Eco-friendly Machining Research Articles

LocustLens: leveraging environmental data fusion and machine learning for desert locust swarm prediction

The desert locust is one of the most destructive locusts recorded in human history, and it has caused significant food shortages, monetary losses, and environmental calamities. Prediction of locust attacks is complicated as it depends on various environmental and geographical factors. This research aims to develop a machine-learning model for predicting desert locust attacks in 42 countries that considers three predictors: soil moisture, maximum temperature, and precipitation. We developed the Global Locust Attack Database for 42 countries (GLAD42) by integrating TerraClimate’s environmental data with locust swarm attack data from the Food and Agriculture Organization (FAO). To improve the usability of spatial data, reverse geocoding which is the process of converting geographic coordinates (longitude and latitude) into human-readable location names (such as countries and regions) was employed. This step enhances the clarity and interpretability of the data by providing meaningful geographic context. This study’s initial dataset focused on instances where locust attacks were recorded (positive class). To ensure a comprehensive analysis, we also incorporated negative class instances, representing periods (specific years and months) in the same countries and regions where locust attacks did not occur. This research utilizes the benefits of lazy learners by employing the K-nearest neighbor algorithm (K-NN), which provides high accuracy and the benefit of no time-consuming retraining even if real-time updated data is periodically added to the system. This research also focuses on building an eco-friendly machine learning model by evaluating carbon emissions from ML models. The results obtained from LocustLens are compared with other machine learning models, including baseline–K-NN, decision trees (DT), Logistic regression (LR), AdaBoost Classifier, BaggingClassifier, and support vector classifier (SVC). LocustLens outperformed all competitors with an accuracy of 98%, while baseline-K-NN achieved 96%, SVC gave 91%, DT gave 97%, AdaBoost has accuracy of 91%, BaggingClassifier gave 94% and LR gave 83%, respectively. Carbon emissions from RAM and CPU electricity consumption are measured in kg gCO2. They are a minimum for AdaBoost Classifier equal to 0.02 and 0.07 for DT and a maximum of 9.03 for SVC. The carbon footprint of LocustLens is 4.87 kg gCO2.

Wear Mechanism of an AlCrN-Coated Solid Carbide Endmill Cutter and Machined Surface Quality under Eco-Friendly Settings during Open Slot Milling of Tempered JIS SKD11 Steel

In the die and mold industry, tempered JIS SKD11 steel is selected to manufacture cold-forming dies that require an optimum balance of toughness, strength, and wear resistance. Therefore, the machinability of tempered JIS SKD11 in the milling machining process is challenging. The use of eco-friendly machining settings is intended to diminish tool wear and enhance the quality of the machined surface as well as the accuracy of the machined components. Adapting to the aforementioned factors for cold-forming dies is a pivotal issue. In this study, the machinability of tempered JIS SKD11 steel was analyzed under dry, MQL, cryogenic cooling with liquid nitrogen (LN2), and liquid carbon dioxide (LCO2) machining settings during open slot milling operations with varying input parameters, including cutting speeds and cutting feeds. An in-depth evaluation of output responses, including tool wear, surface roughness, cutting temperature in the cutting zone, and microhardness of the machined surface, was also conducted. The findings unveiled that the flank wear of the cutters and surface roughness of the machined surfaces obtained minimum values of 0.22 mm and 0.197 µm, respectively, during open slot milling operations at a cutting speed of 100 m/min and a cutting feed of 204 mm/min under cryogenic cooling with liquid carbon dioxide (LCO2). The findings from this study suggest that employing cryogenic cooling with LCO2 could serve as a viable substitute for dry, MQL, and cryogenic cooling with LN2 methods to enhance the machinability of hardened JIS SKD11 steel.

Investigation on fiber fracture mechanism and milling force model of CF/PEEK by ultrasonic milling

Ultrasonic milling can achieve high machining efficiency and surface quality on CF/PEEK composites due to its advantages of low cutting force, high material removal rate, improved surface quality, long tool life, and eco-friendly machining technology. This method is widely used in many scenarios such as aerospace, navigation, and new types of weapons. However, the changes in fiber fracture mode and the effects of fiber friction caused by high-frequency ultrasonic vibration cannot be ignored. To study this, first, a fiber fracture model is constructed based on experiments to describe the fiber fracture mechanism. Then, the machined surface and subsurface are analyzed to establish the relationship between feed speed and fiber deformation depth. Increasing the feed can increase the fiber deformation depth by 3.17 times. Finally, an analysis of the single fiber fracture mechanics is carried out and a force model is created that considers the friction between the tool tip and the fiber during ultrasonic milling. The predictive force model, integrated with the fiber distribution, was validated against experimental results, showing a maximum force error of 5.722 %. This model effectively explains the fracture mechanism of CF/PEEK fibers during ultrasonic milling at the microscopic level.

Experimental Investigation of tool wear, surface roughness during milling of EN 25 steel using coconut based vegetable oil

In this study experimental investigation for utilization of coconut-based vegetable oil as an environmentally sustainable cutting fluid in the milling of EN 25 steel. The study focuses on evaluating the influence of coconut oil as cutting fluid during milling operation. A series of milling experiments were conducted, varying cutting parameters and employing carbide cutting tools, to systematically assess the performance of the coconut-based oil. The results demonstrate that coconut-based vegetable oil exhibits significant potential as a viable alternative to conventional cutting fluids. It not only effectively lubricates the machining process but also substantially reduces surface roughness and tool wear during milling of EN 25 steel workpiece. Advancing eco-friendly machining practices; this research not only contributes to reducing the environmental footprint of machining operations but also offers a promising solution to enhance machining efficiency. The findings presented in this study offer valuable insights for the practical implementation of this sustainable cutting fluid in industrial machining processes, setting the stage for further exploration and adoption of eco-friendly alternatives in the manufacturing industry.

Eco-friendly machining of advanced ceramics: wheel cleaning jet for greenhouse gas reduction

Eco-friendly machining of advanced ceramics: wheel cleaning jet for greenhouse gas reduction

A review of experimental investigations to attain productive and sustainable micro-electrical discharge machining process on metals and superalloys

Purpose This study aims to understand the current production scenario emphasizing the significance of green manufacturing in achieving economic and environmental sustainability goals to fulfil future needs; to determine the viability of particular strategies and actions performed to increase the process efficiency of electrical discharge machining; and to uphold the values of sustainability in the nonconventional manufacturing sector and to identify future works in this regard. Design/methodology/approach A thorough analysis of numerous experimental studies and findings is conducted. This prominent nontraditional machining process’s potential machinability and sustainability challenges are discussed, along with the current research to alleviate them. The focus is placed on modifications to the dielectric fluid, choosing affordable substitutes and treating consumable tool electrodes. Findings Trans-esterified vegetable oils, which are biodegradable and can be used as a substitute for conventional dielectric fluids, provide pollution-free machining with enhanced surface finish and material removal rates. Modifying the dielectric fluid with specific nanomaterials could increase the machining rate and demonstrate a decrease in machining flaws such as micropores, globules and microcracks. Tool electrodes subjected to cryogenic treatment have shown reduced tool metal consumption and downtime for the setup. Practical implications The findings suggested eco-friendly machining techniques and optimized control settings that reduce energy consumption, lowering operating expenses and carbon footprints. Using eco-friendly dielectrics, including vegetable oils or biodegradable dielectric fluids, might lessen the adverse effects of the electrical discharge machine operations on the environment. Adopting sustainable practices might enhance a business’s reputation with the public, shareholders and clients because sustainability is becoming increasingly significant across various industries. Originality/value A detailed general review of green nontraditional electrical discharge machining process is provided, from high-quality indexed journals. The findings and results contemplated in this review paper can lead the research community to collectively apply it in sustainable techniques to enhance machinability and reduce environmental effects.

Performance assessment of vegetable-based additive enriched cutting fluid for eco-friendly machining environment.

The investigation focuses on determining the effects of canola oil-based cutting fluid with three different volume percentages of boric acid additives over the machining forces and surface roughness while turning hardened AISI 1018 mild steel. Experiments were carried out under Taguchi's design of the experiment concept. The minimum quantity lubrication (MQL) technique was followed to minimize the cutting fluid consumption. The homogeneity of the additives dispersed in the fluid has been validated through a zeta potential study. Machining forces and surface roughness were considered as chief machining objectives. The hybrid mathematical model, grey relational analysis (GRA)-artificial neural network (ANN), has been implemented to assess the performance of developed cutting fluid. The results explored that the canola oil cutting fluid with 5 wt% of boric acid additive exhibits lesser cutting forces and surface roughness. The optimal machining parameters identified by the hybrid modeling are 665rpm of cutting speed, 35mm/min of feed rate, and 0.3mm of depth of cut, along with 5 wt% of boric acid composition in cutting fluid. The results explore the 2.677 times improvement in machining objective in comparison with a non-optimal set of parameters. The implementation of hybrid modeling is considered to be a novel attempt to minimize the machining objectives. It has been recorded a negligible error percentage of 0.66% between GRA and ANN prediction.

An Experimental Study on Ultrasonic Vibration-Assisted Turning of Aluminum Alloy 6061 with Vegetable Oil-Based Nanofluid Minimum Quantity Lubrication

Minimum quantity lubrication (MQL) is a potential technology for reducing the consumption of cutting fluids in machining processes. However, there is a need for further improvement in its lubrication and cooling properties. Nanofluid MQL (NMQL) and ultrasonic vibration-assisted machining are both effective methods of enhancing MQL. To achieve an optimal result, this work presents a new method of combining nanofluid MQL with ultrasonic vibration assistance in a turning process. Comparative experimental studies were conducted for two types of turning processes of aluminum alloy 6061, including conventional turning (CT) and ultrasonic vibration-assisted turning (UVAT). For each turning process, five types of lubricating methods were applied, including dry, MQL, nanofluid MQL with graphene nanosheets (GN-MQL), nanofluid MQL with diamond nanoparticles (DN-MQL), and nanofluid MQL with a diamond/graphene hybrid (GN+DN-MQL). A specific cutting energy and areal surface roughness were adopted to evaluate the machinability. The results show that the new method can further improve the machining performance by reducing the specific cutting energy and areal surface roughness, compared with the NMQL turning process and UVAT process. The diamond nanoparticles are easy to embed on the workpiece surface under the UVAT process, which can increase the specific cutting energy and Sa as compared to the MQL method. The graphene nanosheets can produce the interlayer shear effect and be squeezed into the workpiece, thus reducing the specific cutting energy. The results provide a new way for the development of eco-friendly machining.

Performance evaluation of developed new textured tools during turning of AISI 321 material

ABSTRACT Nowadays, productivity enhancement in machining operations in eco-friendly machining environment is a front-end requirement in the machining industries. In general, minimizing tool wear (Vb) and surface roughness (Ra) in machining processes can directly boost productivity. Therefore, the current effort attempts to improve productivity by regulating tool wear and surface roughness in an environmentally friendly machining environment. In this study, innovative textured tools (TT) were created, and the machinability performance of the produced tools was assessed under dry, conventional, and MQL conditions. According to the study’s findings, MQL cooling with TT considerably reduced the cutting temperature (T), Vb, and Ra to maximum values of 13%, 17%, and 29%, respectively, over untextured tools (UT). In addition, it was shown that MQL cooling considerably enhanced turning performance in both tools compared to without cooling and conventional cooling, respectively. Additionally, chip morphology research was done and showed promise using textured tools in MQL conditions as opposed to other machining settings.

Magnetic non-destructive evaluation of microstructural and mechanical characteristics of hardened AISI H13 die steel upon sustainable grinding

This paper describes the potential of non-destructive techniques such as micro-magnetic Barkhausen noise (MBN) to assess the grinding burn flaws in terms of microstructural and mechanical indices of hardened AISI H13 die steel. To overcome this grinding burn issue, minimum quantity lubrication grinding with eco-friendly machining fluids like paraffin oil (PO) and castor oil (CO) was adopted and compared its performance with well-established conventional grinding like wet and dry. Ground surface integrity with castor oil (CO) was found to be significantly improvement in surface quality including lower surface roughness (Rα: 0.23 μm and Rz: 1.83 μm) with uniform surface topography, absence of oxidization and carbonization film, and negligible change in microhardness and microstructure. The reason is strong and uniform anti-friction and anti-wear tribo-film was produced by castor oil, which minimizes heat penetration through limited ploughing and rubbing action. The MBN outcome i.e., root mean square (RMS) has followed a linear relation with microhardness and temperature of the ground sample with a correlation coefficient of 0.993 and 0.981. Besides, lower amplitude and wide peak envelope get shifted towards a higher magnetic field in the MQL-CO grinding caused by poor thermal softening effect on the ground sample, which restricts magnetic domain wall movement and rotation. These outcomes could guide tooling industries for efficient sustainable grinding with faster thermal damage assessment, which helps to minimize production cycle time and back to clean environment.

Carbon emissions and overall sustainability assessment in eco-friendly machining of Monel-400 alloy

With increasing regulations about global warming, environmental pollution, and climate change, reducing carbon emissions from energy-intensive industrial activities routes to sustainable production. Because of its robust thermo-physical qualities at elevated temperatures, Monel 400 alloy is a renowned material for employment in modern aviation, medical tools, and prosthetic parts. Though, its structural stability imparts its low thermal conductivity that causes heat accumulation at the tool-workpiece contact during machining, resulting in tool cutting-edge damage. Many bio-based cutting fluids have been already tried to curtail heat generation and environmental footprints to progress overall machinability. In this endeavor, the effectiveness of dry, minimum quantity lubrication (MQL), cryogenic carbon dioxide (CO2) and Nano based MQL (N-MQL) are evaluated in terms of important sustainability indicator Carbon emission (CE). Multi-walled carbon Nano-tubes (MWCNT) in MQL oil limit the friction at the contact region which in turn reduces the power consumption. The highest CE value was found under a dry (0.0051 Kg-CO2) cutting environment and the lowest with N-MQL (0.0014 Kg-CO2). The sustainability assessment was done for CE with the help of Machine learning (ML) techniques like Decision tree (DT), Naïve Bayes, Random Forest (RF), and Support Vector Machine (SVM). Finally, when the CE levels are discretized while considering industrial needs, SVM paired with the Synthetic Minority Over-sampling approach (SMOTE) demonstrated an accuracy of almost around 100%.

Turning of Al 7075-T6 aerospace alloy under different sustainable metalworking fluid strategies by coated carbide tools

ABSTRACT We primarily need to reduce the consumption of metalworking fluid to ensure sustainable and eco-friendly machining of aerospace alloys. The present study was planned to determine the efficiency of various eco-friendly metalworking fluid strategies for the sustainable turning of aerospace aluminium alloy (Al7075-T6) coated carbide tools under different eco-friendly metalworking fluid strategies namely dry machining, minimum quantity lubrication (MQL), Ranque-Hilsch vortex tube (RHVT), and compressed air. Machining performance was investigated in terms of micro-hardness, tool tip temperature, tool wear, cutting forces, work surface roughness, chip morphology, and energy consumed. Results manifested that MQL and tool coatings can significantly lower tool tip temperature by up to 16%, tool wear by up to 102–106%, average cutting forces by 17–21%, and surface roughness reduced from 11–21% as compared to dry conditions. Abbreviations: BUE, built-up edge; CVD, chemical vapour deposition; CrN, chromium nitride; DCR, disposed chip ratio; DLC, diamond like carbon; DSPR, disposal scrap part ratio; EDS, energy dispersive X-ray spectroscopy; MF, metalworking fluid; MoS2, molybdenum disulphide; MQL minimum quantity lubrication; PVD, physical vapour deposition; RHVT, Ranque-hilsch vortex tube; RPSR, recycled part scrap ratio; RSPR, remanufacturing scrap part ratio; SEM, scanning electron microscopy; SDSS, super duplex stainless steel; TiAlN, titanium aluminium nitride

Investigation on turning process performance during machining of 15-5PH stainless steel material with eco-friendly machining technique

Investigation on turning process performance during machining of 15-5PH stainless steel material with eco-friendly machining technique

Evaluation of Surface Roughness, Tool Wear and Chip Morphology during Machining of Nickel-Based Alloy under Sustainable Hybrid Nanofluid-MQL Strategy

Nickel-based super alloys exhibit high strength, oxidation and corrosion resistance; however, the machining of these alloys is a challenge that can be overcome with effective cooling/lubrication techniques. The use of a minimum quantity lubrication (MQL) technique is limited to lower cutting parameters due to the tremendous heat produced during the machining of Inconel 718. Sustainable and eco-friendly machining of Inconel 718 can be attained using MQL and lubricants based on nanofluids because of their improved heat transfer capabilities. For that purpose, the performance of hybrid nanofluid-MQL is examined. In this novel study, graphene and hexagonal boron nitride (hBN) nanoparticles are reinforced with palm oil and delivered to the machining interface using an MQL setup. The machining experiments are performed under the conditions of dry, wet, MQL and MQL with graphene/hBN deposited in palm oil. The machining performance under selected cutting conditions is assessed by analyzing the surface roughness, tool wear, chip morphology and surface quality of the machined workpiece. A comparison of results showcased the effectiveness of hybrid nanofluid-MQL with improvement in surface finish, reduction in tool wear and favorable chip forms concerning all other machining conditions.

Comparative evaluation of machinability aspects for a sustainable alternative in the machining of Nimonic C-263, a Ni-based superalloy

The primary aim was to recommend a cutting tool that would work well for the eco-friendly machining of Nimonic C-263. The most outstanding performance of the PVD-coated and CVD-coated inserts under dry conditions for sustainable machining has been compared with uncoated inserts under traditional flood cooling and minimum quantity lubrication. A comprehensive investigation was conducted utilizing uncoated, CVD, and PVD-coated commercially available carbide inserts with different cutting environments. The performance of these inserts was compared in terms of surface coarseness, cutting temperature, cutting force, and tool wear with the change of cutting speed and feed. Compared to uncoated inserts, CVD-coated ones were much less effective at lowering surface coarseness and temperature; however, they significantly reduced the cutting force and tool wear at high cutting parameters. Surprisingly, inserts with TiN or TiAlN coating reduced the cutting force required by around 40 percent compared to flood conditions and 16 percent to MQL conditions, respectively. The combination of the thermally resistant TiAlN phase and the outstanding antifriction and anti-sticking properties that TiN possesses may be responsible for this phenomenon.

Sustainable Machining Using Eco-Friendly Cutting Fluids: A Review

The base fluids of eco-friendly cutting fluids should contain some vegetable oil. Due to their eco-friendly, thermal, and tribological qualities, these types of machining fluids are becoming increasingly popular among researchers throughout the world. The authors summarized published research studies on the use of eco-friendly machining fluids (including nanofluids) in various metal removal processes such as turning, milling, grinding, and drilling in this review paper. The impact of several biodegradable oil-based machining fluids on performance metrics such as surface irregularity, machining force, tool wear, power demand, and temperature-induced during the machining process is also explored in this paper. According to the previous and current literature, using an eco-friendly nano machining fluid results in better surface features, less cutting tool wear, lower cutting force, less power required, and lower machining zone temperature during the machining operation due to superior cooling and lubrication properties.

Eco-Friendly Machining of Ti-6Al-4V Alloy: Optimization Using a Hybrid Algorithm (Grey Wolf Algorithm and VIKOR Algorithm)

Eco-Friendly Machining of Ti-6Al-4V Alloy: Optimization Using a Hybrid Algorithm (Grey Wolf Algorithm and VIKOR Algorithm)

Machinability investigation and sustainability analysis of high-pressure coolant assisted turning of the nickel-based superalloy Inconel 718

In recent years, issues related to eco-friendly machining have received more and more attention, leading to the development of new cooling/lubrication techniques. Herein, the paper investigates the effect of high-pressure coolant (HPC) supply on machining performance of Inconel 718 and compare with conventional flood cooling. Significant improvement in tool life, tool wear, tool-chip contact length, material removal volume, and cutting forces have been observed from the outcomes of HPC cooling condition. Moreover, in order to study the environmental impact of machining Inconel 718, a carbon emissions model was established and analyzed for high-pressure and flood cooling conditions, taking into account the carbon emissions from energy, material, cutting tool, and cooling/lubrication fluid. HPC assisted machining was revealed to be better as it makes possible a reduction in overall carbon emissions at higher cutting speeds. In addition, economic analysis for both cutting environments was also carried out. Significant improvement in reduction of the overall machining cost was observed under HPC conditions, especially at higher cutting speeds. In a nutshell, the findings revealed better performance of HPC assisted machining, with regard to machinability, environmental, and economic issues.

Design Modification and Fabrication of Eco-friendly Cleaning Machine

With the growth of technology, researchers are paying greater attention to automated floor cleaning devices in order to make mankind's existence more comfortable. The concept is gaining traction in developed countries, although it is still unpopular because to design complexity, machine costs, and power tariff running costs. A manual floor cleaning machine is proposed in this project. Early in the day, a floor is cleaned with a broom that is controlled by a human hand. This requires a continual movement of the human hand, which is exhausting and time demanding. The goal of this project is to provide a modernised procedure for wet and dry floor cleaning. This equipment is capable of cleaning floors in both dry and wet conditions. It also has a dust storage box. It was decided to create a prototype model that uses a DC drive powered rotary brush with pneumatic controlled dust shifting to assist users in removing waste and maintaining a clean and hygienic environment, thereby avoiding health inequalities and safety concerns for both workers and the general public.

Experimental investigations on the ultrasonic vibration-assisted hard turning of AISI 52100 steel using coated carbide tool

Ultrasonic vibration-assisted turning (UVAT) is a hybrid and eco-friendly machining technique. The UVAT is performed by superimposing high frequency and low amplitude sound waves on the cutting tool in conventional turning. In the present work, a comparative evaluation of the machining performance is presented during conventional turning (CT) and ultrasonically vibration-assisted turning (UVAT) of AISI 52100 hardened steel (62 HRC). Hard turning experiments were performed using a PVD coated TiAlSiN carbide tool considering the effect of process parameters such as cutting speed, feed, and depth of cut. The performance is measured in terms of cutting force and surface roughness. This study observed a better surface finish during of around 8.29% in UVAT when compared to conventional turning. Better surface finish achieved under UVAT could be attributed to better chip breaking and disentanglement of the chip around the tool during UVAT against long curly chips produced that further entangled on the tool while CT. These entangled long curly chips affected the surface finish. On the other hand, no significant difference is observed in cutting force while hard turning under CT and UVAT. This is mostly due to the fact that, although UVAT has less cutting force at slower cutting speeds, but it behaves very identically with CT when cutting speed approaches tangential velocity. This study finds further scope for machinability studies considering the effect of vibrations superimposed on a tool in feed, tangential, and radial directions.