IRJET- Analysis of Process Parameters of Plasma ARC Cutting using Design of Experiment

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 06 | June 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 2733
ANALYSIS OF PROCESS PARAMETERS OF PLASMA ARC CUTTING USING DESIGN
OF EXPERIMENT
Prateek Kumar Gautam1, Vivek Gupta2
1M.Tech. Scholar, Department of Mechanical Engineering, Institute of technology & Management, Aligarh,
U.P., India
2Assistant Professor, Department of Mechanical Engineering, Sanskar College of Engineering and Technology,
Ghaziabad, U.P., India
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Abstract - In last forty years there is tremendous research in machining and development in technology. With increase
in competition in market and to attain high accuracy now a days the nonconventional machining are become lifeline of
any industry. One of the most important non conventional machining methods is Plasma Arc Machining. Its high
accuracy, finishing, ability of machining any hard materials and to produce intricate shape increases its demand in
market.
In thesis work literature has been studied in context to parametric optimization of Plasma Arc Cutting Machine. In order
to attain target and optimum results, Taguchi method employed. The appropriate orthogonal array has been selected as
per number of factors and there levels to perform minimum experimentation.
The work pieces of Stainless Steel (316 L) materials were used for experiment purpose. The optimum value has been
determined with the help of main effect plot and ANOVA table. The Regression equation for MRR and Surface Roughness
(Ra) has been developed with the help of Minitab 15 Software. Confirmation test have done to confirm the value
estimated through thesoftware.
The Confirmation for MRR run was done by using the setting of 5.0 bar (Gas pressure), 150 A (Current flow rate), 600
mm/min (cutting speed) and 4.0 mm (arc gap). The optimum parameter level for Surface Roughness are 6.0 Bar (Gas
Pressure), 150 A (Current), 400 mm/min (Cutting Speed) and 2 mm (Arc Gap). Experimental results are provided to
confirm the effectiveness of this approach. After the confirmation the MRR value was 0.8331g/secand Ra2.635µm. Error
within 10% was allowed.
INTRODUCTION
The topic for the thesis writing is the Analysis of Process Parameters of Plasma Arc Cutting Using Design of Experiment
Techniques. The focus on this project is to obtain an optimum condition (setting) to obtain maximum MRR and minimum the
surface roughness (SR).
A person doesn't need to be a physicist or chemist to understand the Plasma Arc Cutting (PAC) and Gouging process. There are
four states in which physical matter may be found: solid, liquid, gas or plasma. Changes from one physical state to another
occur, by either supplying or subtracting energy, in the form ofheat.
Water can be used as an example of these four states of matter. In the solid state it is ice at temperatures of 0 degrees Celsius
or colder. With the addition of heat the ice melts and changes to water, the liquid state. The addition of more heat to
temperatures of 212 degrees F. (100 degrees C.) or hotter) converts this liquid to its gaseous state,steam.
The fourth state of matter, plasma, looks and behaves like a high temperature gas, but with an important difference; it
conducts electricity. The plasma arc is the result of the electrical arcs heating of any gas to a very high temperature so that its
atoms are ionized (an electrically charged gas due to an unequal number of electrons to protons) and enabling it to conduct
electricity. The major difference between a neutral gas and plasma is that the particles in plasma can exert electromagnetic
forces on one another.
If you happen to be reading this by the light emitted by a fluorescent lamp you see plasma in action. Within the glowing tube of
the lamp is plasma consisting of low pressure mercury or sodium vapour. It is ionized by a high voltage across electrodes at

the ends of the tube and conducts an electric current which causes the plasma to radiate which in turn causes the phosphor
coating on the inner surface of the tube to glow [19] .
For many years, oxy-acetylene cutting was often the process of choice for quickly cutting through steel plate. Over the past few
years plasma cutting has pretty much taken over, for some very good reasons to perhaps most importantly. A plasma cutter
will cut through any metal that is electrically conductive. That means that one unit will cut steel, stainless steel, aluminium,
copper, bronze, and brass etc.
The plasma jet that does the cutting is hotter and narrower than an oxy-acetylene flame, so the kerfs width is smaller, and can
get cleaner cuts. This makes plasma cutting particularly well-suited for cutting sheet metal, a task the oxy-acetylene cutting
torch is not particularly well-suited for since it leaves a lot of slag on the edges. The extremely tight focus of the plasma arc
tends to minimize heat distortion in the cut parts, as well. Objectives of the present work
The present research work is undertaken to develop a new class of natural fiber reinforced polymer composite filled with
ceramic filler and to study their mechanical and erosion wear behavior. Attempts have been made to explore the potential use
of bamboo fiber as reinforcement in polymer composites.
2. Methodology
Problem statement
Plasma arc cutting can be characterized in terms of two distinct speeds. At cutting speeds above, the plasma jet does not
cut through metal plate. At speeds below, the molten metal from the kerf sticks to the bottom of the plate, forming the
so-called dross and how to properly select a plasma cutting system. Plasma can cut in a wide range of cutting parameters
(currents, metal thicknesses and nozzle orifice diameters) for plasma arc cutting of stainless steel materials.
The plasma arc cutting process employs a plasma torch with a very narrow bore to produce a transferred arc to the
work piece at an average current density of within the bore of the torch. The energy and momentum of the high-velocity
plasma jet generated by the plasma torch melts, vaporizes and removes the metal from the region of impingement of the
nozzle. Others problems:
1. What type of metal is to cutting?
2. What is primary input power when cutting process?
3. How thick is the metal want to cut?
4. Traditional way of cutting takes a lot of time.
5. The effective way to conduct the cutting process for Stainless Steel.
6. The most important factors that influence the cutting process?
7. What are the best conditions to achieve optimum performances?
Experimental Design
The objective of this research work is to study MRR and Surface roughness, the design variables can be
summarized as follows:
 Two levels of the Gas Pressure (6Bar and 7Bar).
 Two levels of Current Flow Rate (150A and 200A).
 Two levels of Cutting Speed (400mm/min and 600mm/min).
 Two levels of Arc Gap (2mm and 4mm)
For conducting the experiments, it has been decided to follow the Taguchi method of experimental design and an
appropriate orthogonal array is to be selected after taking into consideration the above design variables. Out of the
above listed design variables, the orthogonal array was to be selected for four design variables (namely Gas Pressure,
Current, Cutting Speed and Arc gap) which would constitute the L16 orthogonal array.
The two most important outputs are Material Removal Rate and Surface Roughness the same have been selected as
response parameters for this research work also. The effect of the variation in input process parameter will be studied

on these two response parameters and the experimental data will be analyzed as per Taguchi method to find out the
optimum machining condition and percentage contribution of each factor. The following machining parameters were
kept fixed.
Task
4.5 ANOVA (Analysis of Variance)
The purpose of the statistical analysis of variance (ANOVA) is to `investigate which design parameter significantly affects
the material removal rate and surface roughness. Based on the ANOVA, the relative importance of the machining
parameters with respect to material removal rate and surface roughness is investigated to determine more accurately
the optimum combination of the machining parameters.
Two types of variations are present in experimental data:
1. Within treatment variability
2. Observation to observation variability
So ANOVA helps us to compare variabilities within experimental data. In my thesis ANOVA table is made with
help of MINITAB 15 software. When performance varies one determines the average loss by statistically
averaging the quadratic loss.
The average loss is proportional to the mean squared error of Y about its target T. The initial techniques of the
analysis of variance were developed by the statistician and geneticist R. A. Fisher in the 1920s and 1930s, and are
sometimes known as Fisher's ANOVA or Fisher's analysis of variance, due to the use of Fisher's F- distribution as
part of the test of statistical significance.
Various formulas for ANOVA:
Degrees of freedom (DF)
Indicates the number of independent elements in the sum of squares. The degrees of freedom for each component of
the model are: DF (Factor) = r-1 DF (Error) = nt – r Total = nt – 1
Where nT = the total number of observations and r = the number of factor levels.
Sum of squares (SS)
The sum of squared distances. SS Total is the total variation in the data. SS (Factor) is the deviation of the estimated
factor level mean around the overall mean. It is also known as the sum of squares between treatments. SS Error is the
deviation of an observation from its corresponding factor level mean. It is also known as error within treatments. The
calculations are:
SS (Factor) = S ni (yi. - y..)2 SS Error = Si Sj (yij - yi. )2 SS Total = Si Sj (yij - y.. )2
Where yi.= mean of the observations at the ith factor level, y.. = mean of all observations and
yij = value of the jth observation at the ith factor level.
S. No. Machining Parameters Fixed Value
1 Material Type Stainless Steel (316 L)
2 Material Thickness 12 mm
3 Kerf 5mm
4 Operating Voltage 200 V

Pure sum of square
SS’ (Factor) = SS (Factor) – DF (Factor) * MS (Error)
Mean square (MS)
The calculations for the mean square for the factor and error are: MS (Factor) = SS (Factor)/ DF (Factor)
MS (Error) = SS (Error)/ DF (Error)
F Value
A test to determine whether the factor means are equal or not. The formula is: F = MS (Factor)/ MS (Error)
The degrees of freedom for the numerator are r - 1 and for the denominator are nT - r. Larger values of F support
rejecting the null hypothesis that the means are equal. Drill speed.
EXPERIMENTAL LAYOUT:
Since in my thesis work there are four factors and two levels for each which are shown below:
Values of variables at different level
After deciding parameters and levels as shown above orthogonal array L16 decided as per degree of freedom of each
factor and dof of interaction among the parameters. Data of parameter was collected in such a way that it shouldn’t
damage or cause any accident to operator and as per literature review. Now perform experiment as per orthogonal
array (L16) on Plasma Arc Cutting Machine Number B/0/2163, output like MRR and surface roughness is being given in
tabulated form. After the experimental results have been obtained, analysis of the results was carried out analytically as
well as graphically. Graphical analysis is done by MINITAB, shows interactions of all parameters. Then ANOVA of the
experimental data has been done to calculate the contribution of each factor in each response. Then we calculated S/N
ratio for MRR and surface roughness of specimens.
Then we obtain optimal conditions has been calculated for MRR and surface roughness of specimen. The following table
shows readings of MRR and surface roughness at each experiment, it also shows S/N ratio for MRR and surface
roughness at each experiments.
Calculation Sheet for MRR and Surface Roughness
Exp No. Mass 1
(Before
Cutting)
Mass 2 (After
Cutting)
Mass Loss (g) Time
Taken
(Sec)
MRR
(g/Sec)
Surface
roughness
1 90 61.2 28.8 45 0.640000 3.834
2 87 58.6 28.4 45 0.631111 3.688
3 85.4 56.4 29 40 0.725000 4.393
4 79.05 49.65 29.4 36 0.816667 4.679
5 98.54 69.74 28.8 40 0.720000 3.180
6 79.69 52.69 27 36 0.750000 3.458
7 102.77 73.87 28.9 36 0.802778 4.571
8 99.48 70.68 28.8 35 0.822857 3.568
9 82.63 56.23 26.4 40 0.660000 3.255
Control Factors Unit Level 1 Level 2 DOF
Gas Pressure bar 5 6 1
Current Flow Rate ampere 150 200 1
Cutting Speed mm/min 400 600 1
Arc Gap mm 2 4 1

10 82.67 53.77 28.9 39 0.741026 3.688
11 72.4 43 29.4 38 0.773684 3.951
12 73 43.2 29.8 37 0.805405 3.958
13 93.45 64.65 28.8 49 0.587755 2.352
14 89.1 60.9 28.2 47 0.60000 2.636
15 86.75 58.55 28.2 37 0.762162 3.969
16 93.27 64.77 28.5 35 0.814286 4.123
Plasma Arc Cutting System:
Plasma Arc Cutter used in this work is Silverin Make with Sharp line Bombay make Burny 10 LCD. Before cutting, worker
always know plasma arc cuts all electrically conductive metals (Ox fuel is usually limited to steel), plasma arc cutting requires
no preheating, turnaround time is fast, the process produces a small heat-affected zone.
Table 3.3 Technical Features
Digital Weight Balancer
The weight of the work pieces (specimens) before and after the cutting process need to be measured in order to obtain the
amount of Material Removal Rate (MRR).
Surface Roughness Tester
There are five steps to measure the surface roughness of specimens. Firstly, clamp the work piece of project use a clamping in
the machine. And then, setting a prop of axis likes up and down, right or left direction. After finish setting, can start measured
a work piece. Lastly, a data value for roughness can print out after finish measured.
The surface roughness tester (FORM TALY SURF) used in this work, with the following specifications:
Manufacturer: Taylor Hobson, U.K, Travelling length: 01mm-50mm, Force: 4mN,
Stylus: Diamond 2µm tip radius, Resolution: 16nm/1.0mm,
Software: Form ultra software
Power Supply
The power supply required depends on the material thickness and cutting speeds desired. Increasing the power increases the
cutting speed or enables thicker metals to be
cut without slow down. Power ratings are commonly between 20 and 200 kW.
Technical Features Machine
Supply voltage 3x400V - 50Hz
Rated power 30 kW
Operating pressure 5 bar
Primary fuse 16 A
Open circuit voltage 260 V
Pilot arc current 50 A

Fig. DC Power Supply Source
DESIGN FACTORS
Design of Experiments technique has been utilized to obtain the best combination of design factors to achieve optimum
performance measures. Plasma Arc Cutting involves several input parameters to be considered during machining process. In
this thesis, the combination factors such as Gas Pressure [bar], Current Flow Rate [A], Cutting Speed [mm/min] and Arc Gap
[mm] are considered. These factors are the most important to have the best value for Material Removal Rate (MRR) and
Surface Roughness (Ra) when cutting material like Stainless Steel or Nickel Base A
3. DATA COLLECTION AND RESULTS
16 test specimens having dimension 30mm x 30mm x 12 mm were prepared for the experimental work.
The material for test specimen was Stainless Steel ASTM A 240 TP 316 L. Here L stands for Low Carbon Content.
Fig. Test Specimen
EQUIPMENTS
Equipment for the experiment use is:
Plasma arc cutting system Silvering Make with Sharpline Bombay make Burny 10 LCD
Digital weight balancer equipment

The surface roughness tester (FORM TALY SURF) Taylor Hobson Make (U.K.)
Result
The Optimum levels of parameters for maximizing MRR are A1 B2 C2 D2 i. e. Gas Pressure: 5 Bar
Current: 150 A
Cutting Speed: 600 mm/min Arc Gap: 4mm
The optimum levels of parameters for minimizing Surface Roughness (Ra) are A2 B2 C1 D1 i. e.
Gas Pressure: 6 Bar Current: 150 A
Cutting Speed: 400 mm/min Arc Gap: 2 mm
After performing experiment as per given optimum levels for MRR and SR following results obtained:
Table Results Before and After Optimisation
So we can say that there is 0.81% improvement in MRR and also Surface Roughness reduce with 5.91%. This finding indicated
that the experiments in this study possess excellent repetitiveness and great potential for future reference.
EXPERIMENTAL RESULTS FOR MRR
Graph :Effects of various factors on S/N Ratio of MRR
By using MINITAB software we obtain some interactions if we look at the graph we will observe that with increase in Gas
Pressure MRR S/N ratio is decreasing. Material removal rate increases with increase in Current, Cutting Speed and Arc gap.
MRR (g/sec) Predicted value of
A1B2C2D2 = 0.8264
Experimental result of
A1B2C2D2=0.8331
Percentage
= 0.81%
Surface Predicted value of A2B2C1D1 =
2.8006
Experimental result of
A2B2C1D1=2.635
Percentage
= 5.91%

EXPERIMENTAL RESULTS FOR SURFACE ROUGHNESS
Graph : Effects of various factors on S/N Ratio of SR
Above graph represent the effect of parameters on Surface Roughness. It can be seen that as value of Gas Pressure and Current
increases, S/N ratio of Surface roughness also increases. However S/N ratio of Surface roughness decreases with increase in
the Cutting Speed and Arc Gap.
CONCLUSIONS:
This thesis has presented an application of the Taguchi method to the optimization of the machining parameters of
Plasma Arc Cutting Machine. As shown in this study, the Taguchi method provides a systematic and efficient
methodology for determining optimal parameters with far less work than would be required for most optimization
techniques. The confirmation experiments were conducted to verify the optimal parameters. It has been shown that
Material Removal Rate (MRR) and Surface Roughness (Ra) can be significantly improved in the Plasma Arc Cutting
process using the optimum level of parameters.
Plasma Arc Cutting Machine is widely utilized in BHEL, Bhopal to cut materials such as Stainless Steel and Nickel-Base
Alloys. This is the basis work where Plasma Arc Cutting was utilized to perform the material removal process at finishing
stage. The Plasma Arc Cutting (PAC) machining of Stainless Steel (316L) has been performed with the application of
combination with design of experiment (DOE).The PAC parameters studied were how to have setting for the parameter
such as Gas Pressure, Current flow, Cutting Speed and Arc gap of machine.
From ANOVA of MRR we can say that some parameters are not making any significant effect .This is because we must
take large number of observations either by considering L27 0r L32 orthogonal array with 3 level designs.
Mathematical equation for MRR of first order is of R-sq of 71.2% and for Surface Roughness (Ra) is of R-sq 77.5% which
is acceptable.
Signal-to-noise: Smaller is better
Main Effects Plot for SN ratios
Data Means

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