Effect of Titanium powder addition on hardness in submerged arc welding

Transcription

1 International Journal of Latest Research in Engineering and Technology (IJLRET) ISSN: ǁ Volume Issue ǁ January 0 ǁ PP 8-4 Effect of Titanium powder addition on hardness in submerged arc welding Atul Kathuria Student M.tech (mechanical(i&p) Galaxy Global Group of Instituions(Ambala) Deepak Gupta Assistant Professor(Mechanical Dept.) Galaxy Global Group of Institutions(Ambala) Abstract This paper reports on an optimization of SAW process by the effects of Titanium powder on hardness by applying Taguchi methods to improve the quality of Submerged arc welding, and engineering development of designs for studying variation. IS 0 steel is used as the work piece material for carrying out the experimentation to optimize the optimal parameter for higher hardness. There are three machining parameters i.e. current, electrode stick out and flux. Taguchi orthogonal array is designed with three levels of parameters with the help of software Minitab 5. In the first run nine experiments are performed and hardness is calculated. The hardness was considered as the quality characteristic with the concept of "the larger-the-better". The S/N ratio for the larger-the-better Where n is the number of measurements in a trial/row, in this case, n= and y is the measured value in a run/row. The S/N ratio values are calculated by taking into consideration with the help of software Minitab 5. The hardness values measured from the experiments and their optimum value for maximum hardness Every day scientists are developing new materials and for each new material, we need economical and efficient welding. It is also predicted that Taguchi method is a good method for optimization of various machining parameters as it reduces the number of experiments. The optimal value of Hardness is maximum on the parameter when current is 50 ampere, electrode 5 mm and flux is used. After all study it was found titanium powder is helpful to increase hardness of weld in submerged arc welding. Index Terms SAW welding, optimization, orthogonal array, ANOVA, S/N ratio. I. INTRODUCTION In submerged arc welding, the end of a continuous bare wire electrode is inserted into a mound of flux that covers the area or joint to be welded. An arc is initiated using one of six arc- starting methods, described later in this chapter. A wire-feeding mechanism then begins to feed the electrode wire towards the joint at a controlled rate, and the feeder is moved manually or automatically along the weld seam. For machine or automatic welding, the work may be moved beneath a stationary wire feeder. Additional flux is continually fed in front of and around the electrode, and continuously distributed over the joint. Heat evolved by the electric arc progressively melts some of the flux, the end of the wire, and the adjacent edges of the base metal, creating a pool of molten metal beneath a layer of liquid slag. The melted bath near the arc is in a highly turbulent state. Gas bubbles are quickly swept to the surface of the pool. The flux floats on the molten metal and completely shields the welding zone from the atmosphere. The liquid flux may conduct some electric current between the wire and base metal, but an electric arc is the predominant heat source. The flux blanket on the top surface of the weld pool prevents atmospheric gases from contaminating the weld metal, and dissolves impurities in the base metal and electrode and floats them to the surface. The flux can also add or remove certain alloying elements to or from the weld metal. As the welding zone progresses along the seam, the weld metal and then the liquid flux cool and solidify, forming a weld bead and a protective slag shield over it. It is important that the slag is completely removed before making another weld pass. [] II. LITRETURE SURVEY A.M. Mercado, V.M. Hirata and M. L. Munoz () were investigation on Influence of the chemical composition of flux on the microstructure and tensile properties of submerged-arc welds. V.B. Trindade, R.S.T. Mello, J.C. Payão and R.P.R. Paranhos () said about the Influence of Zirconium on Microstructure and Toughness of Low-Alloy Steel Weld Metals. P. Kanjilal, T.K. Pal and S.K. Majumdar (4) were researched on combined effect of flux and welding parameters on chemical composition and mechanical properties of submerged arc weld metal. S. Kumanan, J.E.R. Dhas and K. Gowthaman (5) were explaining Determination of submerged arc welding process parameters using Taguchi method and Regression analysis. S. Datta, A. Bandyopadhyay and P.K. Pal () were discussed about Application of Taguchi philosophy for parametric optimization of bead geometry and 8 Page

2 HAZ width in SAW using a mixture of fresh flux and fused flux. A. Singh, S. Datta, S.S. Mahapatra, T. Singha and G. Majumdar (7) were said that Optimization of bead geometry of submerged arc weld using fuzzy based desirability function approach. The experimental studies were conducted under varying current, electrode and flux. III. TAGUCHI S DESIGN METHODE Taguchi methods are statistical methods developed by Genichi Taguchi to improve the quality of manufactured goods, and more recently also applied to engineering, advertising, Professional statisticians have welcomed the goals and improvements brought about by Taguchi methods, particularly by Taguchi's development of designs for studying variation, but have criticized the inefficiency of some of Taguchi's proposals. "Orthogonal Arrays" (OA) provide 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 for optimization, help in data analysis and prediction of optimum results. A. Signal to Noise Ratio There are Signal-to-Noise r a t i o s of common interest for optimization (I) Smaller-The-Better: n = -0 Log 0 [mean of sum of squares of measured data] (Ii) Larger-The-Better: n = -0 Log0 [mean of sum squares of reciprocal of measured data] (Iii) Nominal-The-Best: Square of mean n = 0 Log 0 Variance B. Work Material The work material used for present work is Mild Steel IS 0, the dimensions of the work piece length 50mm, width of 5mm, thickness 0mm. Table : % age composition of base metal Mn C Si P S C EH-4 type of electrode wire is used in this experiment. The diameter of the electrode wire is.mm is constant. D. Flux Table : % age composition of electrode C Mn Si P S Firstly, AUTOMELT B type of flux is used in this experiment. Basicity index of AUTOMELT B is.5 with grain size of mm and is being considered neutral flux, according to the basicity index. Table : % age composition of flux SiO+TiO CaO+MgO AlO+MnO CaF E. Welding parameters and their levels For selection of parameters and their level is based on pilot study. Page

3 Table 4: Welding Parameters and Their Levels Parameters Level Level Level (Amp.) (mm) 5 8 flux Where st flux is (AUTOMELT B), nd flux is (0 % titanium powder addition in AUTOMELT B) and rd flux is (0 % titanium powder addition in AUTOMELT B). FL Level Taguchi Orthogonal Array Taguchi s orthogonal design uses a special set of predefined arrays called orthogonal arrays (OAs) to design the plan of experiment. These standard arrays stipulate the way of full information of all the factors that affects the process performance (process responses). The corresponding OA is selected from the set of predefined OAs according to the number of factors and their levels that will be used in the experiment. Table No.5 shows L Orthogonal array Experimen t no. Table 5: L orthogonal array (Ampere) Process Parameter (mm) flux L L L L L L L L L 4 L L L 5 L L L L L L 7 L L L 8 L L L L L L 0 Page

4 IV. ANALYSIS OF HARDNESS RESULTS The testing would be carried on computerized Vickers Hardness test machine. Table shows the result of hardness. Tria l No. (A) Stick out (mm) Table Results for Hardness Fux on base Metal on Welding on HAZ Mean S/N ratio V. ANOVA FOR S/N RATIOS OF HARDNESS The purpose of the analysis of variance (ANOVA) is to investigate which design parameters significantly affect the quality characteristic. This is to accomplished by separating the total variability of the S/N ratios, which is measured by the sum of the squared deviations from the total mean S/N ratio, into contributions by each of the design parameters and the error. The result of ANOVA is shown in given table. Source Table 7: Result of analysis of variance for Hardness D. O.F Flux Seq SS SS MS F P % age cont ribu tion Page

5 Mean of SN ratios Residual.07 error 4 4 Total The response table for signal to noise ratio are shown in Table 8 Table 8 Response table for signal to noise ratio Level Flux Delta Rank In our experimental analysis, the ranks indicate that flux has the greatest influence on the S/N ratio. For S/N ratio, current has the next greatest influence and the electrode has the least influence. The optimum combination of parameters for hardness value is shown in Table. Table Optimum combination of parameters Level 50 Ampere Level 5 mm Flux Level Main effect plot of signal to noise ratio for hardness test is shown in Fig. Main Effects Plot for SN ratios Data Means Flux Signal-to-noise: Larger is better Fig. Main effect plot of signal to noise ratio for hardness Page

6 VI. ANOVA FOR MEAN OF HARDNESS The analysis of variance for mean is shown in Table 0 Source D.O.F. Seq SS. Table 0 Analysis of variance for mean SS. MS.4 F Flux.77.7 Residual. 0.7 P %Age contribution error Total The response for mean is shown in Table. The response table shows the average of each response characteristic for each level of each factor. Table Response table for mean Level stick out Flux Delta Rank The optimum combinations of parameters is shown in Table Table Optimum combinations of parameters Level 50 Ampere Stick out Level 5 mm Flux Level Page

7 Main effect plot of mean for hardness test is shown in Fig.5 Fig. Main effect plot of mean for hardness VII. CONCLUSION Flux has significant effect on the hardness with contribution of.8 % and whereas current and electrode travel speed has insignificantly effected with contribution of 5. % and 7.87 %. Hardness of mild steel of grade IS 0 will be the maximum when we using current 50 ampere, electrode 5 mm and flux. ACKNOWLEDGMENT First of all, I would like to express my gratitude to my supervisor Mr. Deepak Gupta, Assistant Professor of Mechanical Engineering Department, Glaxy Gloable group of institutions for his exceptional patience, for all his help and for being there for me through all good and bad times. Thank you for all what you have done for me and for providing me with valuable feedback in my research which made it stronger and more valuable. I am sincerely grateful for his priceless support and contribution toward my research. REFERANCES []. R. S. Parmar, Welding processes and technology, nd Ed, 008. []. A.M. Mercado, V.M. Hirata and M. L. Munoz (005) Influence of the chemical composition of flux on the microstructure and tensile properties of submerged-arc welds, Journal of Materials Processing Technology, Volume, issue, pp []. V.B. Trindade, R.S.T. Mello, J.C. Payão and R.P.R. Paranhos (005) Influence of Zirconium on Microstructure and Toughness of Low-Alloy Steel Weld Metals, International Journal of Advanced Manufacturing Technology, Volume l5, pp [4]. P. Kanjilal, T.K. Pal and S.K. Majumdar (00) Combined effect of flux and welding parameters on chemical composition and mechanical properties of submerged arc weld metal. Journal of Materials Processing Technology, Volume 7, issue, pp.. [5]. S. Kumanan, J.E.R. Dhas and K. Gowthaman (007) Determination of submerged arc welding process parameters using Taguchi method and Regression analysis Indian Journal of Engineering and Material Science, Volume 4, pp []. S. Datta, A. Bandyopadhyay and P.K. Pal (007) Application of Taguchi philosophy for parametric optimization of bead geometry and HAZ width in SAW using a mixture of fresh flux and fused flux, International Journal of Advanced Manufacturing Technology, Volume, pp [7]. A. Singh, S. Datta, S.S. Mahapatra, T. Singha and G. Majumdar (0) Optimization of bead geometry of submerged arc weld using fuzzy based desirability function approach, International Journal of Advanced Manufacturing Technology, Volume 4, pp Page