Search

In every conventional machining process interaction of tool interface with that of workpiece results in high temperatures and thermal distortions. Such distortions may lead to change in the surface morphology of the machined workpiece, thus harming the desired finishing of the product. The use of nanofluids as a coolant over traditional cutting fluid help in minimising such problems. In continuation to the past research on nanofluids, the use of hybrid nanofluids in machining operations is attracting the researchers. The synthesis of hybrid nanofluid is done by dispersing two different nanoparticle in traditional heat transfer fluid which can be seen as efficient coolant and lubricant. The hybrid nanofluids are found favourable in terms of thermo physical properties, heat transfer rate and stability. This has led to increase in research on hybrid nanofluids over mono type nanofluids. This paper summarises the application of hybrid nanofluids by various researchers in different machining operations namely turning, grinding, and drilling. Furthermore, the paper deals with the tribological properties of different hybrid nanofluid and the temperature control in the machining operations. [ABSTRACT FROM AUTHOR]

In the manufacturing industry, during machining, the conventional cutting fluid plays a vital role; however, extravagant use of cutting fluids due to its disposal affects the environment badly. Nowadays, due to these advantages of conventional cutting fluids, alternative methods of conventional cutting fluids or alternative methods are preferred. One of the most preferred methods may be the minimum quantity lubrication technique with conventional or nanoparticle-enriched cutting fluids. The present paper has a compilation of the investigations based on MQL application in different machining processes such as turning, milling, grinding, and drilling. The machining also involves hard-to-machine alloys. The paper discusses cryogenic MQL in brief and opens the domain for work in future. The purpose of this paper is to provide a quick reference for researchers working on the practical use of MQL lubricants with nanopowders dissolved and their application in machining for different materials. [ABSTRACT FROM AUTHOR]

Surface roughness is considered as an important measuring parameter in the machining industry that aids in ensuring the quality of the finished product. In turning operations, the tool and workpiece contact develop friction and cause heat generation, which in turn affects the machined surface. The use of cutting fluid in the machining zone helps to minimize the heat generation. In this paper, minimum quantity lubrication is used in turning of AISI 304 steel for determining the surface roughness. The cutting fluid is enriched with alumina nanoparticles of two different average particle sizes of 30 and 40 nm. Among the input parameters chosen for investigation are cutting speed, depth of cut, feed rate, and nanoparticle concentration. The response surface approach is used in the design of the experiment (RSM). For the purpose of estimating the surface roughness and comparing the experimental value to the predicted values, three machine learning-based models, including linear regression (LR), random forest (RF), and support vector machine (SVM), are utilized in addition. For the purpose of evaluating the accuracy of the predicted values, the coefficient of determination (R2), mean absolute percentage error (MAPE), and mean square error (MSE) were all used. Random forest outperformed the other two models in both the particle sizes of 30 and 40 nm, with R-squared of 0.8176 and 0.7231, respectively. Thus, this study provides a novel approach in predicting the surface roughness by varying the particle size in the cutting fluid using machine learning, which can save time and wastage of material and energy. [ABSTRACT FROM AUTHOR]

In machining operations, the application of cutting fluids has been of prime importance for the extraction of heat from rake surfaces, ease of removal of the chips and reduction of friction at the chip–tool interface. These three objectives are achieved by the supply of suitable conventional cutting fluid at the machining zone using different techniques. However, the misuse of these fluids and their wrong disposal methods were found to have an adverse effect on the environment and health of human. To reduce the usage of conventional cutting fluid, minimum quantity lubrication (MQL) technique has been emerged as an alternative means in the last few years, leading to better eco-friendly. Further, to increase the sustainability of MQL technique, it becomes necessary to use an appropriate exceptional nanostructured material with MQL that could be an effective cutting fluid (i.e. nanocutting fluids) with better tribological and thermophysical properties, and might be helpful in addressing the eco-friendly problem to a great extent. Therefore, the present paper focuses on the review of important published works related to the use of mono/hybrid nanocutting fluids with MQL technique at various processing parameters in different metal cutting operations. Most of the studies have shown a significant reduction in cutting forces, temperature at cutting zone, tool wear, and friction coefficient, and considerable improvement in surface quality by the addition of mono/hybrid nanoparticles enriched cutting fluid in MQL technique as compared to dry as well as wet machining processes. Further, the paper discusses the future scope in the area of hybrid nano-cutting fluids in different machining processes. [ABSTRACT FROM AUTHOR]

In any metal cutting operation, the cutting fluid plays a vital role by cooling the surface of the work piece and the cutting tool, removing chips from the cutting zone and by lubricating the tool–work piece interface. However, misuse of the cutting fluid and wrong methods of its disposal can affect human health and the environment badly. Also, it accounts for 16–20% of the total cost of manufacturing in the production industry. Among various techniques available on application of the coolant, researchers, of late, have been focussing on Near Dry Machining (NDM)/Minimum Quantity Lubrication (MQL) as it minimizes the use of coolant by spraying the mixture of compressed air and cutting fluid in an optimized manner instead of flood cooling. The MQL technique has proved to be suitable because it complies with the requirements of ‘green’ machining. This paper presents a review of the important research papers published regarding the MQL-based application of mineral oils, vegetable oils and nanofluid-based cutting fluids for different machining processes, such as, drilling, turning, milling and grinding, etc. The paper explains the mechanism of the MQL technique. In a systematic manner, the present work also discusses its effect on the performance parameters of different machining processes. Most of the experimental studies have shown that application of MQL produces surface better than dry machining and similar to that as produced under wet machining. Its application also reduces cutting forces, cutting zone temperature, tool wear, friction coefficient in comparison to dry and wet machining. Therefore, MQL technique has proved to be a viable alternative to the flood lubrication under similar performance parameters. [ABSTRACT FROM AUTHOR]

A colloidal mixture of nanometer-sized (<100 nm) metallic and non-metallic particles in conventional cutting fluid is called nanofluid. Nanofluids are considered to be potential heat transfer fluids because of their superior thermal and tribological properties. Therefore, nano-enhanced cutting fluids have recently attracted the attention of researchers. This paper presents a summary of some important published research works on the application of nanofluid in different machining processes: milling, drilling, grinding, and turning. Further, this review article not only discusses the influence of different types of nanofluids on machining performance in various machining processes but also unfolds other factors affecting machining performance. These other factors include nanoparticle size, its concentration in base fluid, lubrication mode (minimum quantity lubrication and flood), fluid spraying nozzle orientation, spray distance, and air pressure. From literature review, it has been found that in nanofluid machining, higher nanoparticle concentration yields better surface finish and more lubrication due to direct effect (rolling/sliding/filming) and surface enhancement effect (mending and polishing) of nanoparticles compared to dry machining and conventional cutting fluid machining. Furthermore, nanofluid also reduces the cutting force, power consumption, tool wear, nodal temperature, and friction coefficient. Authors have also identified the research gaps for further research. [ABSTRACT FROM PUBLISHER]

The enormous use of cutting fluid in machining leads to an increase in machining costs, along with different health hazards. Cutting fluid can be used efficiently using the MQL (minimum quantity lubrication) method, which aids in improving the machining performance. This paper contains multiple responses, namely, force, surface roughness, and temperature, so there arises a need for a multicriteria optimization technique. Therefore, in this paper, multiobjective optimization based on ratio analysis (MOORA), VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), and technique for order of preference by similarity to ideal solution (TOPSIS) are used to solve different multiobjective problems, and response surface methodology is also used for optimization and to validate the results obtained by multicriterion decision-making technique (MCDM) techniques. The design of the experiment is based on the Box–Behnken technique, which used four input parameters: feed rate, depth of cut, cutting speed, and nanofluid concentration, respectively. The experiments were performed on AISI 304 steel in turning with minimum quantity lubrication (MQL) and found that the use of hybrid nanofluid (Alumina–Graphene) reduces response parameters by approximately 13% in forces, 31% in surface roughness, and 14% in temperature, as compared to Alumina nanofluid. The response parameters are analyzed using analysis of variance (ANOVA), where the depth of cut and feed rate showed a major impact on response parameters. After using all three MCDM techniques, it was found that, at fixed weight factor with each MCDM technique, a similar process parameter was achieved (velocity of 90 m/min, feed of 0.08 mm/min, depth of cut of 0.6 mm, and nanoparticle concentration of 1.5%, respectively) for optimum response. The above stated multicriterion techniques employed in this work aid decision makers in selecting optimum parameters depending upon the desired targets. Thus, this work is a novel approach to studying the effectiveness of hybrid nanofluids in the machining of AISI 304 steel using MCDM techniques. [ABSTRACT FROM AUTHOR]