Term Paper

Application of Orthogonal Array Design
for Predicting the Surface Roughness
Prof. SrinivasaRao.G
Suneel.D(Y12ME831)
SatyaKiran.K(L13ME997)
Geetha.J(Y12ME851)
Amarnath.J(Y12ME848)
ZudsonPaul.(L13ME1004)

WHY SURFACE
ROUGHNESS ?

 It affects several functional attributes of parts, such
as:
• Friction,
• Wear and tear
• Light reflection
• Heat transmission
• Ability of distributing and holding a lubricant,
coating etc.
Therefore, the desired surface finish is usually
specified and appropriate processes are required to
maintain the quality.

For this project we are using AISI 52100 steel

WHY ???

AISI 52100 Steel
Applications:
Taps, Gauges, swaging dies, Ejector pins, Ball & Roller
bearings.
It is a good quality steel for wear resisting machine parts
and for press tools which do not merit a more complex
quality.

In this project three process parameters namely cutting
speed, feed, depth of cut and two tool parameters namely
nose radius , normal rake angle were considered in
developing the surface roughness model.

Factor
symbol

Factor

Level
‘-1’

Level
‘0’

Level
‘+1’

60

75

90

0.052

0.078

0.104

v

Cutting speed (m/min)

f

Feed (mm/rev)

d

Depth of cut (mm)

0.2

0.4

0.6

r

Nose radius(mm)

4

8

12

α

Rake angle(degrees)

0

6

12

The total number of experiments to be performed to present all these combinations is 3 5 = 243.

So..
L18 (21X37) Orthogonal Array Design

Expt.no.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18

Factors
1
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1

2
-1
-1
-1
0
0
0
1
1
1
-1
-1
-1
0
0
0
1
1
1

3
-1
0
1
-1
0
1
-1
0
1
-1
0
1
-1
0
1
-1
0
1

4
-1
0
1
-1
0
1
0
1
-1
1
-1
0
0
1
-1
1
-1
0

5
-1
0
1
0
1
-1
-1
0
1
1
-1
0
1
-1
0
0
1
-1

6
-1
0
1
0
1
-1
1
-1
0
0
1
-1
-1
0
1
1
-1
0

7
-1
0
1
1
-1
0
0
1
-1
0
1
-1
1
-1
0
-1
0
1

8
-1
0
1
1
-1
0
1
-1
0
-1
0
1
-1
1
-1
0
1
-1

Based on the experimental data, a mathematical model
in terms of process and tool parameters was developed
for main surface roughness using multiple linear
regression analysis using SPSS (Statistical Package for
Social Sciences)

Ra= 3.653-0.541v+0.677f-0.240r-0.304v2-0.452vf0.194vd+1.077vr-0.398vα+0.234fd+0.213fα- 0.278rα.

THANK YOU