermal efficiency, and smoke were 2353 ppm, 31.52%, and 48.7 ppm, respectively. The best-combined results were achieved with a compression ratio of 17.5 and an acetylene flow rate of 3 lpm using the CI20 blend. The findings demonstrated significant improvements in output response factors when the optimal combination was applied, as validated by experimental and artificial neural network (ANN) simulations. The Grey-Taguchi approach proved effective in reducing emissions while enhancing engine performance.

Wear behaviour analysis of thermo-mechanically processed AA7075 and AA7075/SiC/Graphite composite

The current work focuses on investigating the tribological performance of AA7075 alloy and AA7075 hybrid composite with SiC and graphite reinforcements of 2 and 0.5 wt percentages, respectively. The alloy and hybrid composite are fabricated through stir casting and thermo-mechanically processed through hot rolling routes. Dry sliding wear characterization has been carried out using a pin-on-disc wear testing setup for alloy and composite under various processing conditions using experiments designed according to Taguchi's L9 orthogonal array. The technique for order preference by similarity to ideal solution (TOPSIS) method has been adopted to achieve a single multi-response index (MRI) considering the minimization of multiple objective functions for specific wear rate (SWR) and coefficient of friction (COF). The analysis of variance (ANOVA) results of the MRI indicated that sample processing condition and load were the most significant parameters. The wear mechanism at different experimental conditions was studied using Scanning electron microscope (SEM) micrographs, energy dispersive spectroscopy analysis and 3D surface profile of wear track. The AA7075 composites are found to be comparatively good in all experimental conditions compared to the base alloy due to load-bearing SiC particles and solid lubricant graphite as reinforcing elements. The mechanically mixed layer (MML) formation in hybrid composites helped achieve good tribological properties. The AA7075 alloy and hybrid composites cross rolled at 350 °C yielded better results than other samples. The wear mechanism was abrasive and adhesive at low temperature and low load conditions in both alloy and hybrid composites. Whereas, at higher temperatures and high loads oxidative wear mechanism with delamination was prevalent. The transition of SWR from mild to severe value occurs at 250 °C in all experimental cases. The specific wear rate was improved by 85.64 % between worst and best conditions, i.e., annealed alloy and cross rolled composite.

Parameterization Of Electrolysis For The Thickening Of Sludge From Wastewater Treatment Plant: Taguchi Method Approach

The buildup of sludge is a significant issue for wastewater treatment facilities, and this study focuses on thickening it by electrolysis. The main objectives are to identify the factors influencing the sludge characteristics and to determine the optimal levels of these factors for efficient thickening. The Taguchi method with an L8(2^4) orthogonal array was used to conduct the tests, which showed that electrolysis is effective in thickening the sludge, as evidenced by the increase in dryness rate from 2.97% to 34.37% and the mass loss of 0.23 kg or 2.3%. Analyses of the carbon, chlorine, nitrogen, and sodium levels indicate that the process does not pose significant environmental risks. Minitab analysis identified the most influential factors: the electrolytic additive (NaOH) and the settling effect (without settling) for sludge thickening, the current intensity (12.6 A) for sludge quality, and the concentration of the electrolytic additive (0%) for energy consumption and electrolysis efficiency. This data is crucial for optimizing the electrolytic parameters, thereby enhancing the process efficiency and minimizing environmental and energy impacts.

Power performance enhancement for a three-turbine cluster of two-stage Savonius rotors using Taguchi approach

Choosing an optimal Savonius vertical-axis wind turbine (VAWT) arrangement that delivers the largest power coefficient is a significant challenge. So, in this paper, an optimization of the power performance using the Taguchi technique is presented for a three-turbine cluster of two-stage Savonius rotors. A three-dimensional, unsteady, incompressible airflow model is numerically solved using ANSYS and validated using published experimental and numerical studies. The power performance of the three VAWTs is optimized by adjusting five factors, including the relative angles between the turbines (ϕ12 and ϕ13), the rotation directions (RD), and the turbine spacings (S12 and S13). The rated power coefficient (CP) and its corresponding Tip Speed Ratio (TSR) are numerically obtained for an L16 (45) orthogonal array (OA). After the signal-to-noise ratio analysis, the optimal case is obtained. Results indicate that the configuration angles have the main effect on CP, the turbine spacing between the first and second rotors and the combination of rotation directions have the lowest effect. The optimal case is found to be (S12 = 2D, S13 = 2.4D, ϕ12 = ϕ13 = 70⁰, and RD = -, +, -), resulting in an increase of 19.69 % in CP compared to the isolated turbine at a rated TSR of 0.8.

Numerical analysis of the mechanics of foreign particle entry on automotive turbocharger compressor blades

Automotive turbochargers, essential for enhancing intake air pressure and boosting torque in internal combustion engines, operate at exceptionally high rotational speeds of approximately 100,000 to 300,000 rpm. Despite the implementation of dual or triple air filtration systems to filter contaminants, neglected maintenance can lead to clogged filters, resulting in the ingestion of metallic filter mesh, and other small-sized objects from filter indicators, washers, and plastic components into the turbocharger assembly. The current study explores the impact of foreign particles on the mechanics of turbocompressor impeller blades in automotive turbochargers through a computational approach. A finite element model of the turbocompressor wheel was developed with suitable boundary conditions for the turbocompressor and the foreign particle. A Design of Experiments (DoE) approach was employed using a Taguchi L12 orthogonal array to optimize the multiple parameters during the foreign particle impact. The study considered two geometric shapes of the foreign particle (conical with unit aspect ratio and hemispherical), two sizes, and two rotational speeds ranging from 150,000 to 250,000 rpm. ANSYS Explicit Dynamics® software was utilized for the numerical simulations to simulate the mechanics of foreign particle entry and the resulting damage on compressor blades.

Hole quality geometrical measurement and surface roughness for α-Phase titanium alloy (α-Ti-6Al-4V) materials by using L-PBF (laser powder bed fusion) orthopedic implant application

This study examines the quality of circular-hole 3D-printed objects using laser powder bed fusion (L-PBF) on Ti-6Al-4V titanium alloy that typically used for orthopedic implants. Meanwhile measuring surface roughness and hole dimension deviations in AM specimens is very challenging. Thus, the specimens were printed with varying process parameters, followed by an L9 orthogonal array experiment, where parameters included laser power (LP) at 175, 185, and 195 W; scanning speed (SS) at 600, 900, and 1200 mm/s; and hatch distance (HD) at 70, 90, and 110 µm. Thus the, minimum surface roughness values are Ra 2.4 µm for the top surface and Ra 16.06 µm for the inside hole curve. Whereas the smallest hole deviations are 0.1102 mm for external and 0.2094 mm for internal diameters. Therefore, this analysis include FESEM, EDX, XRD, profilometry and stereomicroscopy. Where the best settings are LP 195 W, SS 900 mm/s, and HD 70 µm, producing well-fused, uniform α-phase Ti-6Al-4V specimens that are suitable for biomedical applications.

Formula optimization of herbal drink based on coconut sugar and ginger using the Taguchi method [Optimasi formula minuman herbal berbasis gula merah dan jahe menggunakan metode Taguchi

Increasingly positive public consumption trends have increased demand for functional products such as ginger sugar herbal drinks. However, Micro, Small, and Medium Enterprises (MSMEs) producing ginger sugar herbal drinks still face production challenges, such as relying on traditional recipes passed down through generations with inconsistent processes, which affect quality uniformity. This study aimed to redesign the optimal formulation of ginger sugar herbal drinks based on parameters that affect the process. The method used is the Taguchi method with 4 (four) factors and 3 (three) levels with an L9 (34) orthogonal array matrix. Then, quality parameters were tested to determine the best ginger sugar herbal drink product. The combination of level factors in the optimal formula of ginger sugar herbal drink is the composition of ginger juice 300 mL, brown sugar 700 grams, granulated sugar 500 grams, and cooking time 45 minutes. The results of testing the quality characteristics of the confirmation experiment were following SNI requirements, namely water-insoluble part content 0.84%; water content 4.99%; ash content 1.65%; reducing sugar content 2.48%; sucrose sugar content 81.15%; dissolving time 29.93 seconds; antioxidant activity 67.13 ppm; color sensory properties 5.43; aroma sensory properties 5.32; taste sensory properties 5.16; aftertaste sensory properties 5.53; and overall sensory properties 5.21.Keywords: coconut sugar, ginger, herbal drink, quality, Taguchi method

Multi-objective optimization of EN19 steel milling parameters using Taguchi, ANOVA, and TOPSIS approaches

This study focuses on optimizing milling parameters for EN19 steel through the Taguchi method. Utilizing an L9 orthogonal array with three parameters each set at three levels, the study evaluated four quality characteristics in every run. The optimization process involved the use of Signal-to-Noise Ratio (SNR), Analysis of Variance (ANOVA), and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to determine optimal conditions and identify critical parameters influencing surface roughness, temperature, cutting force, and material removal rate.ANOVA results underscore the significant impact of spindle speed, cutting fluids, and depth of cut (DOC). The TOPSIS analysis identified the optimal conditions as a spindle speed of 710 rpm, a DOC of 0.5 mm, and the use of Neem oil combined with graphene as the cutting fluid. Among these factors, the depth of cut was found to be the most influential, followed by spindle speed and cutting fluid. Confirmation tests corroborated the effectiveness of the optimization approach, affirming its potential to improve milling outcomes. This research offers valuable insights into enhancing machining efficiency and product quality in the milling of EN19 steel.

Optimization of springback parameters of an aluminum 1050 alloy by V-bending

Abstract Springback, one of the fundamental properties of parts formed by V bending, is the dimensional deviation caused by elastic recovery. Numerical estimation and compensation of springback is essential because it affects the workpiece’s dimensional accuracy and geometry and will cause serious errors, especially during the assembly process. This study investigated the effects of process parameters such as sheet thickness and die angle on springback behavior on 1,050 aluminum experimentally and numerically. Experiments were planned according to Taguchi’s L9 orthogonal array. Sheet thickness (1 mm, 1.5 mm, and 2.5 mm) and die angle (90, 135 and 150°), were selected as forming parameters. Springback was calculated after the tests. Optimization of the parameters was evaluated using the signal/noise ratio approach. The effectiveness of parameters on results was determined by analysis of variance (ANOVA). It has been observed that the springback angle decreases with increasing sheet thickness, but springback angle decreases with increasing die angles. It has been seen that the experimental and numerical study results confirm each other. The variance analysis determined that the die angle was the most dominant springback parameter (90.9 %). Second is the sheet thickness (5.79 %).

Application of integrated entropy-COPRAS and ANN approaches for maximizing wire EDM machinability attributes of Al6082-T6/GNP/TiB2 composites

Wire Electrical Discharge Machining (WEDM) utilizes electrical sparks to cut conductive materials precisely. It employs a thin, electrically charged wire to erode the material, creating complex shapes with high accuracy, tight tolerance, and minimal material waste. The current study investigates the effect of WEDM process parameters on the various output properties of machining a hybrid Aluminium metal matrix nanocomposite (HAMMNC). A series of experiments were conducted on a composite constructed using Taguchi’s standard L18 Orthogonal Array (OA) design. The acquired responses of Material-Removal-Rate (MRR), Surface-Roughness (SR), and Kerf-Width (KfW) were optimized using integrated Entropy-COPRAS and artificial neural network (ANN) algorithms respectively. The relative significance ( Qi )values obtained for the alternatives are analyzed with the Taguchi method. The outcomes showed that the optimal setting of WEDM process variables is achieved at Servo Voltage: high volts; Pulse-on-time: 60 μs; Pulse-off-time: 16 μs; Peak Current: 6 Amp; Variable frequency: 18 Hz; Speed: 50 RPM; Sim Speed: 30 RPM respectively. The models developed from ANN were adequate and accurate from the results of error histogram and regression plots and they are best suited for the prophecy of future responses. The surface morphology studies confirmed the appearance of pockmarks, voids, and globules of debris on the Wire EDMed surfaces.

An eco-friendly enzymatic treatment to prepare spinnable banana fibers as an alternative to cotton for textile applications

Banana fibers are a sustainable material with natural mechanical strength and antibacterial properties. These fibers are extracted from the large amount of waste produced by banana pseudo stems annually. However, despite their numerous advantages, their stiffness and rough texture impede their full use in the textile. This research investigates the degumming treatment of banana fibers using enzyme combination and chemical methods to achieve spinnable soft banana fibers. An L9 orthogonal array was used in a Taguchi design of the experiment to optimize the process parameters. For enzyme combination degumming, the experimental setup comprised different quantities of hemicellulase, laccase, amylase, and pectinase; for chemical degumming, varied amounts of sodium hydroxide (NaOH) were used. The results indicate that enzyme-based degumming procedures produce better results than chemical treatments. Optimum enzyme combinations for various fiber qualities were found using the Taguchi design of experiments. These combinations included Hemicellulase 5 %, Laccase 5 %, Amylase 3 %, and Hemicellulase 5 %, Laccase 3 %, Pectinase 5 %. Without degrading the cellulose structure, these ideal enzyme combinations produced fibers with lower lignin content and higher cellulose percentages, moisture content, and tenacity values. By determining the most efficient enzyme combinations and their effects on fiber qualities, the study offers sustainable fiber processing methods for textile grade banana fiber.

Fuzzy logic-based prediction and parametric optimizing using particle swarm optimization for performance improvement in pyramid solar still.

The primary objective of this study is to develop a robust model that employs a fuzzy logic interface (FL) and particle swarm optimization (PSO) to forecast the optimal parameters of a pyramid solar still (PSS). The model considers a range of environmental variables and varying levels of silver nanoparticles (Ag) mixed with paraffin wax, serving as a phase change material (PCM). The study focuses on three key factors: solar intensity ranging from 350 to 950 W/m2, water depth varying between 4 and 8 cm, and silver (Ag) nanoparticle concentration ranging from 0.5 to 1.5% and corresponding output responses are productivity (P), glass temperature (Tg), and basin water temperature (Tw). The experimental design is based on Taguchi's L9 orthogonal array. A technique for ordering preference by similarity to the ideal solution (TOPSIS) is utilized to optimize the process parameters of PSS. Incorporating a fuzzy inference system (FIS) aims to minimize the uncertainty within the system, and the particle swarm optimization algorithm is employed to fine-tune the optimal settings. These methodologies are employed to forecast the optimal conditions required to enhance the productivity of the PSS.

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.