In order to reduce the no of experiments required for finding the output .here we use these mathematically process in order to find output (in our case it is STRENGTH). without using further experiments

1. Mahatma Gandhi Mission's
College Of Engineering and Technology
Noida, 201301
2014-2015
Project Presentation
OPTIMIZATION OF PROCESS PARAMETERS IN TIG
WELDING USING TAGUCHI METHOD AND REGRESSION
ANALYSIS
Project Guide: Presented by
Mr. Abhijit A. Kulkarni Sukhendu Singh (1109540036)
Varun Grover (1109540038)
Vivek Bisht (1109540043)

2. INTRODUCTION
• TIG Welding is a non consumable electrode.
• Arc produced between Tungsten electrode &
work piece.
• Used for thin section jobs.
• Metals that can be welded are MS, SS, &
Non-Ferrous like Aluminum etc.
• Shielding gas prevents oxidation.
• Filler material is optional.
• Slower weld speeds with stronger welds.

3. OPTIMIZATION OF TIG WELDING
PROCESS PARAMETERS
GOAL: Optimize process parameters for TIG
welding.
• The purpose is to efficiently determine
the optimum welding parameters for
achieving the HIGHEST ULTIMATE
TENSILE STRENGTH in the range of
parameters.
• In order to meet the purpose in terms of
both efficiency and effectiveness,
TAGUCHI METHOD AND
REGRESSION ANALYSIS are utilized.

4. NEED FOR OPTIMIZATION
ENSURING
QUALITY OF
PRODUCT
REDUCING
MANUFACTURING
COST
INCREASING
PRODUCTIVITY
INCREASING
TENSILE STRENGTH

5. Taguchi methods are statistical methods developed by Genichi
Taguchi to improve the quality of manufactured goods.
The data is collected & arranged as an “ORTHOGONAL ARRAY”.
Experiments which gives most reduced variance for the experiment
with optimum settings of control parameters are used.
Thus the merger of Design of Experiments with Optimization of
Control parameters to obtain the most appropriate or optimized
results is achieved by the Taguchi Method.
TAGUCHI METHOD

6. REGRESSION ANALYSIS
Regression analysis then chooses among all possible lines by
selecting the one for which the sum of the squares of the estimated
errors is at a minimum.
Regression analysis is a statistical process for estimating the
relationships among variables. It includes many techniques for
modeling and analyzing several variables, when the focus is on the
relationship between a dependent variable and one or more
independent variable.
Y = β0 + β1X1 + β2X2 + βnXn + ε

7. PARAMETERS INVOVLED
TIG WELDING
CURRENT
ELECTRODE DIA
GAS FLOW RATE
WELD STRENGTH
INPUT OUTPUT

8. ORTHOGONALARRAY
• To investigate how different parameters
affect the mean and variance of a
process performance characteristic.
• These designs can be used to estimate
main effects using only a few
experimental runs.
• For doing Experiment on TIG welding,
we are using (L9) Orthogonal matrix
method.
RUN COLUMNS
I II III IV
1 1 1 1 1
2 1 2 2 2
3 1 3 3 3
4 2 1 2 3
5 2 2 3 1
6 2 3 1 2
7 3 1 3 2
8 3 2 1 3
9 3 3 2 1

9. PARAMETERS
(NOTATION)
VALUES
UNITS LEVEL 1 LEVEL 2 LEVEL 3
CURRENT
(I)
A 90 120 150
ELECTRODE
DIAMETER
(ED)
mm 1.60 2.10 2.40
FLOW RATE
(F)
kg/cm² 5 6 7
ORTHOGONAL ARRAY
NOMENCLATURE

10. RUN I ED F
1 1 1 1
2 1 2 2
3 1 3 3
4 2 1 2
5 2 2 3
6 2 3 1
7 3 1 3
8 3 2 1
9 3 3 2
ORTHOGONAL INPUT ARRAY

11. EXPERIMENTAL WORK

12. EXPERIMENT RESULT
CURRENT(A) ELECTRODE
DIA (B)
FLOW RATE
(C)
UTS S/N RATIO
90 1.6 5 397.95 51.996
90 2.1 6 324.24 50.217
90 2.4 7 422.00 52.506
120 1.6 6 512.39 54.192
120 2.1 7 579.90 55.267
120 2.4 5 638.64 56.105
150 1.6 7 320.46 50.115
150 2.1 5 523.97 54.386
150 2.4 6 534.60 54.561

13. DESIGN OF EXPERIMENT
• Design of experiments is a series of tests in which purposeful
changes are made to the input variables of a system or process
and the effects on response variables are measured.
• Design of experiments is applicable to both physical processes
and computer simulation models
• Experimental design is an effective tool for maximizing the
amount of information gained from a study while minimizing
the amount of data to be collected.
• Factorial experimental designs investigate the effects of many
different factors by varying them simultaneously instead of
changing only one factor at a time.

14. WELDED WORKPIECE
Two work pieces of (100x50x3mm) are welded
together to get the final work piece.
DIMENSIONS : 200x50x3 mm

15. TEST SPECIMEN
RECTANGULAR STRIP TYPE
DIMENSIONS : 200x28x3 mm

16. TEST SPECIMENS

17. S1 S2 S3
SPECIMEN AFTER TESTING
All the specimens failed at the weldment.

18. CRACK DEFORMATION MODES
Mode-I corresponds to fracture where the crack surfaces are displaced
normal to themselves. This is a typical tensile type of fracture.

19. SOLUTION BY MINITAB

20. DETERMINE OF RESPONSE TABLE

21. CALCULATION OF RANK
CURRENT(A) ELECTRODE
DIAMETER (B)
FLOW RATE(C) S/N RATIO
1 1 1 51.996
1 2 2 50.217
1 3 3 52.506
2 1 2 54.192
2 2 3 55.267
2 3 1 56.105
3 1 3 50.115
3 2 1 54.386
3 3 2 54.561

22. RESPONSE TABLE S/N RATIO OF UTS
LEVEL CURRENT(A) ELECTRODE
DIAMETER (B)
FLOW
RATE(C)
1 51.57 52.10 54.16
2 55.19 53.29 52.51
3 53.02 54.39 52.63
DELTA=
MAX-MIN
3.61 2.29 1.65
RANK 1 2 3

23. MAIN EFFECT PLOTS FOR ULTIMATE
TENSILE STRENGTH

24. ONE WAY ANOVA:
S/N RATIO VS CURRENT
SOURCE ADJ SS DOF ADJ M.S F P
CURRENT 14.76 2 7.379 1.97 0.220
ERROR 22.51 6 3.752
TOTAL 37.26 8

25. ANOVA GRAPH FOR CURRENT

26. ANOVA GRAPH FOR CURRENT

27. ONE WAY ANOVA:
S/N RATIO VS ELECTRODE
SOURCE ADJ
SS
DOF ADJ
M.S
F P
ELECTRODE
DIAMETER
7.867 2 3.934 0.80 0.491
ERROR 29.4011 6 4.9002
TOTAL 37.267 8

28. ANOVA GRAPH FOR
ELECTRODE DIAMETER

29. ANOVA GRAPH FOR
ELECTRODE DIAMETER

30. ONE WAY ANOVA:
S/N RATIO VS GAS FLOW RATE
SOURCE ADJ SS DOF ADJ M.S F P
FLOW
RATE
1.824 2 0.9116 0.15 0.86
ERROR 35.443 6 5.9075
TOTAL 37.2677 8

31. ANOVA GRAPH FOR GAS FLOW RATE

32. ANOVA GRAPH FOR GAS FLOW RATE

33. ANALYSIS OF VARIANCE FOR
S/N RATIO
All the three one-way ANOVA is calculated for S/N ratio and
finally merged together to form a single ANALYSIS OF
VARIANCE for S/N ratio.
Since the total of all the one-way ANOVA for current, electrode
diameter and flow rate is same therefore it is taken as constant for
the resultant in the ANOVA for S/N ratio which is marked with
line in.
After applying the value of constant total value in the main
ANOVA table, the error and finally F and P values of ANOVA
table can be calculated according to those values, the calculated
value is shown in table.

34. ANOVA FOR S/N RATIO
COMBINATION OF ALL
SOURCE SEQ SS DOF M.S F P
CURRENT 14.756 2 7.3754 1.15 0.468* Significant
ELECTRODE
DIAMETER
7.866 2 3.933 0.61 0.620
FLOW RATE 1.8234 2 0.9117 0.14 0.875
ERROR 12.820 2 6.4100
TOTAL 37.264 8

35. NORMAL PROBABILITY PLOT OF
RESIDUAL FOR UTS (Mpa)

36. PLOT OF RESIDUAL vs FITTED UTS
VALUES

37. MATHEMATICAL MODEL
Using multiple linear regression and correlation
analysis, mathematical models for Ra is obtained as
follows
Ra = a0 + a1*x1 + a2*x2 + a3*x3
Where a0, a1, a2, a3 are constant coefficient
X1 = Current
X2 = Electrode diameter
X3 = Flow rate

38. RESULT
• Main effects plots revel that current and electrode diameter are the
factors which has considerable influence on ultimate tensile strength.
Flow rate has small / lesser influence.
• The optimum welding condition obtained by Taguchi method are:
CURRENT = 120 A
ELECTRODE DIAMETER = 2.4 mm
FLOW RATE = 5 kg/cm2

39. RESULT
The Regression Equation is :
ULTIMATE TENSILE STRENGTH =
(1.882667 x Current) + (149.7731 x Electrode
diameter) – (22.36 x Flow rate) + 176.385
The maximum strength in our case by using this
equation is 649.96 MPa.

40. CONCLUSION
•From the ANOVA results, it is found that none the welding
parameter current has effecting the ultimate tensile stress.
•Main effects plots revel that current and electrode diameter are the
factors which has considerable influence on ultimate tensile strength.
Flow rate has small / lesser influence.
•Confirmation test is confirms the improvement of the UL which
also indicates the validity of the present optimization procedure by
using Taguchi methodology.

41. CONCLUSION
 The strip specimens have simpler geometry and are easier to fabricate,
they are not a good choice for tensile testing because of large stress
concentration factors (as high as 1.84, for the materials properties used
in the analysis).
 The dumbbell specimens with sharp junctions should also be avoided
because of the relatively high stress concentration factors (1.16–1.74,
for the materials properties used in the analysis).
 The dumbbell specimens with rounded junctions are the preferred
specimen shape. The ratio of the radius of fillet to the gage width
should be maximized, so as to minimize stress concentration factors.

42. WELDING FIXTURE
SIMPLE FIXTURE MADE
AFTER ANAZLYZING THE
PROBLEMS FACED.

43. REFERENCES
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CHAPTER 3 “ANALYZING & OPTIMIZING TIG WELDING PROCESS PARAMETERS”
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6. Google , Wikipedia
7. www.minitab.com