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Available online at www.ijapie.org
International journal of advanced production and industrial engineering
IJAPIE-2018-01-126, Vol 3 (1), 21-26
IJAPIE Connecting
Science & Technology with Management.
A Journal for all
Products & Processes.
(1Northern India Engineering College, Shastri Park, Delhi – 110053
2Maharaja Agrasen Institute of Technology, Delhi, -110086, India)
7ramakant@gmail.com,
| IJAPIE | ISSN: 2455–8419 | www.ijapie.org | Vol. 3 | Issue. 1 | 2018 | 21 |
Optimization of Temperature variations on Steel Grade EN-18 using Pin-on-disc
Method Srikant Rana
1, Sumit Kumar
1, Ramakant Rana
2
Abstract : In this era, technology has the main role and have tremendous number of industrial machines which are also used in
daily life. Steel is the basic industrial material used in all sectors. From all the Steel, Tool Steel have been extensively used and has
many applications in today’s technological industries. Tool Steel Grade EN-18 is used for the experimentation in this research. It
has noteworthy range of physical properties which can be imparted to various field. Experiments were conducted for analysing the
temperature variations on Steel Grade EN-18 using a pin-on-disc wear test rig as per ASTM specification G99. The temperature
rises at the contact area when there is relative motion between two mating surfaces. This motion also results in the failure of the
components. Experiments have been carried out to study and analyse the temperature variations of various material with respect to
tool steel, while the operational parameters were normal load, sliding velocity of pin w.r.t. rotating disk at room temperature and
different materials. Based on the experiments the dependency of temperature variations is found on applied load, sliding speed and
material.
Keywords: Friction, Wear, Speed, Pin-On-Disc, Taguchi, Optimization.
I. INTRODUCTION Mild steel is the most common form of steel and its price is
relatively low. The properties provided by this material are
acceptable for many applications. Mild steel has a relatively
low tensile strength, but it is cheap and malleable; surface
hardness can be increased through carburizing. It is often
used when large quantities of steel are needed [1-4].
In 1798, Rumford’s boring cannon experiment for detection
of frictional heat generation proved that mechanical work can
be converted into heat.
This experiment laid the foundation of experimental analysis
of mechanical equivalent of heat. However, no attempt was
made to measure the mechanical equivalent of heat
numerically. Over more than half a century later the
mechanical equivalence of heat was successfully established
by Joule [2] by envisioning a calorimetric method. Taylor
and Quinney’s [3] study of the generation of heat
accompanied by plastic strain strengthened the concept of
mechanical equivalence. They measured the temperature of
various specimens under tensile test during the formation of
creep and they found that the major amount of plastic energy,
used for deforming the specimen, gets converted into heat. In
metal cutting application, Taylor [4] studied the relation
between cutting velocity and tool life, and developed a tool
life equation. He also invented a tough, wear resistant, heat
resistant, and hard tool material (HSS) which is still in use.
Since then, scientists and researchers have been developing
various methods and techniques to estimate the temperature
variations at various points of tool, chip, and work piece.
II. EXPERIMENTAL SETUP Set up used in the study of wear test is capable of creating
reproducible abrasive wear situation accessing the abrasive
wear resistance of the prepared samples. It consists of a pin
on disc, loading panel and controller. The entire test was
carried out using a “pin on disk” machine with normal
condition. The condition has 40-50% relative humidity and at
room temperature. A high precision temperature measuring
device (accuracy ±0.01OC.) has been used to measure the
temperature of pin contact [Fluke Thermal image Camera,
Ti300]. In the due course of the experiment.
Fig. 1: Test-Rig used to Monitor temperature variations for
the Wear Tests
Srikant Rana et al.,
International Journal of Advanced Production and Industrial Engineering
| IJAPIE | ISSN: 2455–8419 | www.ijapie.org | Vol. 3 | Issue. 1 | 2018 | 22 |
III. DESIGN OF EXPERIMENT Table 1: Selected Parameters and their Level
Symbol
Process
Parameter
s
Unit
Leve
l 1 Leve
l 2 Leve
l 3
A Materials - Brass
Mild
Steel
Al
B Load Kg 2 5 8 C Speed Rpm
1000 1300
1600
IV. LAYOUT OF EXPERIMENT
Fig. 2: Tool Steel (Raw Material) used in Wear and Friction
testing.
The sliding distance was kept at 1.0 km for all tests various
levels of the load speed and pin material were listed in table.
Table 2: Composition of Tool Steel
MATERIAL COMPOSITION (%)
C
0.85-1.00
Mn
1.00-1.40
Si
0.50
Cr
0.40-0.60
Ni
0.30
W
0.40-0.60
V
0.30
Cu
0.25
P
0.03
S
0.03
In every experimentation, at least 3-5 values of temperature
were taken by clicking the photographs using Fluke Thermal
Image Camera, Ti300 as shown in Fig. 1. [12- 15]. The
maximum of each set was selected for the temperature
variations. These values were noted down in L9 OA for
Taguchi optimization techniques. Figure 3 (a) & (b) to Figure
11 (a) & (b) shows the temperature variation in each
experiment runs.
Table 3: L9 Orthogonal Array Input Parameters
S.NO.
Materials
Load
Speed
1
Brass
2
1000
2
Brass
5
1300
3
Brass
8
1600
4
Mild Steel
2
1300
5
Mild Steel
5
1600
6
Mild Steel
8
1000
7
Aluminium
2
1600
8
Aluminium
5
1000
9
Aluminium
8
1300
V. RESULT It is clear from the Fig. 4 that Brass has less thermal variation
as compared to Aluminium and Mild Steel [6, 7]. The wear
rate increases with the increase in Disc Speed but the
variation in temperature is more sudden. The major amount
of temperature occurs due to sticking of the material due to
the heat generated at the frictional contact [5, 8-11].
1) Temperature was lowest when: - Brass was used.
- Load is lowest i.e. 2kg
- Speed is highest i.e. at 1600 R.P.M.
Table 4: Mean values of Temperature Variations
S.NO. Materials Load Speed Temp.
(K)
1 Brass 2 1000 297.0 2 Brass 5 1300 312.3 3 Brass 8 1600 361.3 4 Mild Steel 2 1300 327.0 5 Mild Steel 5 1600 363.7 6 Mild Steel 8 1000 456.4 7 Aluminium 2 1600 430.3 8 Aluminium 5 1000 454.1 9 Aluminium 8 1300 599.5
Table 5: Response Table for Means for Temperature
Level Material Load Speed
1 323.5 351.4 402.5
2 382.4 376.7 412.9
3 494.6 472.4 385.1
Delta 171.1 121.0 27.8
Rank 1 2 3
Srikant Rana et al.,
International Journal of Advanced Production and Industrial Engineering
| IJAPIE | ISSN: 2455–8419 | www.ijapie.org | Vol. 3 | Issue. 1 | 2018 | 23 |
Srikant Rana et al.,
International Journal of Advanced Production and Industrial Engineering
| IJAPIE | ISSN: 2455–8419 | www.ijapie.org | Vol. 3 | Issue. 1 | 2018 | 24 |
Srikant Rana et al.,
International Journal of Advanced Production and Industrial Engineering
| IJAPIE | ISSN: 2455–8419 | www.ijapie.org | Vol. 3 | Issue. 1 | 2018 | 25 |
Fig. 12: Main of Means effect plots for Temperature
Variation
Fig. 13: Main of S/N Ratio effect plots for Temperature
Variation
Fig. 14: Contour Plot of “Temperature vs Load& Speed”
Fig. 15: Probabilistic Curve of Temperature Variations
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| IJAPIE | ISSN: 2455–8419 | www.ijapie.org | Vol. 3 | Issue. 1 | 2018 | 26 |
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