Papers by Keyword: Minimum Quantity Lubrication (MQL)

Abstract: Turning is a mostly used metal removal process in the engineering industry that involves generation of high temperature and cutting forces. Lubrication becomes critical to minimize the effects of this temperature and forces on cutting tool and workpiece. Development of lubricants that are environmental is acquiring importance. For this, a specific study on the application of Minimum Quantity Lubricants as lubricating oil in turning operation is working on. In the present work a specific study on the application of nanosolid boric acid with titanium dioxide (μm) suspended in lubricating oil in turning of EN24steel with carbide tool. SAE-40 is taken as base lubricants and boric acid solid lubricant of (50, 60 80, 538nm) particles size and titanium dioxide (100μm) with different weight percentages taken as suspensions. Variations in cutting forces, tool temperatures, and surface roughness are studied. For this Boric acid nanoparticle were prepared by using High Energy Ball Milling. Ball milling which was carried out for the total duration of 15 hours. The sample was taken out after every 5 hours of milling for characterizing. The nanostructured boric acid particle size measurement was done by X-Ray Diffractometer which was supported by the XRD Scherer’s formula. It was found that the particle size got reduced from 538nm to 63nm for the period of 15 hrs. In present work, the obtained results were predicted by using Regression analysis method for the prediction of output parameters of the lathe machining process is modelled using two input variable parameters such as particle size of boric acid (nm) and the weight percentage of titanium dioxide (μm). Then the model predictions are compared with a set of reliable experimental data available, and it is found So that proposed Regulation analysis gives the results which are well in agreement with experimental results. Keywords: Turn machining, SAE-40 oil, Boric acid, Titanium dioxide, Minimum Quantity Lubrication (MQL), Regression analysis

Abstract: The aim of this study were to evaluate the performance of PVD (TiAlN+TiN) and CVD (TiCN+Al₂O₃+TiN) coated inserts in end milling of EN–31 hardened die steel of 43±1 HRC during dry and MQL (Minimum quantity lubrication) machining. The experiments were conducted at a fixed feed rate, depth of cut and varying cutting speed to measure the effect of cutting speed on cutting force and tool wear of CVD and PVD-coated inserts. The performance of CVD and PVD-coated inserts under dry and MQL condition by measuring the tool wear and cutting force were compared. During cutting operation, it was noticed that PVD inserts provide less cutting force and tool wear as compared to the CVD inserts under both dry as well as the MQL condition because PVD inserts have a thin insert coating and CVD inserts have a thick insert coating, but PVD inserts experience catastrophic failure during cutting operation whereas CVD inserts have a capability for continuous machining under different machining. Tool wear has measured by SEM analysis. The result shows that MQL machining provides the optimum results as compared to the dry condition. MQL machining has the ability to work under high cutting speed. As the cutting speed increases the performance of dry machining was decreased, but in MQL machining, the performance of the inserts was increased with increases of cutting speed. MQL machining generates less cutting force on the cutting zone and reduces the tool wear which further increase the tool life.

Abstract: Cutting fluid plays an important role in machining processes to achieve dimensional accuracy, reduce tool wear, and improve tool life. Use of flood cooling conventionally used in machining is not cost effective and consumption of huge amount of cutting fluids is not health and environmental friendly. Therefore, one of the alternatives is to use minimum quantity of lubrication (MQL) in machining process. MQL is eco-friendly and has economical advantage on manufacturing cost. Study of the effects of MQL on burrs and aspect ratio should be carried out because burrs and aspect ratio are important issues in microdrilled parts used as microfluidic channels in bio-medical applications. In case of micromachining, flood cooling is not recommended to avoid any possible damage of the microstructures. As a result alternative solutions are sought. This paper investigates and compares burrs and aspect ratio in dry microdrilling and microdrilling with the presence of MQL on aluminium alloy 1100. The relationship among tool diameter, feed rate, and spindle speed on the area affected by burrs and drilled hole aspect ratio are analysed. The values of aspect ratio for both conditions show that there is slight improvement on aspect ratio in MQL over dry drilling. MQL has significant influence on affected area by burrs. It is observed that low spindle speed, high feed rate, and bigger drill diameter should be used along with MQL to reduce burrs.

Abstract: Producing good surface integrity is one of the main challenges of the machining industry. The increase of the utilization of minimum quantity lubrication (MQL) in order to reduce the amount of lubrication induced a lack of understanding of the physics behind the residual stress generation. Residual stress in the machined surface and subsurface is affected by materials, machining conditions, and tool geometry. These residual stresses could affect the service qualify and component life significantly. Residual stress can be determined by empirical or numerical experiments for selected configurations, even if both are expensive procedures. This paper presents a hybrid neural network that is trained using Simulated Annealing (SA) and Levenberg-Marquardt Algorithm (LM) in order to predict the values of residual stresses in cutting and radial direction after the MQL face turning process accurately. First, SA is used to train the weight and bias values of the ANN after which LM is used to fine tune the values trained by SA. Then, based on the predictions, an optimization procedure, using Genetic Algorithm (GA), is applied in order to find the best cutting conditions. At each generation, GA suggests a population of inputs that are then sent to the trained ANN in order to predict the residual stresses. The objective is to find the optimal inputs that minimize the tensile stress on the machined surface.

Abstract: This objective of this article is to present a new technique of nanofluids/MQL in high speed milling by using MWCNTs. In the past, studies have shown the MQL process can improve tool life and surface accuracy in high speed cutting. The purpose of using carbon nanotubes is to increase the thermal conductivity of cutting fluid and to reduce the temperature during the cutting and decrease the thermal wear of tool. The proposed study is to investigate the characterization of the MWCNTs/ nanofluids combined with MQL during the high speed milling of AISI 1050 and AISI P21 experimentally. The Taguchi robust design was also used to optimize the parameters of nozzle with respect to tool feed direction, such as spraying distance, angle of ejection, and relative locations for improving the MWCNTs/MQL cutting effect. Experimental results showed the MWCNTs/ nanofluid had the benefits of improving surface roughness and reducing wear of tool in high speed milling. The results were compared to dry cutting, and wet cutting in detail.

Abstract: Surface integrity, such as surface roughness and residual stress, is an aspect of surface quality on machined parts. Residual stress in the machined surface and subsurface is affected by materials, machining conditions, and tool geometry. These residual stresses could affect the service qualify and component life significantly. Residual stress can be determined by empirical or numerical experiments for selected configurations, even if both are expensive procedures. This paper presents a hybrid neural network that is trained using Simulated Annealing (SA) and Levenberg-Marquardt Algorithm (LM) in order to predict the values of residual stresses in cutting and radial direction after the MQL face turning process accurately. To verify the performance of the proposed approach, the predicted results are compared with the results obtained by training an ANN using SA and LM separately. The results have shown that the hybrid neural network outperforms SA and LM in predicting machining induced surface integrity that is critical to determine the fatigue life of the components.

Abstract: In the present research, an attempt has been made to experimentally investigate the cutting forces in hard milling of H13 steel with coated carbide tools under dry, MQL (minimum quantity lubrication) and MQCL (minimum quantity cooling lubrication) cutting conditions. Based on Taguchis method, four-factor (cutting speed, feed per tooth, radial depth of cut, and axial depth of cut) four-level orthogonal experiments were employed. It is found that the periodical fluctuation of the cutting forces caused by the variation of the undeformed chip thickness with the entry/exit of the cutting edge is an essential feature of the hard milling process. The empirical models for cutting forces are established, and ANOVA (analysis of variance) indicates that the quadratic models can well express the relationship between cutting forces and cutting parameters.

Abstract: In the current paper, some aspects regarding the quality of the surface machined under different lubrication conditions is being assessed: cutting under a jet of cutting fluid, minimum quantity lubrication cutting, dry cutting. The objective was to assess the results obtained after MQL cutting in comparison with dry cutting and cutting under a jet of cutting fluid. The variables of the cutting regime were the feed rate and the type of milling (climb and conventional). This study has an important ecological impact over the use of cutting fluids.

Abstract: In recent years, the energy efficiency improvement has become significant due to rapid consumption of world's energy resources. Particularly in manufacturing industry, hard turning process is one of the most fundamental metal removal processes that require huge power consumption and it could be improved in term of energy usage by many alternatives. At the same time, the improvement in term of machined surface quality is become a need since it would reflect appearance, performance and reliability of the products. As for example in the CNC machining field, one of the solution for this issue is by increasing the effectiveness of the existing lubrication systems as it could improve the machined surface quality, reduce the power required to overcome the friction component in batch production of machining process and reduce the oil consumption. The effectiveness of the lubrication system could be improved by introducing the nanobase lubrication system for much less power consumption as the rolling action of billions units of nanoparticle in the tool chip interface could reduce the cutting forces significantly. In this research work, the possibility of using SiO₂ nanobase lubrication system is investigated to reduce the machining power consumption as well as improving surface quality in hard turning process of AISI4140.

Abstract: This paper presents an analytical approach to predict the machining force, temperature and residual stress under minimum quantity lubrication (MQL) condition. Both the lubrication and cooling effects are considered to change the tribological and thermal properties in the modified Oxleys model, which is capable to predict the cutting force and temperature in MQL machining directly from cutting conditions. The machining-induced residual stress is predicted by modified McDowell hybrid algorithm. The predicted cutting forces and residual stresses are verified by orthogonal cutting tests for C45 steel and TC4 alloy steel.