Analysis of Surface Roughness during Machining of Hardened AISI 4340 Steel using Minimum Quantity lubrication

Analysis of Surface Roughness during Machining of Hardened AISI 4340 Steel using Minimum Quantity lubrication

Available online at www.sciencedirect.com ScienceDirect Materials Today: Proceedings 4 (2017) 3627–3635 www.materialstoday.com/proceedings 5th Inte...

494KB Sizes 3 Downloads 18 Views

Recommend Documents

No documents
Available online at www.sciencedirect.com

ScienceDirect Materials Today: Proceedings 4 (2017) 3627–3635

www.materialstoday.com/proceedings

5th International Conference of Materials Processing and Characterization (ICMPC 2016)

Analysis of Surface Roughness during Machining of Hardened AISI 4340 Steel using Minimum Quantity lubrication Sanjeev Kumar*, Dilbag Singh, Nirmal S. Kalsi Department of Mechanical Engineering ,Beant College of Engineering and Technology, Gurdaspur, Punjab - 143521, India

Abstract Trends of machining hardened steel are increasing in manufacturing industry due to its advantages in surface quality over grinding and other finishing process. One of the major benefits of hard turning is attaining better surface quality with high dimensional accuracy. However, large amount of heat generation during hard turning to affects the machining performance. The application of lubricants during the machining are used to control the temperature. The use of conventional cutting fluids have become more problematic in terms of health and environmental pollution. Minimization of cutting fluid will lead to costeffectiveness in overall machining. Therefore, the aim of this research work is to investigate the role of minimum quantity lubrication (MQL) technique on surface quality in turning of hardened AISI 4340 steel with CBN tools. The cutting speed, feed rate, and nose radius and workpiece hardness are selected as process parameters during investigations. The mathematical model of surface roughness is developed using second order regression analysis. Analysis of Variance (ANOVA) results show that MQL helps in improving the surface quality as compared to dry and wet conditions in turning. ©2017 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of Conference Committee Members of 5th International Conference of Materials Processing and Characterization (ICMPC 2016). Keywords: CBN, Hard turning, MQL, Nose Radius, Surface roughness;

1. Introduction Superior surface quality and long life of the finished products are the advantageous features to meet the challenges of this era in machining processes. Therefore, to achieve this, it is required to optimize the cost, quality and

* Corresponding author. Tel.: +91-75893-44561; fax: +91-1874-221463. E-mail address:[email protected] 2214-7853©2017 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of Conference Committee Members of 5th International Conference of Materials Processing and Characterization (ICMPC 2016).

Sanjeev Kumar et al / Materials Today: Proceedings 4 (2017) 3627–3635

3628

Nomenclature Ra v f h r DF

Surface roughness (µm) Cutting Speed (m/min) Feed rate(mm/rev) Workpiece hardness (HRC) Tool nose radius (mm) Degree of freedom

continuous advancement in machining technology that leads to the growth in novel techniques of machining. Machining of hardened materials is one of them. Hard turned materials are preferred because of their high wear resistance and better surface quality. In recent years, the hard turning has gained significant attentions in the metal cutting process as it can apparently replace the traditional process such as grinding and other finishing processes. When compared to grinding, the hard turning process on nearly net shape parts can lower set-up cost by producing multiple surfaces in a single set-up. In addition, hard turning requires shorter tool change time, consume low energy and are environmental-friendly, thereby shows potential cost-effective benefits. Moreover, hard turning has a broad range of applications in manufacturing industries such as tool and die, automobile, aircraft. The major problem during hard turning is the high heat generation due to friction between chips-tool interface that cause higher wear rate, low surface quality and shorter tool lives. Therefore, tool life and surface quality of the components can be improved by controlling the temperature of cutting zone. Traditionally it is being controlled by using cutting fluids. The role of cutting fluids used in machining processes is to reduce friction at the tool-workpiece interface and remove the chip. Procurement, storage and disposals that involve expenses are the main problems associated with the cutting fluids. In addition, cutting fluids have to obey with environmental legislation such as (Occupational Safety and Health Administration) OSHA as well [1]. Therefore, in the order to decrease the utilization of cutting fluids without reducing machining performance, many researchers made attempts to investigate the effects of using minimum quantity lubrication (MQL) during machining. Varadarajan et al. analysed that machining performance found superior with the use of minimum amount of cutting fluid when compared to dry and wet conditions. They also observed during MQL, a major segment of the fluid is evaporated and remaining carried away by the work and chip that cause little contamination in the surroundings. In addition, temperature decreases significantly at the cutting zone with the use of MQL when compared with dry and wet conditions [2]. Diniz et al. analysed that the use of compressed air with the MQL facilitates in getting better surface quality and tool life during machining of SAE 52100 hardened steel with CBN tool [3]. Khan and Dhar observed a significant drop in temperature at the cutting area with the use of vegetable oil-based MQL supply during the machining of AISI 1060 steel. The results indicate that due to reduction in temperature the dimensional accuracy and surface quality are enhanced [4]. Dhar et al. investigated that tool life and surface quality are improved by the application of MQL during the machining of AISI 4340 steel, when compared to dry and conventional machining with flooded cooling. The surface finish and dimensional accuracy are improved mainly due to a reduction of wear [5]. Choudhury et al. observed that the cutting forces are decreased from 5 % to 20% with the use of MQL supply during the machining. The results shows that axial component of force decreased more than normal component and surface finish improved due to decrease in tool wear [6]. Kumar and Ramamurthy examined that the machining performance of cutting tools are superior during MQL supply when compared to dry turning and traditional wet turning. They also observed during MQL supply the cutting performance depend on parameters such as nozzle pressure, the number of pulses and the amount of cuttingfluid in each pulse [7]. Tasdelen et al. observed small contact length between tool–chip with the use of the minimum quantity of liquid along with compressed the air during the machining. It results better surface quality due to very short engagement times and decrease in friction in the sliding region [8]. Khan et al. analysed that the significant improvement in tool life and surface quality during machining of AISI 9310 steel under the application of a minimum quantity of vegetable oil based cutting fluid. They observed that

Sanjeev Kumar et al/ Materials Today: Proceedings 4 (2017) 3627–3635

3629

with the use of MQL the back surface of chips appears brighter and smoother. It indicates that the reduction in temperature as results in a decrease in tool wear and surface roughness [9]. Hwang and Lee investigated that the surface roughness and cutting forces are significantly reduced by the use of MQL supply during the machining of AISI 1045 steel when compared to the wet condition [10]. Chowdhury and Dhar analysed that surface quality obtained by the application of MQL is better than dry condition during machining of hardened medium carbon steel. [11]. Kuarh and Sadaiah analysed that cutting forces are affected by both cutting speed and environmental conditions during the machining process. The cutting forces are found lesser during MQL supply when compared with dry and wet environment conditions. The result shows the minimum value surface roughness (Ra) 0.9 µm during MQL supply whereas 1.2 µm for dry machining and for wet turning 1.1 µm [12]. Lohar and Nanavaty reported that cutting forces are decreased and surface finish improved with the use of MQL supply during the machining of hardened steel AISI 4340. They concluded that the cutting temperature is less for 20 ml/min as compared to 10 ml/min during MQL supply [13]. Hada and Sadeghi reported that cutting performance is improved by the application of MQL supply during the machining of AISI 4140 steel when compared to dry and flooded conditions. They also analyzed that position of MQL nozzle as relevant parameters during the machining process [14]. Ekinovic et al. investigated that cutting forces are reduced to 16% by MQL supply during the machining of aluminium bronze. It is due to a decrease of friction between chip-tool interface. They also observed that MQL helps in energy saving due to decrease in cutting forces during machining [15]. Da Silva et al. reported that the machining performance with vegetable-based fluid (Boron, Chlorine and Nitrite free) delivers with MQL provide comparable performance to that of the dry condition during machining of SAE 1050 steel [16]. Nguyen et al. observed longer tool life during the hard turning of 9CrSi steel by (MQL) of peanut oil when compared with dry and emulsion MQL [17]. Naigade et al. observed that surface finish improved by the application of MQL during the machining of hardened alloy steel AISI 4340 (45 HRC) with CBN insert. In addition, the cutting forces are significantly affected by depth of cut and cutting environment during the machining [18]. Hadi investigated that optimal surface quality achieved at cutting fluid supplies 200 ml/h, feed rate 0.08 mm/rev and cutting speed 200 m/min during machining of AISI H13 steel [19]. Lawal et al. concluded that the surface roughness, tool wear and thrust force are reduced by application of vegetable based MQL supply during machining of AISI 9310 low alloy steel. In addition, vegetablebased MQL supply is environmental friendlily and it reduced the cost of machining. The results indicate that the developed model useful for achieving desired surface roughness close to the tolerance limits by fixing the cutting parameters during machining [20]. Shihab et al. analyzed the effect of different cutting parameters on cutting force using Castrol oil as lubricant during hard turning of alloy steel AISI 52100. They developed mathematical models of cutting force using the response surface methodology (RSM). The results indicate that cutting forces are influenced maximum by depth of cut [21]. Beatrice et al. developed the model for surface quality based upon artificial neural network (ANN) when hard turning of AISI H31 steel with MQL [22]. Robinson et al. reported that effect of an auxiliary pulsing jet of water on the top side of the chip in addition to MQL supply during hard turning of AISI 4340 steel (45 HRC). They noticed the presence of a supplementary high speed of pulsing jet of water at the tool work boundary improve the chip curl. Also, it reduces tool-chip contact length and provide better rake face lubrication at the tool-chip interface [23]. Kedare et al. observed the 27% improvement in surface quality during the use of MQL supply during milling of mild steel (15HRC). The results also indicate that that MQL supply during machining is an cost-effective and environmental friendly technique[24]. Dureja et al. observed the optimal value of surface quality at 150 ml/h of cutting fluid supplied with cutting speed (23 m/min) and feed rate (0.07 mm/rev) while machining AISI 202 steel with coated carbide tools [25]. Saad et al. analysed longer tool life was observed at 50 ml/h of lubricant supplied during machining of AISI 420 steel (47-48 HRC) [26]. Therefore it is clear from the above mentioned literatures that MQL is an alternative to wet machining. Although, some studies have been carried out by using MQL supply during hard turning. Also very few studies have been reported regarding the use of MQL during hard turning of AISI 4340 steel at hardness level below 45 HRC. Since the hard turning involve machining at hardness levels above 45 HRC. Therefore there is need to study the use of MQL supply during hard turning of AISI 4340 steel at higher hardness levels i.e. above 45 HRC. Hence, in this research work perfomance of hard turning using CBN tools will be investigated using MQL at different levels of hardness and comparison is made with dry and wet conditions during hard turning of AISI 4340 steel.

Sanjeev Kumar et al / Materials Today: Proceedings 4 (2017) 3627–3635

3630

2. Experimental Detail In this research work, AISI 4340 alloy steel is selected as the workpiece material. It is being used in manufacturing industries where high tensile and yield strength are required. Components made of AISI 4340 steel are widely used in aircraft, automotive and general engineering industries e.g. rotor shaft, propeller shafts, connecting rods, gear shafts, and other automobile parts. The workpiece is heat-treated to obtain high wear resistance. Using standard methods of heat treatment. The hardened specimens were in five hardness levels at 40, 45, 50, 55, and 60±2 HRC. After heat treatment, microscopic examinations of the specimens were carried out. The micrographs of specimens at different hardness level are shown in Fig 1.

Figure 1 Micrograph of heat–treated AISI 4340 steel at 500X.

The micrographs show that fine tempered martensite was observed in the samples 1, 2, 3 and 5 whereas sample 4 shows the bainitic structure. The goemetry of workpiece material (65 mm diameter and 350 mm length) is selected as per ISO 3685 standards 1993 [27]. The alloy composition in AISI 4340 steel is given in Table 1. The inserts grade K5625 having 65% CBN content with ISO geometry SNGA 431S0425MT and tool holder with (ISO) MSSNR2525M12 of Kennametal are selected for this study. Table 1 Chemical percentage of element in AISI 4340 steel Elements % AISI 4340 steel

C 0.42

Mn 0.58

Si 0.27

S 0.024

P 0.026

Cr 1.06

Ni 1.47

Mo 0.22

Fe 95.93

In this experimental work, four parameters namely cutting speed (v), feed rate (f), nose radius(r) and workpiece hardness (h). Five levels of each variable are taken. The process variables and their levels are shown in Table 2. Table 2 Process variables and their levels Factors

Level-1

Level-2

Level-3 125

Level-4 150

Level-5

A: Cutting Speed (v), m/min

75

100

175

B: Feed Rate (f), mm/rev

0.1

0.125

0.15

0.175

0.2

C: Workpiece hardness (h), HRC

40

45

50

55

60

D: Nose Radius (r), mm

0.2

0.4

0.8

1.2

1.6

Sanjeev Kumar et al/ Materials Today: Proceedings 4 (2017) 3627–3635

3631

The design of experiment plays a vital role in performing the experiments with the available resources. Therefore, the central composite design of response surface method was selected to reduce the number of experiments. This method is useful for developing, analysing, improving and optimizing the products process that provides an overall perspective of the system response within the design space [28]. According to the central composite design, 30 experiments were performed. All the experiments were performed at a constant depth of cut of 0.2 mm. The surface roughness (Ra) is chosen as a response variable. A high precision HMT made lathe was used for experimentation. The schematic diagram for MQL is as shown in Fig 2(a). Pressure valve Flow Control Valve

Pressure

Flow Control Valve

Nozzle Mixture

Compresso

Cutting oil

(a)

(b)

Fig. 2 (a) Experimental set-up for MQL supply (b) Surface Roughness Tester

The surface roughness (Ra) of the AISI 4340 steel was measured with Mitutoyo made surface roughness tester as shown in Fig 2(b). The average of three measurements was used as a response value. Before the actual test, the trial run has been performed to get minimum surface roughness against the different rate of cutting fluids supply. The trial run was carried out at cutting speed 125 m/min, feed rate 0.15 mm/rev, tool nose radius 1.2 mm and at the hardness of workpiece 45 HRC, 50HRC and 55 HRC. The cutting fluid through the spray gun along with compressed air at 6 bar. It was found that at 100 ml/hr flow rate, the surface roughness observed to be minimum. 4. Results and Discussion The analysis of variance (ANOVA) was helpful to study the significance of the process parameters on the surface roughness. The first order models were not adequate and therefore second order models were generated as given in Table 3, 4 and 5. The multiple regression coefficient of the model for dry, wet and MQL assisted machining are estimated as 0.9854, 0.9839 and 0.9859 respectively. The calculated values of F- ratio for the model are greater than the table values of the F-ratio as shown in ANOVA tables 3, 4 and 5 the model is adequate at 95% confidence level to represent the relationship between the response and process parameters during hard turning. Table 3. Analysis of variance for dry turning Source

DF

Sum of Square

Mean Square

Fcal

p-value Prob ˃ F

Remarks

Model Residual error Lack-of fit

13 16 11

18.72 0.28 0.24

1.44 0.017 0.022

83.12 2.96

˂ 0.0001 0.1207

Pure error Total

5 29

0.037 19

0.0073

-

-

Significant NonSignificant -

Rsq = 0.9854

Rsq(adj. ) = 0.9736

Rsq(pred.) = 0.9383

Sanjeev Kumar et al / Materials Today: Proceedings 4 (2017) 3627–3635

3632

The calculated lack-of-fits for the surface roughness models are less than the tabulated value for the lackof fit at 95% confidence level. Therefore, it concluded that cutting speed, feed rate, workpiece hardness and tool nose radius have significant effect on surface roughness Ra, which implies that all model are adequate. The experimental results were used to compute the mathematical models for each machining conditions. The proposed second-order models developed from the functional relationship using RSM methods as follows: Table 4. Analysis of variance for wet turning Source

DF

Sum of Square

Mean Square

Fcal

p-value Prob ˃ F

Remarks

Model Residual error Lack-of fit

14 15 10

18.61 0.30 0.27

1.33 0.020 0.027

65.45 4.29

˂ 0.0001 0.0608

Pure error Total

5 29

0.032 18.91

0.00636

-

-

Significant NonSignificant -

Rsq = 0.9839

Rsq(adj. ) = 0.9689

Rsq(pred.) = 0.9098

Table 5. Analysis of variance for MQL turning Source

DF

Sum of Square

Mean Square

Fcal

p-value Prob ˃ F

Remarks

Model Residual error Lack-of fit

14 15 10

16.22 0.23 0.21

1.16 0.015 0.021

74.80 3.77

˂ 0.0001 0.079

Pure error Total

5 29

0.027 16.45

0.0054

-

-

Significant NonSignificant -

Rsq = 0.9859

Rsq(adj. ) = 0.9727

Rsq(pred.) = 0.9219

Dry hard turning Ra = + 0.92 – 0.264 *A + 0.161 * B + 0.054 * C - 0.292 * D + 0.354 * A* B – 0.200 * A * C – 0.554 * A * D – 0.446 * B * D + 0.160 * C * D + 0.164 * A2 + 0.047 * B2 + 0.162 * C2 +0.406 * D2 Wet hard turning

(i)

Ra = +0.67 – 0.43 *A + 0.27 *B + 0.01*C – 0.21*D + 0.12*A*B – 0.31* A*C – 0.38 *A*D + 0.18*B*C – 0.39*B*D + 0.19*C*D + 0.27*A2 +0.14 *C2+0.30 *D2 MQL based hard turning

(ii)

Ra = + 0.63- 0.40*A+0.27*B+0.098*C-0.22*D+0.12*A*B-0.29*A*C-0.35*A*D +0.17*B*C- 0.37*B*D + 0.16*C*D +0.24A2 + 0.11*B2 +0.14 *C2 +0.29*D2 (iii) The developed mathematical models are used for predicting the relationship between process parameters and surface roughness as shown in Fig (3 and 4). Fig 3 (a) indicate that that surface roughness decrease with increase in cutting speed. At cutting speed (75 m/min) the surface roughness observed to be maximum and it start to decrease with an increase in cutting speed. It is because with increase in cutting speed the friction is reduced that are accompanied by force decrease lead to a more stable process and better surface quality.

Sanjeev Kumar et al/ Materials Today: Proceedings 4 (2017) 3627–3635

3633

In addition the with increase in the speed the time for which the chip remains in contact with tool decreases and the heat is not carried away by the chip. It is one of the primary sources of carrying generated heat. Moreover when applied lubricant in flooded conditions at coolant may not have enough time to remove heat accumulated at cutting zone. On the other hand, under MQL the cutting fluid is supplied at high pressure and high velocity that penetrates into the tool-chip interface that causes reduction in friction and lead to better surface quality. Kumar and Ramamoorthy [7] have reported a similar study. The surface quality is also affected by the feed rate. The variation of surface roughness with feed rate is shown in Fig 3(b) it is observed from the figure that the surface roughness increases with rise in feed rate. It is beacuse with increase in feed rate large amount of heat generated at the cutting zone due to high material removal rate. It results in an increase in tool wear which in turn increases the surface roughness.

(a)

(b)

Fig 3. Variation of surface roughness with (a) Cutting Speed (b) Feed Rate

In addition when using MQL during the machining, it provides cutting fluids at high velocity with injection pressure. The high-velocity cutting fluids facilitates better penetration of the cutting fluid on impact to the root as well as the underside of the chip facilitates its passageway through the tool–chip interface. Which results in the decrease of friction it leads to decrease in cutting zones temperature and hence surface quality is improved when it compared with dry and wet machining. Similar analysis has been made by Varadarajan et al.[2].

(a)

(b)

Fig 4. Variation of surface roughness with (a) Workpiece hardness (b) Nose radius

Sanjeev Kumar et al / Materials Today: Proceedings 4 (2017) 3627–3635

3634

It has observed from the Fig 4(a) that high surface roughness observed at the starting when workpiece hardness is 40 HRC. It starts decreasing reaches a minimum values at 55 HRC and then again increases after 55 HRC. As high heat generation due to workpiece leads to plastics deformation which results in a decrease in cutting forces and hence surface quality improve. However, after 55 HRC the surface roughness increases rapidly, it is due to the facts that high hardness leads to tool wear in the presence of various hard carbides particles of steel. The same have been reported by, Derakhshan and Akbari [29] also by Poulachon et al. [30]. Fig 4(b) shows the variations of surface roughness with tool nose radius. It is observed that at tool nose radius 0.2 mm the surface roughness found to be very high. It is because when machining with small nose radius, the area of contact available for conduction between the tool and workpiece is small. Hence, the reduction of the heat conduction area promotes local temperature rise along the cutting edge as results surface roughness increase. As and when nose radius increases the surface roughness decreases and reaches a critical value and with further increase in tool nose radius the surface roughness increase. In addition, it observed from the plot that at tool nose radius 1.6 mm the surface roughness increases. It is because during hard turning with an increase in tool nose radius the friction between tool and workpiece increases. It leads to the rise of cutting forces and the cutting temperature the rate of growth of auxiliary flank wear increases as results the surface roughness increases. MQL takes away the significant portion of heat, reduces the temperature resulting decrease in the dimensional deviation, and improve the surface quality of the machining. It have been observed from the above analysis that surface quality found to be superior with the use of MQL during machining as compared with conventional wet and dry conditions. It is due facts that during MQL facilitating better lubrication and efficient heat transfer leading to low cutting temperature than flooded cutting fluids during wet turning. 6. Conclusions The performance of hard turning is analysed by the surface quality of the machined products. The performance of MQL during hard turning was investigated and compared with wet turning processes in terms of surface quality. Based on the above results of the experimental investigations the following conclusions are drawn for MQL machining • Surface quality improves by 7 % to 10 % with MQL when compared with flooded supply of lubricants. Surface finishes developed mainly due to the reduction of wear and damage at the tool tip by the application of MQL. • MQL provide advantage primarily by dropping the heat generation at the cutting zone, which leads to improves tool life and chip-tool interaction. Also, it maintains the sharpness of the cutting edges which results in better surface quality. • Surface quality with the use of MQL is better than conventional wet and dry machining. It is due facts that during regular wet turning, only convective heat transfer extracts the heat, but during MQL, cooling occurs by convective as well as an evaporative mode of heat transfer occur. Acknowledgment The authors are highly thankful to Punjab Technical University, Jalandhar, Punjab, India for continuous technical support in this field of research works. References [1] [2] [3] [4]

E. Diniz, R. Micaroni, Cutting conditions for finish turning process aiming: the use of dry cutting. International Journal of Machine Tools and Manufacture. 42 (2002)899-904. A.S. Varadarajan, P.K. Philip, B. Ramamoorthy, Investigations on hard turning with minimal cutting fluid application (HTMF) and its comparison with dry and wet turning. International Journal of Machine Tools & Manufacture 42(2002)193–200. A.E. Diniz, J.R. Ferreira, F.T. Filho, Influence of refrigeration/lubrication condition on SAE 52100 hardened steel turning at several cutting speeds. International Journal of Machine Tools and Manufacture. 43(2003) 317–326. M.M.A. Khan, N.R. Dhar, Performance evaluation of minimum quantity lubrication by vegetable oil in terms of cutting force, cutting zone temperature, tool wear, job dimension and surface finish in turning AISI-1060 steel. Journal of Zhejiang University Science- A. 11( 2006) 1790-1799.

Sanjeev Kumar et al/ Materials Today: Proceedings 4 (2017) 3627–3635 [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30]

3635

N.R. Dhar, S. Islam, M. Kamruzzaman, Effect of Minimum Quantity lubrication (MQL) on Tool Wear, Surface Roughness and Dimensional Deviation in Turning AISI-4340 Steel. G.U. Journal of Science 20(2007) 23-32. S.M.A. Choudhury, N.R. Dhar, M.M.A. Bepari, Effect of Minimum Quantity Lubricant on temperature chip and cutting force in turning medium carbon steel. Proceedings of the International Conference on Mechanical Engineering (ICME2007) 29- 31 December 2007, Dhaka, Bangladesh. V.C.H.R Kumar, B. Ramamoorthy, Performance of coated Tools during Hard Turning under Minimum Fluid Application. Journal of Materials Processing Technology. 185(2007) 210–216. H. Tasdelen, D. Thordenberg, Olofsson, An experimental investigation on contact length during minimum quantity lubrication (MQL) machining. Journal of materials processing technology. 203( 2008) 221–231. M.M.A. Khan, M.A.H. Mithu, N.R. Dhar, Effects of minimum quantity lubrication on turning AISI 9310 alloy steel using vegetable oilbased cutting fluid. Journal of Materials Processing Technology. 209 (2009) 5573–5583. Y.K. Hwang, C.M. Lee, Surface roughness and cutting force prediction in MQL and wet turning process of AISI 1045 using design of experiments. Journal of Mechanical Science and Technology. 24( 2010)1669-1677. T.N. Chowdhury, N.R. Dhar, Experimental analysis and modeling of tool wear and surface roughness in hard turning under minimum quantity lubricant environment. international conference on industrial engineering and operations management, Kuala Lumpur, Malaysia, January 22 – 24, 2011. P.D. Kumarh, M.Sadaiah, Investigations on finish turning of AISI 4340 steel in different cutting environments by CBN insert. International Journal of Engineering Science and Technology. 3 (10) 2011. DV Lohar and Nanavaty CR. Performance Evaluation of MQL for turning of AISI 4340 steel. International Journal of Emerging Trends in Engineering and Development July 2012. M. Hada, B. Sadeghi, Minimum quantity lubrication-MQL turning of AISI 4140 steel alloy. Journal of Cleaner Production. 54 (2013) 332343. S. Ekinovic, E. Begovic, E. Ekinovic, B. Fakic, Cutting Forces And Chip Shape in MQL Machining Of Aluminium Bronze. Journal of Trends in the Development of Machinery and Associated Technology. 17( 2013)17-20. R.B. Da Silva, A.R .Machado, D.O. Almeida, E.S. Costa, Turning of Medium Carbon Steel with Vegetable-Based Oil delivered by MQL. 22nd International Congress of Mechanical Engineering (COBEM 2013) November 3-7, 2013, Ribeirao Preto, SP, Brazil. V.C. Nguyen, T.S. Le, M.D. Tran, D.B. Nguyen, An Investigation on Effect of Characteristics of the Peanut oil MQL on Tool life in Hard turning 9CrSi steel. International Journal of Machining and Machinability of Materials.13(2013)428-438. D.M. Naigade, D.K. Patil, M. Sadaiah, Some investigations in hard turning of AISI 4340 alloy steel in different cutting environments by CBN inserts. Int. J. of Machining and Machinability of Materials 14(2013)165 - 193. M. Hadi, Investigation on turning of AISI H13 with applying Minimum Quantity Lubricant. Indian Journal of Science and Technology16(2) 2013. S.A. Lawal, I.A. Choudhury, Y. Nukman, A critical assessment of lubrication techniques in machining processes: a case for Minimum quantity lubrication using vegetable oil-based lubricant. Journal of Cleaner Production41( 2013)210-221. K.S. Shihab, A.Z. Khan, Aasmohammad, A. N. Siddiquee, Application of Response Surface Methodology for Determining Cutting Forces in Hard Turning Using Castrol Coolant, Advanced Materials Manufacturing & Characterization, 3(1) 2013. B.A.Beatrice, E. Kirubakaran, P. Ranjit, J.Thangaiah, K. Leo, D. Wins, Surface Roughness Prediction using Artificial Neural Network in Hard Turning of AISI H13 Steel with Minimal Cutting Fluid Application Procedia Engineering. 97(2014)205 – 211. R. Robinson, A.S. Varadarajan, Investigation on the Effect of an Auxiliary Pulsing Jet of Water at the Top Side of Chip during Hard Turning of AISI 4340 Steel with Minimal Fluid Application. International Journal of Precision Engineering and Manufacturing 15(2014)1435-1441. S. B. Kedare, D.R, Borse. P. T. Shahane, Effect of Minimum Quantity Lubrication (MQL) on Surface Roughness of Mild Steel of 15HRC on Universal Milling Machine Procedia Materials Science 6(2014)150–153. J.S. Dureja, R. Singh, T. Singh, M. Dogra, M.S. Bhatti, Performance Evaluation of Coated Carbide Tool in Machining of Stainless Steel (AISI 202) under Minimum Quantity Lubrication (MQL). International Journal of Precision Engineering and Manufacturing-Green Technology. 2(2015)123-129. M.H.Saad, D.Kurniawan, M.Y. Noordin, Use of Castor Oil as Cutting Fluid in Machining of Hardened Stainless Steel with Minimum Quantity of Lubricant. Procedia CIRP 26(2015) 408 – 411. International Organization for Standardization. Tool-Life Testing with Single Point Turning Tools. ISO 3685–1993 (E), 2nd Edition; ISO: Geneve, Switzerland, 1993. D.C. Montgomery, Design and Analysis of Experiments, 7th Ed.; John Wiley and Sons Pvt. Ltd. New Delhi, 2012. E.D. Derakhshan, A.A.Akbari, Experimental Investigation on the Effect of Work piece Hardness and Cutting Speed on Surface Roughness in Hard Turning with CBN Tools. Proceedings of the World Congress on Engineering, Vol II WCE 2009, July 1 - 3, London, U.K. G. Poulachon, B.P. Bandyopadhyay, I.S. Jawahir, S. Pheulpin, E. Seguin, The influence of the microstructure of hardened tool steel workpiece on the wear of PCBN cutting tools. International Journal of Machine Tools & Manufacture 43( 2003)139–144.