machining behavior of en24 and en36c steelsijiet.com/wp-content/uploads/2019/04/4.pdfchip reduction...

International Journal of Innovations in Engineering and Technology (IJIET)

http://dx.doi.org/10.21172/ijiet.124.04

Volume 12 Issue 4 March 2019 021 ISSN: 2319-1058

Machining Behavior of En24 and En36c Steels

Nikhil Bharat1, Vishal Mishra2, Dr Kalyan Chakraborty3 1,2M.Tech (Mechanical) Student, Department of Mechanical Engineering

National Institute of Technology, Silchar, Assam 3Associate Professor, Department of Mechanical Engineering

National Institute of Technology, Silchar, Assam

Abstract EN24 and EN36C steels are among the steels that are used in dynamic environment and in heavy duty

applications. The paper presents the machinability of EN24 and EN36C steels with reference to turning of the work

materials on lathe using carbide insert. Principal aim of investigation was to know the mechanism of chip formation and

von Mises stress (VMS) generation during machining. Severe plastic deformation occurs in the primary deformation zone

(PDZ) and subsequently chip forms and von Mises stress generates. Cutting velocity, feed and depth of cut (d.o.c) are the

input parameters for machining on work material and chip reduction co-efficient (CRC) and von Mises stress (VMS) are

the output parameters. 33 factorial design of experiment was considered to conduct the experiment. The von Mises stress

(VMS) was determined employing CRC and material properties namely strain hardening exponent ‘n’ and strength co-

efficient ‘K’.

Presence of residual stress on machined item has to be identified as this may cause some detrimental effect on machined

component. Therefore, presence of such stress was identified through XRD study in the present work.

Finally, behavior of chip material during formation was also observed by SEM and EDX examination.

Keywords Chip reduction coefficient (CRC); von Mises stress (VMS); Chip formation mechanism.

I. INTRODUCTION

EN24 and EN36C steels are usually used for production of various mechanical components. These materials are processed extensively by machining. Therefore, present study is aimed at to determine machinability of these

materials. Machining response parameters like tool wear, surface roughness, cutting forces etc are usually

considered for machinability assessment. Induced von Mises stress (VMS) on machined surface can be another

factor to be considered for machinability assessment.

Machining process is based on plastic deformation of work material. Machining chip is formed through plastic

deformation only. Chip reduction coefficient(ξ) can be considered as an index of plastic deformation. Machining

process is very much influenced by deforming behaviour of work material. It is therefore necessary to incorporate

CRC as an index for determination of induced von Mises stress (VMS) on the machined item. Generated von Mises

stress (VMS)on the machined component is also strongly influenced by property of the work material.

Present work illustrates the method for determination of von Mises stress (VMS) based on deformation index (CRC)

and material property namely strength coefficient ‘K’ and strain hardening exponent ‘n’. This method for determination of von Mises stress (VMS) employing ξ, n and K can be considered as most appropriate consideration

since von Mises stress (VMS) generation is directly related toplastic deformation and subsequently to property of

materials. Literature considering this procedure to determine the von Mises stress (VMS) on the machined

component employing ξ, n and K is scarce.

Vishal Mishra et al. [1] performed machining on EN24 and EN36C steels using carbide tool and found that tool

wear takes place through adhesion and chipping while machining EN24 steel. They also observed that for machining

with EN36C steel, tool wear takes place through abrasion.

Vishal Mishra et al. [2] studied the effects of von Mises stress (VMS) generation during Machining on EN36C steel.

It was observed that EN36C steel showed better results during maching at cutting speed: 60m/min, feed:

0.63mm/rev and doc: 1mm.

Geethanjali KS et al. [3] studied the effects of machining on tool forces, power consumption and surface roughness.

It was observed that for EN19 steel and EN24 steel, cutting speed has a significant effect on power. Nikhil Bharat et al. [4] conducted experiment on EN24 steel on lathe using carbide tool and concluded that EN24

steel can be machined at higher speed, feed and depth of cut (d.o.c).

II. EXPERIMENTAL PROCEDURE

In the present study EN24 and EN36C steels are used as work materials having 400mm of length and 110mm of

diameter. Machining was performed on central lathe by using tool insert of coated carbide grade. Table 1 and table 2

show the chemical compostion of work material.




Table 1. Chemical composition of EN24 steel

%Fe %C %Mn %Si %P %Cr %Mo %Ni %Al %S

Balanced 0.398 0.582 0.206 0.029 1.04 0.246 1.36 0.0235 0.0164

Table 2. Chemical composition of EN36C steel.

%Fe %C %Mn %Si %P %Cr %Mo %Ni %Al %S

Balanced 0.159 0.386 0.182 0.0164 0.820 0.131 3.10 0.0182 0.0199

Central lathe was employed for machining on the work material which has speed range of 45 rpm to 1000 rpm and

feed range of 0.06 mm/rev to 1.72 mm/rev.

2.1. Tool Specification Holder specification: ASBNR 25*25 M12-A

Holder Specifications Designation System Assigned Values

A Clamping system Double clamping

S Insert shape Square

B Cutting edge style Principle Cutting edge angle=15o

N Relief angle of insert 0o

R Hand of tool Right hand

25*25 Shank size 25mm*25mm(height*width)

M Holder length 150mm

12 Insert size 12mm

A Machining insert Turning

Insert Specification: SNMG 120404 TM T9125

Insert Specifications Designation System Assigned Value

S Insert shape Square with hole

N Relief angle 0o

M Accuracy Tolerance

G Groove Cylindrical hole

12 Cutting edge length 12mm

04 Thickness 4mm

04 Corner radius 4mm

TM Chip breaker symbol TM

T9125 Stocked grade Coated

Cutting speed, feed and depth of cut (d.o.c) are the input process parametrs used for the experimentation. The

experimentation was based on 33 factorial design. Table 3 shows the arrangement of input process parameters with

given level of cutting.

Table 3. Input parameters used for machining.

Factors Level 1

(lowest level)

Level 2

(moderate level)

Level 3

(highest level)

Coding -1 0 1

Speed (m/min) 36 60 100

Feed (mm/rev) 0.49 0.63 0.86

D.O.C (mm) 0.67 1 1.5




Formulation for the selection of input process parameter values for the level.

Where,

Code(v,f,d)=values for various codes with reference to speed,feed and d.o.c

(v,f,d)m= cutting speed, feed and doc at moderate level.

(v,f,d)max= cutting speed, feed and doc at highest level.

Based on the above given input process parameters, 33 factorial design of experiment was done which provided 27

different combinations.

Table 4. 33 factorial design is showing the input parameters for machining.

S.No. Assigned Codes Velocity (V)

m/min

Feed (f)

mm/rev

Depth of cut (d)

mm V F d

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

-1

-1

-1

-1

-1

-1

-1

-1

-1

0

0

0

0

0

0

0

0

0

1

1

1

1

1

1

1

1

1

-1

-1

-1

0

0

0

1

1

1

-1

-1

-1

0

0

0

1

1

1

-1

-1

-1

0

0

0

1

1

1

-1

0

1

-1

0

1

-1

0

1

-1

0

1

-1

0

1

-1

0

1

-1

0

1

-1

0

1

-1

0

1

36

36

36

36

36

36

36

36

36

60

60

60

60

60

60

60

60

60

100

100

100

100

100

100

100

100

100

0.49

0.49

0.49

0.63

0.63

0.63

0.86

0.86

0.86

0.49

0.49

0.49

0.63

0.63

0.63

0.86

0.86

0.86

0.49

0.49

0.49

0.63

0.63

0.63

0.86

0.86

0.86

0.67

1

1.5

0.67

1

1.5

0.67

1

1.5

0.67

1

1.5

0.67

1

1.5

0.67

1

1.5

0.67

1

1.5

0.67

1

1.5

0.67

1

1.5

Cutting velocity V= (m/min)

Where,

N = Spindle speed (rpm).

D = diameter of work material (mm)




Based on the coding and the assigned values as mentioned in table 4, machining of the work material was carried out

for a time period of 30 seconds.

From the experimentation, 27 different types of chip samples were collected. Each chip was takenand its

corresponding weight and length were measuredandfurther the chip thickness was determined.

Figure 1(a). EN36C steel mounted on lathe. Figure 1(b).EN24 steel mounted on lathe.[4]

Figure1(c). Tool insert with holder. Figure 1(d). Carbide tool insert.

After completion of 27 experiments, tensile testing specimen of the work material was prepared according to

ASTM E8 standard and it was subjected to tensile test by INSTRON 1195 UTM machine and the true stress-true

stress curve was obtained from experimental data. From the curve, three points within the yield point and ultimate

stress point were selected and were then plotted on log-log graph paper. The straight line that was obtained on the

log-log graph was extrapolated and the strength coefficient ‘K’ and the strain hardening exponent ‘n’ of the work

material was recorded. In the same context, on getting the value of K and n, power equation (σ = Kɛn) was obtained

as

σEN24 = 1240ɛ0.207

σEN36C = 1495ɛ0.178

Where, σ = true stress (MPa).

ɛ = true strain

Figure 2(a). True stress vs True strain log-log graph for EN 24 steel.[4]




Figure 2(b). True stress vs True strain log-log graph for EN36C steel. [2]

Formulations

Uncut chip thickness (t1)= f * sinϕ

Where

ϕ = Principal cutting edge angle (degree).

f = feed (mm/rev)

Formed chip thickness (t2)= W (mm)

Where ρ𝑤𝑙 W = weight of chip (gm).

l = length of chip (mm).

𝑤 = width of chip (mm)

ρ = density of steel (0.008 gm/mm3).

Width of a chip (w) = d (mm)

cos(90 − Ѳ)

Where

d = depth of cut (mm).

Ѳ = Principal approach angle (degree)

Chip reduction coefficient (ξ) = t2 (mm)

t1

Von Mises stress σv = 1.74*K*(lnξ)n (MPa)

Another set of experiments were conducted by face turning on the workpiece at

Cutting speed = 135.72 m/min. Feed = 0.86 mm/rev.

Depth of cut = 1.2 mm.

Machined region from the face surface was sectioned by using hacksaw to prepare sample inorder to identify the

presence of any residual stress through XRD study. Cu target was used for the purpose. Sample from the

unmachined region was also prepared for the same study.

EDX analysis was performed to identify material deposition if any from work material to tool rake face.

III. RESULTS AND DISCUSSIONS

Analysis of variance considering the experimental data for CRC was done. Results of ANOVA are shown in table 5

and table 6.

Table 5. ANOVA analysis for CRC of EN24 machining chip

Result Details

Source SS df MS

Between-treatments 1.5793 2 0.7896 F = 4.72602

Within- treatments 4.0099 24 0.1671




Total 5.5892 26

The f-ratio value is 4.72602. The p-value is 0.018598. The result is signification at p < 0.05.

Table 6. ANOVA analysis for CRC of EN36C machining chip

Result Details

Source SS df MS

Between-treatments 0.4969 2 0.2485 F = 5.29175

Within- treatments 1.1268 24 0.047

Total 1.6237 26

The f-ratio value is 5.29175. The p-value is 0.012477. The result is signification at p < 0.05.

It is apparent that the experimental CRC data for both EN24 and EN36C steels are statistically acceptable (p<0.05) and therefore, further study can be explored.

From the input and output data, second order regression equations for CRC and von Mises stress are obtained for

both the steels using MINITAB software which are mentioned below: -

For EN24 Steel

bCRC = 2.3193 + 0.1127x1 - 0.2205x2 + 0.0156x3 - 0.4538x1² + 0.036x2² - 0.35x3² - 0.030x1 x2 - 0.056x1 x3 -

0.161x2x3 (eq.a)[4]

bVMS = 2106.5 + 18 x1 - 87.5 x2 + 14.5 x3 - 234 x1² + 33.7 x2² - 170.9 x3² - 50.2 x1 x2 - 13.9 x1 x3 - 93.6 x2x3

(eq.b)[4]

For EN36C Steel

bCRC = 1.3334 - 0.0561x1 - 0.0322x2 - 0.0163x3 - 0.2708x12 + 0.1474x2

2 + 0.0563x32 + 0.0366x1x2 + 0.0183x1x3 -

0.0093x2x3 (eq. c)[2] bVMS= 1810.7 - 76.2x1 – 25.1x2 - 7x3 - 324x1

2 + 265.7x22 + 157.9x3

2 + 101.5x1x2 + 129.5x1x3 - 374x2x3

(eq. d)[2]

Using above equations, 3D plots were made using MATLAB software considering depth of cut as constant factor

which are mentioned below: -

At lowest depth of cut (-1)

-1

-0.5

0

0.5

1

-1

-0.5

0

0.5

11.6

1.8

2

2.2

2.4

SPEED CODE

CRC FOR DOC -1

FEED CODE

CR

C

-1

-0.5

0

0.5

1

-1

-0.5

0

0.5

11.35

1.4

1.45

1.5

1.55

1.6

SPEED CODE

CRC FOR DOC= -1

FEED CODE

CR

C

Figure 3(a). Variation of CRC w.r.t cutting speed Figure 3(b). Variation of CRC w.r.t cutting speed

and feed code for d.o.c code -1 for EN24 steel. and feed code for d.o.c code -1 for EN36C steel.

From Figure 3(a) at code -1, for EN24 steel, CRC increase with increase of speed was observed. Increased speed

causes temperature rise in primary deformation zone leading to thermal softening. This causes increased CRC at

high speed. Effect of feed on CRC is found to be minimized.

From Figure 3(b) at code -1, for EN36C steel, it was observed that CRC reduced with increase of speed. Strain hardening of the work material occurs at higher speed leading to brittleness transition of the work material. This

causes lower CRC at higher speed. Effect of feed on CRC is found to be minimized.




-1

-0.5

0

0.5

1

-1

-0.5

0

0.5

11740

1760

1780

1800

1820

1840

SPEED CODE

VMS FOR DOC -1

FEED CODE

VM

S (

in M

Pa)

-1

-0.5

0

0.5

1

-1

-0.5

0

0.5

11600

1800

2000

2200

2400

2600

2800

SPEED CODE

VMS FOR DOC= -1

FEED CODE

VM

S (

in M

Pa)

Figure 4(a). Variation of VMS w.r.t cutting speed Figure 4(b). Variation of VMS w.r.t cutting speed

and feed code for d.o.c code -1 for EN24 steel. and feed code for d.o.c code -1 for EN36C steel.

From Figure 4(a) at code -1, it is apparent that for EN24 steel, VMS increases with increase of speed. Increase in

CRC at higher speed causes increase of VMS. This is attributed to thermal softening during chip formation. Effect

of feed on VMS is found to be negligible.

From Figure 4(b) at code -1, it is seen that for EN36C steel, VMS reduces with increase in speed. Reduced VMS at

higher speed is owing to brittleness transition of work material. Increased feed causes increase of VMS. Such

increase of VMS is due to thermal softening leading to higher CRC.

At moderate depth of cut (0)

-1

-0.5

0

0.5

1

-1

-0.5

0

0.5

11.8

2

2.2

2.4

2.6

SPEED CODE

CRC FOR DOC 0

FEED

CR

C

-1-0.5

00.5

1

-1

-0.5

0

0.5

11.3

1.35

1.4

1.45

1.5

SPEED CODE

CRC FOR DOC= 0

FEED CODE

CR

C

Figure 5(a). Variation of CRC w.r.t cutting speed Figure 5(b). Variation of CRC w.r.t cutting speed

and feed code for d.o.c code 0 for EN24 steel. and feed code for d.o.c code 0 for EN36C steel.

-1

-0.5

0

0.5

1

-1

-0.5

0

0.5

11850

1900

1950

2000

2050

2100

SPEED CODE

VMS FOR DOC 0

FEED CODE

VM

S

-1

-0.5

0

0.5

1

-1

-0.5

0

0.5

11900

1950

2000

2050

2100

2150

SPEED CODE

VMS FOR DOC= 0

FEED CODE

VM

S (

in M

Pa)

Figure 6(a). Variation of VMS w.r.t cutting speed Figure 6(b). Variation of VMS w.r.t cutting speed


From Figure 5(a) and Figure 5(b), it is observed that at code 0,EN24 and En36C steel follow similar trend as with

Figure 3(a) and Figure 3(b).




From Figure 6(a), it is seen that at code 0 for EN24 steel, VMS increases with increase in speed which is attributed

to thermal softening effect at higher cutting speed. VMS reduces with increase of feed because of brittleness

transition of the work material at this cutting condition.

From Figure 6(b), it is observed that at code 0 for EN36C steel, effect of feed on VMS is seemed to be less

significant. Otherwise trend is similar as with Figure 4(b). At highest depth of cut (1)

-1

-0.5

0

0.5

1

-1

-0.5

0

0.5

11.4

1.6

1.8

2

2.2

2.4

2.6

SPEED CODE

CRC FOR DOC 1

FEED CODE

CR

C

-1

-0.5

0

0.5

1

-1

-0.5

0

0.5

11.35

1.4

1.45

1.5

1.55

SPEED CODE

CRC FOR DOC= 1

FEED CODE

CR

C

Figure 7(a). Variation of CRC w.r.t. cutting speed Figure 7(b). Variation of CRC w.r.t. cutting speed


From Figure 7(a) at code 1, for EN24 steel, it is apparent that similar trend is obtained as with Figure 5(a). CRC

increases with increase in speed. CRC reduces with increase in feed, which is attributed to the strain hardening

effect at higher feed. From Figure 7(b) at code 1, for EN36C steel, almost similar trend is observed as with Figure 5(b).

-1

-0.5

0

0.5

1

-1

-0.5

0

0.5

11600

1700

1800

1900

2000

2100

SPEED CODE

VMS FOR DOC 1

FEED CODE

VM

S (

in M

Pa)

-1

-0.5

0

0.5

1

-1

-0.5

0

0.5

11600

1800

2000

2200

2400

2600

2800

SPEED CODE

VMS FOR DOC= 1

FEED CODE

VM

S (

in M

Pa)

Figure 8(a). Variation of VMS w.r.t. cutting speed Figure 8(b). Variation of VMS w.r.t. cutting speed


From figure 8(a) at code 1, for EN24 steel, similar trend as with Figure 6(a) is found. VMS reduces with increase of

feed because of strain hardening of the work material during chip formation. Such phenomenon causes brittleness

transition of work material during chip formation process.SEM examination of under surface of the chip (Figure

9(a)) showed the presence of massive crack indicating brittleness transition of the material during chip formation.

SEM examination of fractured surface of the chip also showed the chip fracture by brittle mode (Figure 9(b)).

Figure 9(a). SEM image of chip under surface Figure 9(b). SEM image of a fractured chip at a cross

at 500X magnification for EN24 steel. [4] section at 2500X magnification for EN24 steel. [4]




From Figure 8(b) at code 1, it is seen that for EN36C steel, VMS increases with increase in speed because of thermal

softening. Chip side edge along with top surface was viewed under scanning electron microscope and found that

much deformation had taken place in the chip through ductile mode. (Figure 10(a)) [2]. Moreover, SEM

examination of chip fractured surface indicated ductile separation of chip during fracture. Numerous dimples are

observed in SEM micro-graphof chip fractured surface (Figure 10(b)). This finding illustrates the dominating role of temperature so as to cause ductile transition of the material at primary deformation zone during the process of

chip formation.

VMS reduces with increase in feed. Higher feed causes more strain hardening of the work material leading to

reduced VMS at higher feed.

Figure 10(a). SEM image of the side edge of Figure10(b). SEM image of the fractured surface of

chip at 3000X magnification for EN36C steel. [2] chip at 10000X magnification for EN36C steel. [2]

3.1 Experimental and predicted analysis

Figure 11(a) and Figure 11(b) show the variation between experimental and predicted values for CRC of EN24 chip

and EN36C chip.

Figure 11(a).Comparison chart between experimental CRC and predicted CRC for EN24 chip.

Figure 11(b).Comparison chart between experimental CRC and predicted CRC for EN36C chip.




Figure 12(a) and Figure 12(b) show the variation between experimental and predicted values for VMS of EN24 and

EN36C steels respectively.

Figure 12(a).Comparison chart between experimental VMS and predicted VMS for EN24 steel.

Figure 12(b).Comparison chart between experimental VMS and predicted VMS for EN36C steel.

XRD analysis of the work material

For EN24 steel.

20 40 60 80 100 120

5000

10000

15000

INT

EN

SIT

Y

2

INTENSITY

20 40 60 80 100 120

10000

15000

20000

25000

INT

EN

SIT

Y

2

INTENSITY

Figure 13 (a) Phase position for core region Figure 13(b) Phase position for face turningsurface

(un-machined region) obtained from XRD. at V = 135.72 m/min, f = 0.86 mm/rev and d.o.c =

1.2mm obtained from XRD.




For EN36C steel.

15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95

10000

15000

20000

25000

INT

EN

SIT

Y

2

INTENSITY

20 40 60 80 100 120

8000

10000

12000

14000

INT

EN

SIT

Y

2

INTENSITY

Figure 14 (a).Phase position for core region Figure 14 (b) Phase position for face turning

(un-machined region) obtained from XRD. surface at V = 135.72 m/min, f = 0.86 mm/rev

and d.o.c = 1.2mm obtained from XRD.

Figure 13(a) and Figure 13(b) show the peaks (α-Fe) of the un-machined and machined samples for EN24 steel.

From XRD data, it is observed that there is some difference with reference to the peak position considering two conditions. This illustrates the presence of residual stress within the machined sample.

Figure 14(a) and Figure 14(b) show the peaks (α-Fe) of the un-machined and machined samples for EN36C steel.

Using XRD data It is seen that there is also peak shift with the machined sample with respect to the peak position for

the un-machined sample. This finding confirms the presence of residual stress within the machined workpiece for

EN36C steel.

EDX analysis

Considering machining parameters forEN24 steel, V = 125m/min, f = 0.86mm/rev, d.o.c = 1.5mm and time period

(t) = 3min.

Table 7. Chemical composition of diffused and deposited element on tool rake face

Result Type Weight %

Spectrum Label Spectrum 7 C 63.37

O 6.15

Al 0.19

Si 0.76

P 0.00

Ti 15.30

Cr 0.00

Mn 0.01

Fe 11.15

Ni 0.04

Mo 3.03 Total 100.00




Figure 15(a) Material deposited at location 1 on tool rake face (EDX)

Figure15(b). Composition of material deposit at location 1 on tool rake face(EDX).

Figure 15(a) &Figure 15(b) showthe material deposited location 1 (EDX) and EDX spectrum respectively for EN24

material deposition on tool rake face. It is seen that work material deposit takes place on the tool rake face in

addition of which some transport from tool occurred to the deposited material through diffusion (Table 7)

Considering machining parameters for EN36C steel at V = 125m/min, f = 0.86mm/rev, doc = 1.5mm and time

period (t) = 3min

Table 8. Chemical composition of diffused and deposited element on tool rake face

Result Type Weight % Spectrum Label Spectrum 3

C 74.60

Al 14.71

Si 5.80

P 0.25

S 0.42

Cr 0.06

Mn 0.05

Fe 2.19

Ni 0.07

Mo 1.87 Total 100.00

Material deposit

location 1.




Figure 16. (a) Material deposit at location 2 on tool rake face (EDX)

Figure 16. (b)Composition of material deposit at location 2(EDX).

Figure 16(a) &Figure 16(b) show the material deposited location2 (EDX) and the EDX spectrum for EN36C

material deposition on tool rake face respectively. Material deposition from work material to tool rake face (along with tool elemental diffusion to deposited material) is identified (Table 8)

IV. CONCLUSION

Effect of feed is to lower the VMS at different depth of cut conditions for EN24 steel.

Effect of speed is to raise the VMS at various depth of cut conditions for EN24 steel.

Effect of feed at highest depth of cut condition is to reduce the VMS for EN36C steel. However, at lowest depth of

cut VMS increases with feed.

Effect of speed at highest depth of cut is to raise the VMS for EN36C steel. However, at lowest depth of cut VMS

reduces with speed with EN36C steel.

Residual stress is found to be present in both the steelswhen machined at higher speed, feed and d.o.c condition.

Material transport from work material to tool and tool to work material takes place during machining on EN24 and

EN36C steels through diffusion.

Material deposit

location 2




V. ACKNOWLEDGEMENT

The authors sincerely and gratefully acknowledge the assistance provided by IIT Kanpur while using various

laboratories at IIT Kanpur.

VI. REFERENCES [1] Vishal Mishra, Nikhil Bharat & Kalyan Chakraborty, “Comparative assessment on the machinability of EN 24 and EN 36C Steels.”

International Journal of Engineering and Advanced Technology (IJEAT) Volume-8 Issue-3, February 2019) ISSN: 2249 – 8958.

[2] Vishal Mishra & Dr. Kalyan Chakraborty, “Machinability of Nickel Chromium Case Hardened Steel (EN36C).” Global Journal of

Researches in Engineering: A Mechanical and Mechanics Engineering Volume 19 Issue 1 Version 1.0 Year 2019. Online ISSN: 2249-4596

Print ISSN:0975-5861.

[3] Geethanjali KS, Ramesha C.M, Chandan B.R, “Comparative Studies on Machinability of MCLA Steels EN19 and EN24 Using Taguchi

Optimization Techniques.” Materials Today: Proceedings 5 (2018) 25705–25712.

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machining behavior of en24 and en36c steelsijiet.com/wp-content/uploads/2019/04/4.pdfchip reduction...

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