Optimization of tig welding using taguchi and regression analysis
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Transcript of Optimization of tig welding using taguchi and regression analysis
Mahatma Gandhi Mission's College Of Engineering and Technology
Noida, 2013012014-2015
Project PresentationOPTIMIZATION OF PROCESS PARAMETERS IN TIG
WELDING USING TAGUCHI METHOD AND REGRESSION ANALYSIS
Project Guide: Presented byMr. Abhijit A. Kulkarni Sukhendu Singh (1109540036) Varun Grover (1109540038) Vivek Bisht (1109540043)
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.
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.
NEED FOR OPTIMIZATIONENSURING
QUALITY
OF PRODUC
TREDUCING MANUFACTURING
COST
INCREASING PRODUCTIVITY
INCREASING TENSILE STRENGTH
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
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
PARAMETERS INVOVLED
TIG WELDING
CURRENT
ELECTRODE DIA
GAS FLOW RATE
WELD STRENGTH
INPUT OUTPUT
ORTHOGONAL ARRAY• 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
PARAMETERS(NOTATION)
VALUES
UNITS LEVEL 1 LEVEL 2 LEVEL 3
CURRENT (I)
A 90 120 150
ELECTRODEDIAMETER
(ED)
mm 1.60 2.10 2.40
FLOW RATE (F)
kg/cm² 5 6 7
ORTHOGONAL ARRAY NOMENCLATURE
RUN I ED F1 1 1 12 1 2 23 1 3 34 2 1 25 2 2 36 2 3 17 3 1 38 3 2 19 3 3 2
ORTHOGONAL INPUT ARRAY
EXPERIMENTAL WORK
EXPERIMENT RESULTCURRENT(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
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.
WELDED WORKPIECE
Two work pieces of (100x50x3mm) are welded together to get the final work piece.
DIMENSIONS : 200x50x3 mm
TEST SPECIMENRECTANGULAR STRIP TYPE
DIMENSIONS : 200x28x3 mm
TEST SPECIMENS
S1 S2 S3
SPECIMEN AFTER TESTING
All the specimens failed at the weldment.
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.
SOLUTION BY MINITAB
DETERMINE OF RESPONSE TABLE
CALCULATION OF RANKCURRENT(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
RESPONSE TABLE S/N RATIO OF UTS
LEVEL CURRENT(A) ELECTRODEDIAMETER (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
MAIN EFFECT PLOTS FOR ULTIMATE TENSILE STRENGTH
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
ANOVA GRAPH FOR CURRENT
ANOVA GRAPH FOR CURRENT
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
ANOVA GRAPH FOR ELECTRODE DIAMETER
ANOVA GRAPH FOR ELECTRODE DIAMETER
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
ANOVA GRAPH FOR GAS FLOW RATE
ANOVA GRAPH FOR GAS FLOW RATE
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.
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
NORMAL PROBABILITY PLOT OF RESIDUAL FOR UTS (Mpa)
PLOT OF RESIDUAL vs FITTED UTS VALUES
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 = CurrentX2 = Electrode diameterX3 = Flow rate
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
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.
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.
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.
WELDING FIXTURE
SIMPLE FIXTURE MADE AFTER ANAZLYZING THE PROBLEMS FACED.
REFERENCES1. Parthiv T. Trivedi, Ashwin P. Bhabhor “A Review on Effect of Process Parameters on Weld Bead for
GTAW” International Journal of Engineering and Management Research (IJEMR) Volume-4, Issue-1, February-2014, ISSN: 2250-0758, pp. 22-26
2. Mallikarjun Kallimath , G Rajendra , S. Sathish “TIG Welding Al6061 using Taguchi and Regression Analysis Methods” International Journal of Engineering Research(IJER) Volume-3 Issue No: Special 1 March 2014, ISSN:2319-6890)(online), 2347-5013(print) , pp. 151-154
3. Ajit Khatter, Pawan Kumar, Manish Kumar “Optimization of Process Parameter in TIG Welding Using Taguchi of Stainless Steel-304” International Journal of Research in Mechanical Engineering and Technology (IJRMET) Volume-4, Issue-1, November-2013-April 2014, ISSN: 2249-5762(Online), ISSN : 2249-5770 (Print) pp. 31-36
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6. Google , Wikipedia
7. www.minitab.com