Dry Flooded And Minimum Quantity Lubrication Biology Essay

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Cutting fluids are employed in machining operations to improve the tribological conditions along with some more advantages. Cutting fluids have many detrimental effects. Many of the fluids, which are used to lubricate metal forming and machining, contain environmentally harmful or potentially damaging chemical constituents. These fluids are difficult to dispose and expensive to recycle and can cause skin and lung disease to the operators and also air pollution. In dry machining, higher order friction between tool and work and between tool and chip can lead to high temperatures in the machining zone. Because of these some alternative measures have been made to minimize the use of cutting fluids, in which Minimum Quantity Lubrication has been chosen.

The minimal quantity lubrication can be practiced instead of dry machining. A cutting fluid for MQL could be selected not only on the basis of primary characteristics (cutting performance) but also of its secondary characteristics, such as biodegradability, oxidation stability, and storage stability. Minimum Quantity Lubrication machining refers to the use of a small amount of cutting fluid, typically in the order of 100 ml/hr or less, which are about three to four orders of magnitudes lower than that used in flooded lubricating conditions. This project work deals with experimental investigations and optimization of process parameter in turning of 6351 Aluminum alloy with dry, flooded and Minimum Quantity Lubrication conditions using Taguchi's design of experiments methodology on cutting forces and chip formation with uncoated carbide tool.

The results have been compared among dry, flooded and MQL conditions. From the experimental investigations, MQL shows some favorable results in reduction of cutting forces and formation of chip compared to dry and flooded conditions. The results also indicated that, MQL is suitable at higher depth of cut lower cutting speeds and moderate feed rates. The chip morphology studies reveals that, chips produced in MQL are curly chips with shorter in length compared to dry and flooded lubricant condition, this shows improved tool life in MQL.

Keywords: Turning, Aluminum alloy, Carbide tool, Dry, Flooded, MQL, Taguchi method, ANOVA, Cutting force;

Introduction

In any metal cutting operation, lot of heat is generated and it affects the quality of the products produced (dimensional accuracy and surface finish) besides the tool wear. Hence, the heat produced during the machining process is critical in terms of work piece quality. Thus, effective control of heat generated in the cutting zone is essential to ensure good work piece surface quality and optimum tool life in machining.

Cutting fluids have been the conventional choice to deal with this problem. Cutting fluids are introduced in the machining zone to improve the tribological characteristics of machining processes and also to dissipate the heat generated. The main purpose of using cutting fluid in machining processes is to reduce cutting zone temperatures in order to increase tool life. The advantages of this use, however, have been called into question lately due to the negative effects on product cost, environment and human health.

The application of conventional cutting fluids creates some techno-environmental problems like environmental pollution, biological problems to operators, water pollution, etc. Further, the cutting fluids also incur a major portion of the total manufacturing cost. All these factors prompt investigations on the use of biodegradable coolants and coolant free machining.

J.F.Kelly, [1], discussed about the lubricants in machining. Industry and research institutions are looking for ways to reduce the use of lubricants because of ecological and economical reasons. While there are established applications of dry turning and milling, dry drilling presents special difficulties due to the problems of swarf clearance from the flutes and consequent heat build-up and clogging. The rising costs associated with the use and disposal of cutting fluid have forced engineers to concern themselves more disposal together with exploring the potential for cooling lubricant reduction and avoidance. This paper presents an investigation into various methods of cutting fluid application with the objective of deriving the optimum cutting condition for the drilling of cast aluminum alloys. A series of tests were carried out using various methods of cutting fluid application, under varying conditions of cutting speed and feed. N.R.Dhar, [2,4], investigated the role of MQL on cutting temperature, chip reduction coefficient, cutting forces, tool wears, surface finish, and dimensional deviation for turning of AISI 1040 and 4340 steel. The results shows that significant reduction in cutting temperature, chip reduction coefficient, cutting forces, tool wear rate, surface roughness and dimensional deviation by MQL mainly through reduction in the cutting zone temperature and favorable change in the chip-tool and work-tool interaction. A.Attanansio, [3], has used the MQL technique in turning to determine the tool wear reduction. The results obtained from experimental tests and EDS microanalysis of tools are as follows. Lubricating the rake surface of a tip by the MQL technique does not produce evident wear reduction. Tool life time of a tip used in dry cutting conditions is similar to that of a tip lubricated by MQL on the rake. Lubricating the flank surface of a tip by the MQL technique reduces the tool wear and increases the tool life. Traces of lubricant compounds have been found on the worn surfaces only when MQL has been applied on the flank surface. The conclusion of authors is that, the MQL gives some advantages during the turning operation, but it presents some limits due to the difficulty of lubricant reaching the cutting surface.

Reduction of environmental pollution has been the main concern in the present day manufacturing industry. Increasing pollution-preventing initiatives globally and consumer focus on environmentally conscious products has put increased pressure on industries to minimize the use of cutting fluids. However, the use of lubricant cannot be swayed away in view of the high temperatures and forces generated during machining. The heat generated in machining adversely affects the quality of the products. As an alternative to the conventional cutting fluids, researchers experimented with biodegradable and cryogenic coolants in order to reduce the heat generated in machining zone by reducing the coefficient of friction and tool wear. The effectiveness of cryogenic coolant seemed to increase at higher feeds. It reduced the magnitude of tensile residual stress for all materials, although to varying degrees, under all feed levels. This was attributed to the efficient cooling action, better modes of chip formation, less specific energy and finally, lower grinding zone temperature. The concept of minimum quantity lubrication (MQL) was also employed as an alternative approach.

This paper presents an investigation into various methods of cutting fluid application with the objective of deriving the optimum cutting conditions for the turning of 6351 aluminum alloys.

Methodology

Taguchi method is a unique and powerful statistical experimental design technique, which greatly improves the engineering productivity. Taguchi developed the procedure, which apply orthogonal arrays of statistically designed experiments to obtain the best model with minimum number of experiments and thus reducing the time and cost of experimentation. Taguchi suggests signal-to-noise (S/N) ratio as the objective function for the matrix experiments, which is used to measure the performance characteristic and the percent contribution of process parameters through analysis of variance (ANOVA). Taguchi classifies the objective functions as smaller the better type, larger the better type and nominal the best type characteristics. The optimal level for a process parameter is the level, which results in highest value of S/N ratio in the experimental region.

Experimental procedure

This paper deals with experimental investigates and optimization process parameters like cutting speed, feed rate and depth of cut in order to minimize cutting forces using Taguchi's robust design methodology. An extensive literature survey has been carried out for better understanding of importance of Dry, Flooded and Minimum Quantity Lubrication and its manufacturing and performance aspects. The experiments are conducted under Dry, Flooded and Minimum Quantity Lubricant conditions using L9(34)standard orthogonal array (O.A). The cutting forces are measured using 3 -Dimensional lathe tool dynamometer. Each experiment is conducts for two trails. The chip samples are collected while turning under Dry, Flooded and Minimum Quantity Lubrication condition has been categorized with respective to their shape and color. The analysis of mean is carried out to determine the optimum combination of process parameters and ANOVA is performed to determine the percentage contribution of each parameter using Taguchi's robust design methodology.

Cutting fluid delivery system

In the dry machining lubricant is not applied as shown in Fig. 1, where as in flooded machining kerosene is applied at the rate of 800 lit./hr is shown Fig. 2 and in Minimum Quantity Lubrication corn seed oil is applied at rate of 250 ml/hr and pressure at 7 MPa. The cutting fluid is supplied to the cutting zone by a specially designed experimental setup is shown in Fig. 3. The MQL is supplied at high pressure and impinged at high speed through the nozzle at the cutting zone continuously. The MQL jet has mainly concentrated at the interface of the rake and flank surfaces to protect tool for better performance.

Fig 1. Dry machining

Fig 2. Flooded machining

Fig 3. Minimum Quantity Lubrication

Work piece material

For the present study, Aluminum 6351 alloy is selected as a work material. It is general purpose aluminum having a wide range of applications in automobile and other application by virtue of its good hardenability. Bars of 55 mm diameter and 350 mm length are used in the present investigation.

Cutting tools

Carbide, SNMG 120408 - (H - 13A ISO specification) hard metal inserts from leading manufacturer of cutting inserts are selected for the present work.

Cutting performance

The experiments are carried out on Kirloskar Lathe (Turn master - 35). The cutting performance is characterized by measuring the cutting forces. The machining experiments are carried out using carbide tools under dry, flooded and Minimum Quantity Lubrication by varying cutting speed, feed rate and depth of cut.

The relative influence of cutting parameters such as cutting speed, feed rate, depth of cut and cutting fluid is studied by using Taguchi's L9(34) orthogonal array given is in Table 1. This approach considerably reduces the number of trials required and several factors were varied together. Three independent parameters at three different levels are selected as input parameters for this study is given in Table 2. The experiments are carried out with two replications. The cutting performance is evaluated by measuring cutting forces using lathe tool dynamometer for each experiment.

Table 1: Basic design matrix for experiments

Experiment

Number

Column

1

2

3

4

1

2

3

1

1

1

1

2

3

1

2

3

1

2

3

4

5

6

2

2

2

1

2

3

2

3

1

3

1

2

7

8

9

3

3

3

1

2

3

3

1

2

2

3

1

Table 2: Control factors and levels

Level Number

Speed (A) (rpm)

Feed Rate (B) (mm/rev)

Depth of Cut (C) (mm)

1

450

0.18

0.4

2

710

0.25

0.6

3

1120

0.315

0.9

4. Experimental results, analysis of data and discussion

4.1 Cutting forces

Figure 4 shows the variation between cutting speed and cutting forces. When the cutting speeds are low, the cutting forces are also low for MQL compared to dry and flooded conditions, but under higher cutting speeds, the cutting force is high for MQL compared to dry and flooded conditions. The main reason for high cutting force in MQL at higher cutting speed is due to insufficient lubricant supply at higher speeds. From Figures 4, it can be understood that, MQL shows some favorable results in reducing cutting forces compared to dry and flooded conditions.

Figure 4: Variation of cutting forces with cutting speed

Figure 5 shows the variation between depth of cut and cutting forces, when the depth of cut is low, the cutting forces are also low for MQL compared to dry and flooded conditions, but under higher depth of cut, the cutting force is high for flooded condition compared to dry and MQL conditions. As the depth of cut is increases, the cutting forces are also increases but it is observed that, the cutting forces are less in dry and MQL conditions compared to flooded condition. Figures 5 indicates that, MQL shows some favorable results for cutting forces compared to dry and flooded conditions.

Figure 5: Variation of cutting forces with depth of cut

Figure 6 shows the variation between feed rate and cutting forces. When the feed rate is low, the cutting forces are low for MQL compared to dry and flooded conditions, and also under higher feed rate the cutting force is low for MQL compared to flooded and dry conditions. Figures 6 indicates that, MQL shows some favorable results for cutting forces compared to dry and flooded conditions.

Figure 6: Variation of cutting forces with feed rate

Finally, it is concluded that, machining of 6351 aluminum alloy with uncoated carbide tool using MQL conditions shows better performance compared to dry and flooded conditions in terms of cutting forces. In MQL the cutting fluid is supplied at high pressure and high velocity, which penetrates in to the tool chip interface zone causes reduction in frictional contribution to the cutting force.

4.2 Optimization of cutting parameters

In the present work, the performance characteristics namely cutting force is to be minimized and hence "smaller the better type" quality characteristic has been selected for each of the response. The S/N ratios for average cutting forces are given by

The computed values of S/N ratio for each trail under dry, flooded and MQL conditions in the orthogonal array are shown in Table 3.

The analysis means is carried out to determine the optimal combination of process parameters. The level of parameter with maximum S/N ratio is the optimum level. The optimum cutting parameters found in turning of aluminum 6351 alloy for minimum cutting forces for dry machining is A3-B1-C1, flooded machining A3-B1-C1 and MQL machining A2-B1-C1 and comparison of the optimum parameters for under dry, flooded and MQL condition are shown in Table 4. It is observed that, the MQL is effective under lower cutting conditions compared to dry and flooded conditions, but MQL cannot be used for higher cutting speeds due to coolant and lubricant actions have not sufficient.

Table 3: Data summary cutting forces and S/N ratio

EXPERIMENT

NUMBER

Average cutting force in kgf

S/N RATIO (dB)

Average cutting force in kgf

S/N RATIO (dB)

Average cutting force in kgf

S/N RATIO (dB)

Dry machining

Flooded Machining

MQL Machining

1

2

3

16

16.5

18.5

-24.09

-24.35

-25.34

16

26.5

31.5

-24.09

-28.47

-29.96

15

18.5

19

-23.54

-25.34

-25.57

4

5

6

20.5

20

19.5

-26.23

-26.03

-25.80

16

16

23.5

-24.09

-24.09

-27.43

15.5

16.5

18.5

-23.81

-24.35

-25.34

7

8

9

15.5

16.5

18.5

-23.81

-24.35

-25.34

19

14

17

-25.68

22.92

-24.62

17.5

18.5

20.5

-24.86

-25.34

-26.23

Table 4: Optimum parameters for cutting forces

MQL

F.C

DRY

Cutting speed, rpm

710

1120

1120

Feed rate, mm/rev

0.18

0.18

0.18

Depth of cut, mm

0.4

0.4

0.4

4.3 Influence of cutting parameters

ANOVA is performed to determine the percentage contribution of each parameter. Table 5 presents the results of ANOVA on performance characteristics for cutting forces under dry machining. As seen from the ANOVA Table 5, the cutting speed has major contribution (59.51 %) in optimizing the performance characteristics followed by feed rate and depth of cut. Further, it is observed that, ANOVA has resulted with 18.73 % of error contribution. The anticipated ηpredicted is to be calculated to predict the process average under chosen optimum condition. This is calculated by summing the effects of factor levels in the optimum condition. S/N ratios of optimum condition are used to predict the S/N ratio of the optimum condition using the additive model.

-- (1)

Where Y is average S/N ratio. The predicted S/N ratio is calculated using eq. (1) for A3, B1 and C1 parameter level combination is -23.89 dB. Conducting a verification experiment is a crucial final step of the robust design methodology. The predicted results must be conformed to the verification test, the verification experiment is conducted with the optimum conditions of cutting speed -1120 rpm, feed rate - 0.18mm/min and depth of cut - 0.4mm. The calculated is S/N ratio is (ηexpt) -23.95dB. It is found that the S/N ratio value of verification test is within the limits of the predicted value at 95%

confidence level and the objective is fulfilled. These suggested optimum conditions can be adopted.

Similarly ANOVA is performed for flooded machining. Table 6 presents the results of ANOVA on performance characteristics for cutting forces under flooded machining. As seen from the ANOVA Table 6, the cutting speed has major contribution (29.93 %) in optimizing the performance characteristics followed by feed rate and depth of cut. Further, it is observed that, ANOVA has resulted with 44.63 % of error contribution.

The predicted S/N ratio is calculated using eq. (1) for A3, B1 and C1 parameter level combination is -22.43 dB. Conducting a verification experiment is a crucial final step of the robust design methodology. The predicted results must be conformed to the verification test, the verification experiment is conducted with the optimum conditions of cutting speed-1120 rpm, feed rate - 0.18mm/min and depth of cut - 0.4mm. The calculated S/N ratio is (ηexpt ) -22.94dB. It is found that the S/N ratio value of verification test is within the limits of the predicted value at 95% confidence level and the objective is fulfilled. These suggested optimum conditions can be adopted.

Similarly ANOVA is performed for MQL machining. Table 7 presents the results of ANOVA on performance characteristics for on cutting forces under MQL machining. As seen from the ANOVA Table 7, the feed rate has major contribution (59.38 %%) in optimizing the performance characteristics followed by cutting speed and depth of cut. Further, it is observed that, ANOVA has resulted with 13.51 % of error contribution. The predicted S/N ratio is calculated using eq. (1) for A2, B1 and C1 parameter level combination is -23.45 dB. Conducting a verification experiment is a crucial final step of the robust design methodology. The predicted results must be conformed to the verification test, the verification experiment is conducted with the optimum conditions of cutting speed-780 rpm, feed rate -

Table 5: Summary of ANOVA in dry machining on cutting force

Factor

Pool

S.S

D.O.F

M.S.S

F-RATIO

Speed

Feed

Depth of cut

40.62

10.26

6.96

2

2

2

20.31

5.13

3.48

28.01

7.07

4.8

39.17

8.81

5.51

59.51 %

13.38 %

8.37 %

Error

Yes

7.98

11

0.725

-

-

-

Pooled Error

7.98

11

0.725

-

12.33

18.73 %

65.82

17

29.64

-

65.82

100 %

Mean

5,793.18

1

-

-

-

-

5,859

18

-

-

-

-

Table 6: Summary of ANOVA in flooded machining on cutting force

Factor

Pool

S.S

D.O.F

M.S.S

F-RATIO

Speed

Feed

Depth of cut

210.05

158.09

56.39

2

2

2

105.02

79.04

28.19

6.70

5.04

1.79

178.71

126.75

25.05

29.93 %

21.23 %

4.19 %

Error

Yes

172.42

11

15.67

-

-

-

Pooled error

172.42

11

15.67

266.44

44.63 %

596.95

17

227.92

-

596.95

100 %

Mean

7,160.05

1

-

-

-

-

7,757

18

-

-

-

-

Table 7: Summary of ANOVA in MQL machining on cutting force

Factor

Pool

S.S

D.O.F

M.S.S

F-RATIO

Speed

Feed

Depth of cut

13.83

34.77

3.45

2

2

2

6.91

17.38

1.72

15.28

38.45

3.80

12.92

33.86

2.54

22.65 %

59.38 %

4.45 %

Error

Yes

4.98

11

0.452

-

-

-

Pooled Error

4.98

11

0.452

-

7.71

13.51 %

57.03

17

26.46

-

57.03

100 %

Mean

5,651.97

1

-

-

-

-

5,709

18

-

-

-

-

0.18mm/min and depth of cut - 0.4mm. The calculated S/N ratio is (ηexpt) -23.54dB. It is found that the S/N ratio value of verification test is within the limits of the predicted value at 95% confidence level and the objective is fulfilled. These suggested optimum conditions can be adopted.

4.4 Chip morphology

The chip samples are collected while turning of 6351 aluminum alloy with the uncoated carbide insert under dry, flooded and MQL condition. These have been visually examined and categorized with respect to their shape and color. Under dry machining, the color of the chip is white and the discontinuous chips are produced at lower cutting speed and continuous chips are produced at higher cutting speeds. Figure 7 (a) and Figure 7 (b) shows the discontinuous and continuous chips produced under dry conditions respectively.

Under flooded machining, the color of the chip is dark blue and continuous with long curly chips are produced at lower and higher cutting speeds. Figure 7 (c) shows continuous with curly chips produced under flooded condition.

Under MQL machining, the color of the chip is white color and continuous with shorter curly chips are produced at lower and higher cutting speeds. Figure 7 (d) shows continuous with shorter curly chips produced under MQL condition. Shorter curly chips are produced due to air pressure and this forms chips higher tool life.

(a)

(b)

(c)

(d)

Figure 7: (a) Chip morphology under dry machining at lower cutting speed (b) Chips morphology under dry machining at higher cutting speed (c) Chip morphology under flooded machining (d) Chip morphology under MQL machining

Conclusions

Based on the results of the present experimental investigations the following conclusions are drawn:

The cutting performance of MQL machining shows favorable and better compared to dry and flooded conditions.

The MQL machining shows advantage mostly by reducing quantity of the cutting fluid, cutting forces and environmental problems, which reduces the friction between the chip & tool interaction and maintains sharpness of the cutting edges.

The ANOVA shows that machining with MQL condition is suitable under lower cutting conditions compared to dry and flooded lubricant conditions.

The ANOVA reveals that cutting speed is dominant parameter under dry and flooded conditions in optimizing the cutting forces where as feed rate is most dominant parameter under MQL conditions in optimizing the cutting forces.

In MQL, continuous with shorter curly chips are produced. This indicates that, the interaction between the tool and work piece becomes less and also improves tool life.

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