MIG WELDING PARAMETRIC OPTIMIZATION USING TAGUCHI S ORTHOGONAL ARRAY AND ANALYSIS OF VARIANCE

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1 MIG WELDING PARAMETRIC OPTIMIZATION USING TAGUCHI S ORTHOGONAL ARRAY AND ANALYSIS OF VARIANCE Amit Pal Mechanical Department, AIMT, Karnal, Haryana, India Er.amit.pal31@gmail Abstract The MIG welding is one of the most popular welding techniques used in industries. This uses a consumable metal electrode. The input parameters in MIG welding play a significant role in deciding the weld quality, strength, cost and speed. Most of times manufacturer faces a problem to select optimum process parameters for a good quality weld. This paper tries to present the effect of different welding parameters like welding voltage, filler wire rate and v-butt angle on the strength of the weld joint and elongation produced during the tensile test. These all parameters have different effect on welding quality. In order to optimize these parameters for better weld quality Taguchi Orthogonal array has been used. The medium carbon steel slabs have been used as welding material. The ANOVA is also employed to predict the percentage effect of each parameter on results. Keywords- MIG welding, Taguchi orthogonal array, and NOVA. 1. INTRODUCTION 1.1 MIG Welding MIG welding is one of the important, easiest & strongest welding techniques used in industries. Metal inert gas welding consists of transferring the material of filler wire in the form of molten liquid to work piece. The heat produced by the short circuit, along with a non-reactive (means inert) gas locally melts the metal and allows them to mix together. Once the heat is removed the metal begins to cool and solidify, and forms a new piece of fused metal. Metal inert gas welding is also called Gas metal arc welding (GMAW).MIG welding is very useful because you can use it to weld many different types of metals like carbon steel, aluminum, stainless steel, nickel etc. 1.2 Literature Review Figure.1: Working with MIG S.V. Sapakal & M.T. Telsang presented a research on the optimization of MIG welding parameters using Taguchi design method. In their research they considered welding current, welding voltage and welding speed as input variables and penetration depth as output variable.ms C20 was selected as work piece material. A plan of experiments based on Taguchi technique has been used to acquire the data. An orthogonal array, signal to noise(s/n) ratio and analysis of variance (ANOVA) were employed to investigate the welding characteristics of MS C20 material and optimize the welding parameters. Their experimentation results that the lower current, medium voltage and lower welding speed leads to better penetration in the welding of MS C20 material. [1] 211 P a g e IJRREST h t t p : / / i j r r e s t. o r g / i s s u e s /? p a g e _ i d = 1 2

2 S.R. Meshram & N.S. Pohokar has done a research on optimization of process parameters of gas metal arc welding to improve the quality of weld bead geometry. In their work, a grey-based Taguchi method was adopted to optimize the gas metal arc welding process parameters. Many quality characteristic parameters were combined into one integrated quality parameter by using grey relational grade or rank. The welding parameters considered in their research were arc voltage, wire feed rate, welding speed, nozzle to plate distance and gas flow. The quality characteristics consider were penetration, reinforcement and bead width. Analysis of variance has performed to find the effect of individual process parameter on quality parameters. The Taguchi L25 array was adopted to conduct the experiments. The stainless steel (AISI410) was used as welding specimen. [2] A.K. Panday, M.I. khan & K.M. Moeed performed their analysis on optimization of resistance spot welding parameters using Taguchi method. The experiments were conducted under varying pressure, welding current and welding time. The output characteristic considered was tensile strength of the welded joint. The material used was low carbon steel sheets of 0.9mm. Their conclusion leads that the contribution of welding current holding time and pressure towards tensile strength is 61%, 28.7% and 4 % respectively as determined by the ANOVA method. [3] Nirmalendu Choudhary, Asish Bandypadhay & Ramesh Rudrapati has presented their work on design optimization of process parameters of TIG welding using Taguchi method. They considered welding current, gas flow rate and filler rod as input process parameters and optimizes their values using Taguchi method to improve the ultimate load on weld materials. Taguchi design of experiment, S/N ratio and ANOVA analysis has performed for optimizing the results. The stainless steel slabs & mild steel slabs were used as work piece material. The optimum welding condition is obtained by the Taguchi method: current= 100A, gas flow rate= 18l/min, filler rod= 2. Confirmation test confirmed the optimum values. [4] S.R Patil & C.A Waghmare presented their work on optimization of MIG welding parameters for improving welding strength. They presents the influence of welding parameters welding current, welding voltage, welding speed on ultimate strength of welded joints of AISI mild steel materials. A plan of experiments using Taguchi has decided. Experiments were performed and result was confirmed. From this study they concluded that the welding current and welding speed are the major factors affecting tensile strength of welded joints. [5] Ajit hooda, Ashwani dhingra & Satpal sharma has done their research on optimization of MIG welding parameters in order to improve yield strength of AISI 1040 mild steel. The process parameters welding current, voltage, gas flow rate and wire speed were studied. The experiments were conducted based on four factors, three level orthogonal arrays. The empirical relationship can be used to predict the yield strength of welded material. [6] In the present work, it is planned to analyse the different input parameters in MIG welding to improve the ultimate tensile strength and reduce the elongation of the welding joint using Taguchi s orthogonal array and Grey relational analysis. 2. TAGUCHI S METHOD The Taguchi method has become an influential tool for improving output during research and development, so that better quality products can be produced quickly and at minimum cost. Dr. Taguchi of Nippon Telephones and Telegraph Company, Japan has established a method based on "ORTHOGONAL ARRAY" experiments which gives much reduced "variance" for the experiment with "optimum settings" of control variables. Thus the marriage of Design of Experiments with optimization of control parameters to find best results is attained in the Taguchi Method. "Orthogonal Arrays" (OA) gives a set of well balanced (minimum) experiments and Dr. Taguchi's Signal-to-Noise ratios (S/N), which are log functions of desired output, serve as objective functions in optimization, help in data analysis and estimation of optimum results. The S/N ration in Taguchi s method is calculated by giving formulas: (i) Smaller the better η = -10 log [( Y 2 i )/ n] (1) (ii) Larger the better η = -10 log [( 1/Y 2 i )/ n] (2) Where, η = Signal to Noise ratio, 212 P a g e IJRREST h t t p : / / i j r r e s t. o r g / i s s u e s /? p a g e _ i d = 1 2

3 Y i = i th observed value of response n = no. Of observations in a trial y = average of observed response Smaller the better approach is followed for the response parameter which we wants to be minimum and larger the better approach is followed for response parameter which we wants maximum. [7,8] 3. EXPERIMENTAL PLAN AND DETAILS 3.1 Experimental Setup & Work Materials The experiments were conducted at Apex institute of management and technology, Gorgarh, Karnal on Medium carbon steel plates of AISI 1040 grade of steel 10mm thickness were cut into 150mm 100mm plates.experiments were carried out using the Ajit Welding Machine (Fine flow-250) under the shied of commercial CO 2 gas. Figure.2: Welding Setup Used Steel electrode wire ER 70S-6(Grade S4-C504) of diameter 1.2mm was used as feeler material. 3.2 Welding Input Parameters Selection To perform the experiments, the levels of welding parameters are selected as in Table1. Symbol Table1: Welding Parameters and their Levels Welding parameters Units Levels A Wire Feed Rate Meter/minute B Arc Voltage Volts C V-butt Angle Degree Taguchi Orthogonal Array Selection For performing the experiments Taguchi L 9 orthogonal array was selected for 3-factor and 3-levels process parameters. Which reduces the number of experiments and is gives as in Table P a g e IJRREST h t t p : / / i j r r e s t. o r g / i s s u e s /? p a g e _ i d = 1 2

4 Table2: Taguchi L 9 Orthogonal Array Experiment Process parameters No. (A) (B) (C) Experimentation and Calculation All nine welding experiments were performed with the help of orthogonal array. For the calculation of the responses (Ultimate tensile strength and percentage elongation) the work pieces were machined into standard shape of tensile specimens. On these specimens tensile test were performed on Universal testing machine for calculation of ultimate tensile strength and percentage elongation at CITCO lab, Chandigarh. The results of ultimate tensile strength and calculation of percentage elongation are shown in Table 3. Figure.3: Welded Test Pieces Figure.4: Tensile Test Piece Prepared Figure 5: Tensile Test Specimens after Failure on UTM Table 3: Design of Experiment and Calculation Exp. No. A B C Ultimate tensile strength (N/mm 2 ) % Elongation ANOVA Table and Response calculation The purpose of analysis of variance (ANOVA) is to investigate which design parameter significantly affects the response parameters. The ANOVA table for both UTS and Percentage elongation are shown in Table 4 and P a g e IJRREST h t t p : / / i j r r e s t. o r g / i s s u e s /? p a g e _ i d = 1 2

5 Table 4: ANOVA Table for UTS Source DOF S.S M.S F P %C A * B ** C *** Error Total Table 5: ANOVA table for percentage elongation Source DOF S.S M.S F P %C A ** B * C *** Error Total The response values of each parameter for UTS & percentage elongation are shown in Table 6 and 7. Table 6: Response Table for UTS Levels A B C Delta Rank Table 7: Response Table for Percentage Elongation Levels A B C Delta Rank The ANOVAs table and response table calculation represents the effect of different parameters on individual responses. Here *** & ** represents most significant and significant parameters and * as less significant for individual response. 4. RESULT AND DISCUSSION 4.1 Optimum parameter selection from S/N ratio for UTS The observed value of Ultimate Tensile strength (UTS) and corresponding values of S/N ratio are listed in Table V and the response values for S/N ratio of UTS are listed in Table VI. The graphical plots for showing S/N ratio with each parameter are presented in figure 5. By analyzing these values, the optimize MIG parameters values 215 P a g e IJRREST h t t p : / / i j r r e s t. o r g / i s s u e s /? p a g e _ i d = 1 2

6 for Maximizing the Ultimate Tensile strength of welding joint comes out are Maximum wire feed, middle arc voltage and maximum v-butt angle( A3B2C3). Figure.6: Main Effect Plots for S/N Ratio for UTS 4.2 Optimum Parameter Selection from S/N Ratio for Percentage Elongation The observed value of Percentage elongation and corresponding values of S/N ratio are listed in table V and the response values of S/N ratio of percentage elongation are listed in table VII. The graphical plots for showing S/N ratio with each parameter are presented in figure 6 by analyzing these values,the optimize MIG parameters values for minimization of Percentage elongation are maximum wire feed, middle arc voltage and maximum v- butt angle(a3b2c3). Figure.7: Main Affects Plots for S/N Ratio for Percentage Elongation 216 P a g e IJRREST h t t p : / / i j r r e s t. o r g / i s s u e s /? p a g e _ i d = 1 2

7 4.3 Analysis of Variance (ANOVAs) Results for UTS The calculated values of Analysis of variance for ultimate tensile strength of welding joint are listed in table 4. The calculated values of ANOVAs present the percentage effect of each parameter on ultimate tensile strength of the joint. From the analysis, it is seen that v-butt angle is the most contribution factor and the wire feed rate is the least contribution factor for UTS of joint. 4.4 Analysis of Variance (ANOVAs) Results for Percentage Elongation The calculated values of Analysis of variance for percentage elongation of welding joint are listed in table5. The calculated values of ANOVAs present the percentage effect of each parameter on percentage elongation of the joint. From the analysis, it is seen that V-butt angle is the most contribution factor and the arc voltage is the least contribution factor for percentage elongation of joint. 5. CONCLUSION In this research work, the Taguchi orthogonal array and ANOVAs method were used for parameter optimization of MIG welding for two responses i.e. Ultimate tensile strength and percentage elongation. This research can be found very useful for obtaining best combination of parameters for both output responses individually; results variation will be small from desired value. 6. REFERENCES [1] S.V Sapakal, M.T. Telsang,(2012), Parametric optimization of MIG welding using Taguchi design method. International Journal Of advanced Engineering Research and Studies, pp [2] S.R. Meshram, N.S. pohokar, (2013), Optimization of process parameters of Gas Metal Arc Welding to improve Quality of Weld bead geometry. International journal of Engineering, Business and Enterprise Applications, pp [3] A.K. Panday, M.I. Khan, K.M. Moeed,(2013), Optimization of resistance welding parameters using Taguchi method. Internatinal Journal of Engineering Science and Technology, pp [4] Nirmalendhu Choudhury, Asish Bandyopadhyay, Ramesh Rudrapati, (2014), Design optimization of process parameters for TIG welding based on Taguchi method. International Journal of Cureent Engineering and Technology, pp [5] S.R. Patil, C.A. Waghmare,(2013), Optimization of MIG welding parameters for improving strength of welded joints. International Journal of Advanced Engineering and Studies, pp [6] Ajit Hooda, Ashwani Dhingra and Satpal Sharma, (2012), Optimization of Welding process parameters to predict maximum yield strength in AISI International Journal of mechanical Engineering and Robotics Research India, pp [7] B.Shivapragash,,K.Chandrasekran,C.Parthasarathy, M.Samuel, (2013), Multiple Response optimization in Drilling using Taguchi and Grey relational analysis. International Journal of Modern Engineering Research, pp [8] Guo.H Fuzzy, (1985), Introduction of coefficient of grey relational grade. Fuzzy Mathematics, special issue on Grey system, pp [9] Kuo.C.F.J,Wu.Y.S, (2006), Optimization of film coating process for polymer blends by the Grey based Taguchi method. International Journal of Advanced manufacturing Technology,pp [10] Lin C.L. and Lin. J.L, (2002), The use of orthogonal array with Grey relational analysis to optimize the EDM process with multiple performance characteristics. J Matar Process tacnol,pp P a g e IJRREST h t t p : / / i j r r e s t. o r g / i s s u e s /? p a g e _ i d = 1 2