Nano Cutting Fluids in Minimum Quantity Lubrication

D.Nageswara Rao

Dept. of Mechanical Engg.,College of Engineering, Andhra University, Visakhapatnam, India.

R.R.Srikant, P.Vamsi Krishna, M.S.Subrahmanyam

Dept. of Industrial Production Engineering, GIT, GITAM University, Visakhapatnam, India

Abstract Machining is characterized by high cutting forces and

temperatures that drastically influence the product quality. To

deal with the problem, cutting fluids have been the conventional

choices. However, several problems posed by the cutting fluids,

including the health hazards like dermatitis to the exposed

workers, have demanded for alternative cooling methods. As a

solution, Minimum Quantity Lubrication

(MQL) has emerged. This calls for fluids of high thermal

conductivity. In the present work, inclusion of nano-particles is

studied for the enhancement in cutting fluid properties. Parent

cutting fluid properties are estimated through a series of tests as

per ASTM. CuO nano particle inclusion, in varying proportions

is studied. Heat transfer rates are computed for the parent fluid

and the fluids with nano particle inclusion are computed and

temperature profiles of cutting tool are simulated using Finite

Element Analysis. The results are compared with the

experimental results of dry machining and machining with parent

cutting fluid. Results indicate that nano-particle inclusion shows

drastic improvement in the properties of the cutting fluid.

Inclusion upto 6% is beneficial to machining through cooling and

inclusion beyond 6% is not desirable. The flow rate of the

coolant is controlled and minimized to obtain satisfactory levels

of cooling with minimum quantity of the lubricant. An intelligent

system is built up using artificial neural networks to decide the

required flow rate for any percentage of nano-particle inclusion.

This work provides a basis for studying the effectiveness of the

fluids in MQL.

Keywords: metal cutting, cutting fluids, nanofluids

1. Introduction In the present day world of cutthroat competition, the

quality and economy are the buzzwords of any industry.

However, the long idle times and overheads associated with the

production processes prevent achieving the goal. Machining,

being a major manufacturing process, contributes to the majority

of the products’ cost. Economy of machining is affected by the

frequent interruptions during tool change as cutting tool wears,

thus prolonging the production times and increasing the cost of

product.

Though several parameters affect on the condition of

cutting tool, cutting forces and temperatures are found to be most

influential. Hence, it has constantly been the drive to device

techniques for reducing friction and temperatures associated with

metal cutting. Among such methodologies, application of Cutting

Fluids is prominent.

The prime function of cutting fluids stands is to provide

adequate lubrication and cooling in metal cutting operations. The

coolant of the fluid prevents thermal expansions of the workpiece.

Consequently, the fluids help in achieving longer tool life and

better surface finish of the product. These benefits made the

existence of the fluids in metal cutting operations for the last 200

years.

Cutting fluids play a significant role in machining

operations and impact shop productivity, tool life and quality of

work[1,2]. However, with time and use, fluids degrade in quality

and eventually require disposal once their efficiency is lost.

Waste management and disposal have become increasingly more

complex and expensive.

Mist generation is another problem prevalent with the

cutting fluids. The aerosol gets accumulated in the respiratory

system of the worker and can cause severe problems.

Environmental liability is also a major concern with

waste disposal. Many companies are now paying for

environmental cleanups or have been fined by regulatory

agencies as the result of poor waste disposal practices [3]. Further,

addition of additives is also restricted due to their effect on the

environment during disposal.

With several limitations of cutting fluids, the search for

substitutes is underway. This has given rise to Minimum Quantity

Lubrication (MQL) where a bare minimum quantity of the fluid is

employed. Since high cooling is to be achieved with minimum

quantity of the fluid, the coolant needs to be of high thermal

conductivity. Nanofluids have emerged as a promising solution to

this problem. Nanofluids are engineered colloidal suspensions of

nanoparticles (1-100 nm) in a base fluid [4]. The use of

nanofluids as coolants in radiators and other applications is under

study [5]. The applicability of the fluids as coolants is mainly due

to the enhanced thermal conductivity of the fluids due to the solid

particle inclusion [6].

The use of cutting fluid is constrained by its properties,

primarily cooling abilities. In the present work, cooling abilities

of the fluid are assessed by the estimation of thermal conductivity

of the fluids with and without nanoparticles inclusion. To

estimate the cutting tool temperature, machining is carried out.

Cutting conditions are selected considering the chosen workpiece

material and tool combination besides the machine tool available

in the laboratory for conducting experiments.

2. Experimental Setup & Experimentation AISI 1040 (EN 8) steel is used as the workpiece

material.

Experiments are conducted on PSG-124 lathe at

constant cutting conditions. This machine has both auto feed and

variable spindle speed capabilities. Experimental set-up on a 10

HP lathe (Make: PSG) is shown in Fig. 1.

Fig. 1 Experimental set up on PSG-124 Lathe Machining is carried out using cemented carbide insert and HSS

tool separately.

The choice of tool holder and cutting tool insert for machining

process is provided by Sandvik India Limited. Tool insert and

tool holder with a provision for placing an embedded

thermocouple [7].

Cutting tool insert: uncoated Carbide, SNMG

120408 (H-13A ISO specification)

Tool holder: PSRNR 12125F09 (ISO

specification)

Cutting temperatures indicate the amount of heat generated

during machining. To assay the effectiveness of the cutting fluid

as a coolant, cutting temperatures are measured. Embedded

thermocouple is used to measure the temperature of the cutting

tool insert at a nodal point. Digital temperature indicator is used

for recording and displaying the temperature of the hot junction

of

thermocouple

.

A Cr-Al,

K-type

thermocouple

is used to

measure the

temperatures.

Machining is

done under

constant

cutting

conditions on

PSG lathe

with AISI 1040 (EN 8) workpiece, cemented carbide inserts as

cutting tools. Cutting temperatures are measured. Cutting fluid is

used at a rate of 0.11 m3/ min. The results are analyzed to asses

the performance of the fluids in machining.

3. Estimation of Heat Transfer coefficients The thermal conductivity of a nanofluid is given by

[8]:

−+−+

−−−−+=

)()1(

)()1()1(

pffp

pffp

fnfkkknk

kknknkkk

φ

φ

where knf is the nanofluid thermal conductivity, kf is the base fluid

thermal conductivity, kp is the bulk solid particle thermal

conductivity, φ is the particle volume fraction, and n is an

empirical scaling factor that takes into account how different

particle shapes affect thermal conductivity. We used spherical

nanoparticles in our experiments for which n = 3.

The effective density of nanofluids is given by:

sfnf φρρφρ +−= )1(

where ρnf is the nanofluid density and ρs and ρf are the densities of

the solid particles and base fluid, respectively.

The specific heat of nanofluids, cpnf, can be calculated using the

standard equation based on the volume fraction.

pfpspnf CCC )1( φφ −+=

where cps is specific heat of solid particles and cpf is specific heat

of base fluid.

Heat transfer coefficient is calculated taking the condition as flow

over flat plates [9] as:

Nu = 0.453*(Re0.5)*(Pr0.333) For 1% to 5%)

0.4637*(Re0.5)*(Pr0.333)

Nu = _________________________

[1+ (0.0207/Pr)0.67]0.25 (For 6% to 8%)

Nu * k

h = ________

x

The values of thermal conductivity and kinematic

viscosity of the base fluid are taken form our earlier published

paper [10].

Table 1 Kinematic viscosity of cutting fluids

(95% water), x 104 m2/sec

Temperature, 0C

Kinematic

Viscosity

34 0.025

40 0.02

48 0.016

54 0.016

65 0.016

Table 2 Thermal conductivity of the cutting fluids,

W/m-0C

Based on the relations presented in earlier heat transfer

coefficients are calculated and presented in table 3.

Table 3

% inclusion of

nanoparticles

Heat Transfer

Coefficient, W/m2K

0.0 1774.46

0.5 1857.42

1.0 1885.8

2.0 1941.84

3.0 1990.08

4.0 2018.61

5.0 2032.58

6.0 2099.79

7.0 2066.90

8.0 2058.06

Temperature 0C

Thermal

Conductivity,

W/m-K

30 0.296

35 0.298

40 0.301

50 0.306

55 0.309

60 0.311

65 0.314

70 0.317

80 0.322

90 0.327

4. Estimation of Cutting temperatures The prime function of a cutting fluid is to act as a coolant in

machining. Dry machining is done to measure the tool

temperatures. Nodal temperatures at a point on the tool nearer to

the tip are recorded while machining under application of

ordinary cutting fluid and dry machining are recorded. The

results are presented in Fig. 3. Nodal temperatures increase

initially and stabilize over time as the tool attains steady state. As

the contact between the tool and the workpiece is a single point,

where the cutting fluid cannot reach, the cutting tip temperature

is constant in all the cases; however the nodal temperatures

change due to different thermal conductivities of the fluids. In

case of dry cutting, the heat transfer coefficient is taken as 60

W/m2-K [11] and the cutting tip temperatures are estimated

extrapolating the nodal temperatures recorded. Tip temperatures

are assumed to be in the range of 200 0C to 1200 0C. At the

assumed tip temperature, nodal temperature is estimated by

Finite Element Analysis using ANSYS 5.4. 10-node tetrahedron

element is chosen in the present work owing to its high

adaptability to complicated shapes and curved surfaces. Steady

state thermal analysis is carried out (Figs. 4 &5). Calculated

nodal temperatures are compared with the experimental values

and the choice of tool tip temperatures is tuned till the calculated

and measured nodal temperatures are identical. The tool tip

temperatures are presented in Fig. 6. Temperatures increase

rapidly in the initial period, but stabilize on achieving steady

state.

0

20

40

60

80

100

120

140

160

180

0 20 40 60 80

Machining Time, mins

Nodal T

em

pera

ture

, 0C

Dry

Cutting Fluid

Fig.3 Recorded nodal temperatures

.

Fig.5 Estimation of tip temperatures for cemented carbide

tool

300

400

500

600

700

800

900

1000

0 10 20 30 40 50 60

Machining Time, mins

To

ol T

ip T

em

pe

ratu

re, 0C

Fig.6 Extrapolated tool tip temperatures under dry cutting

The calculated heat transfer coefficients are used in FEA

analysis to estimate the nodal temperatures in all the cases.

Nodal temperatures for different cutting fluids with varying

inclusion of nanoparticles are estimated and presented in Fig.7.

The results clearly show that temperatures are decrease from

0.5% to 6% inclusion of nanoparticles beyond which the

temperatures increase. Upto 6%, the decrease in temperatures is

more drastic compared to concentrations beyond 6%. This is due

to the decreased heat transfer coefficient because of the impact

of increased viscosity.

0

10

20

30

40

50

60

0 20 40 60 80

Machining Time, mins

No

dal

Tem

pera

ture

s,

0C Cutting Fluid

0.5%

1%

2%

3%

4%

5%

6%

7%

8%

Fig.7 Nodal Temperatures for cutting fluids with varying

nanoparticle inclusion To decide on bare minimum quantity of cutting fluid,

an intelligent system is built using artificial neural networks [12].

Inputs are taken as nodal temperature and time, output being the

quantity of the fluid. 2-2-1 is chosen as architecture of the back

propagation network. To obtain the same cooling as an ordinary

cutting fluid, 0.02 m3/min of fluid with 6 % nano particle

inclusion is found to be sufficient.

5. CONCLUSIONS

Based on the studies carried out and calculations made, the

following conclusions can be drawn.

1.Thermal conductivities of the fluids increase with content of

nanoparticles.

2.Viscosities of the fluids increase with content of nanoparticles.

3.Heat transfer coefficients are estimated analytically with

reasonable accuracy.

4.Cutting fluids with inclusion of nanoparticles have enhanced

heat transfer capacity upto 6% and decreases beyond.

5. Enhanced heat transfer being the epitome of MQL,

cutting fluids with inclusion of nanoparticles can be successfully

used in MQL.

6.An intelligent system can be successfully used to decide upon

the quantity of fluid.

Despite its useful findings and contributions, the work has

several possibilities of being extended.

1.Experimental verification of the calculations for nanofluids

may be carried out.

2.Increased viscosity has a detrimental effect on heat transfer

coefficient. However, as the viscosity increases, friction and

hence cutting forces decrease. This may have a positive impact

on the tool life and other affecting parameters. This is to be

investigated into.

3.Impact of different nanoparticles may be studied.

4.Microbial analysis of the nano cutting fluids may be studied to

assay the environmental impact.

5.Mist generation of the formulated fluids may be studied. As

the fluids have metallic inclusions, the mist, if any, may be

lethal and have fatal affect on the workers’ health.

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