PREDICTION ON WELD STRENGTH OF ULTRASONIC METAL WELDING OF COPPER WIRE AL8011 SHEET

Transcription

1 Volume 119 No , ISSN: (on-line version) url: ijpam.eu PREDICTION ON WELD STRENGTH OF ULTRASONIC METAL WELDING OF COPPER WIRE AL8011 SHEET S.Raja 1 and Dr.N.Balaji 2 1 Assistant Professor, Department of Mechanical Engineering, Sri Krishna College of Engineering and Technology, Coimbatore. 2 Associate Professor, Department of Mechanical Engineering, Sri Krishna College of Engineering and Technology, Coimbatore. Abstract Ultrasonic welding employing high frequency vibrations is an efficient method of joining two materials with less amount of heat. The sheet metal employed in this analysis is subjected to a mechanical force which acts on the parts to be welded. The surface to be welded are subjected to these forces. In this present work, investigation of the weld strength of Al 8011sheet and copper wire by USW process are carried out. A numerical method of response surface methodology is used to predict the strength based on the input parameter such as amplitude, weld time and weld pressure with the experimental values. Keywords: ultrasonic welding, Copper wire Al 8011(Aluminium alloy) weld strength, response surface methodology (RSM). 1. Introduction Ultrasonic welding is a method of joining two parts by transforming electrical energy into heat energy of relatively low temperature using a high frequency mechanical vibration. High frequency vibrations along with pressure are used to join two materials together quickly and safely without producing enormous heat. Response surface methodology (RSM) is used for modelling the process. It gives the information about the main and interaction effects. The current study deals with the second order Response model for the outcome of weld strength The predicted values are then compared with the experimental results. 2 LITERATURE SURVEY S.Elangovan, et al [1] stated the using of high frequency vibrations in ultrasonic welding without producing large amount of thermal input for joining of two 2217

2 materials together. But in ultrasonic welding, the parts to be welded are acted upon by shear and normal force at the weld interface. These forces press the parts to be welded. FEA model is capable of finding the temperature interface and stress distribution during welding and their strength influences in the work piece. Ganesh M, et al [2] stated that Ultrasonic welding of thin similar or dissimilar sheet metals of non-ferrous alloys without filler material resulting in high quality weld. Dissimilar metals of aluminium and copper sheets have been joined through Ultrasonic welding. Results are particularly promising on thin aluminium and copper through Ultrasonic Metal Spot Welding. Three different parameters such as the weld time and amplitude is important in weld strength. With low amplitude, high weld time and moderate pressure, weld strength is poor and vice versa. S. Elangovan, et al [3] presents the method to increase the strength of joints produced by ultrasonic welding using RSM. RSM is utilized to create an efficient analytical model for welding strength in terms of welding parameters namely pressure, weld time, and amplitude. Experiments were conducted as per central composite design of experiments for spot and seam welding of 0.3- and 0.4-mm-thick Al specimens. An effective second-order response surface model is developed utilizing experimental measurements. Gunaraj, et al [4] describes RSM is a method to find the root cause and effect relationship between responses and input. A four-factor five-level central composite rotatable design matrix with full replication for planning, conduction, execution and development of mathematical models is designed through RSM. Predicting the weld bead quality and obtaining optimum process parameters for achieving the supreme quality. Contour graphs for various responses to show the interaction effects of different process parameters through RSM. Marius Pop-Calimanu, et al [5] showcase the problem of poor weld strength encountered by researchers and industry with ultrasonic welding process, due to poor welding parameters. In this work, parameters, like welding time, welding pressure and amplitude of the vibration are measured during the welding of Al/20%SiC composite material in disks form, with the thickness of 1 mm. It is found that welding pressure and welding time has a significant effect on the joint strength. J. Pradeep Kumar, et al [6] states a Mathematical model to forecast the weld strength of the joint established on the experiments conducted. The ASM standard tensile test was selected to extract quality response. Using Analysis of Variance each factors contribution percentage of are determined. EXPERIMENT PROCEDURE 3.1 Material details In the existing research, Al 8011, is engaged for welding. The additional material used in ultrasonic welding is copper. The chemical configuration for Al 8011 is listed in the table

3 Element Al Fe Si Mn Zn Cu Ti Cr Mg Content (%) Experimental details Table 1: chemical composition of Al The experiment analysis were conceded with an ultra-sonic welding machine covering different weld parameters. The sample include 0.3 mm Al 8011 sheet and 1.2mm diameter copper wire. Welding factors such as Weld force, amplitude and weld period are considered for welding experiments. A maximum of 20 joints with 20 different combinations of different pressure, weld time and amplitude are carried out. Various levels of lower, middle and higher welding parameters for RSM design is shown in Table 2. Parameters are selected based on trial and error method ranges of welding. S.No Factors Designation Level Level 2 Level 3 1 Pressure ((bar) A Time (sec) B Amplitude (µm) C RSM for weld strength Table 2: Experimental parameters and their levels A mathematical model was developed for predicting the values of weld strength using RSM. The mathematical models with second-order have been developed to predict the weld strength. The polynomial equation for the three factors considered in the present case is Where is the response, i.e., weld strength; represents pressure, weld time, and amplitude;,,, and represent the constant, linear, quadratic, and interaction terms, respectively. Input to the Minitab software is the weld strength obtained from experimental results for various combinations of parameters, and mathematical model of second order for predicting weld strength is manipulated. 3.4 Tensile testing Twenty samples are tested in computerized ultimate tensile testing machine for tensile shear strength. Quality of joints is determined by the Strength of weld at 2219

4 the weld interface. The weld strength at the interface is find out by using a testing machine as shown in fig.1. This machine consists of electronic control panel load cells and. gripper for flat specimen (0-10mm thickness) 4 RESULTS AND DISCUSSION Fig 1: Computerized Tensile testing machine 4.1 Experiments and response surface model Totally twenty experiments were conducted at different factor levels to joint 0.3 mm thick Aluminium 8011 sheet with 1.2mm diameter copper wire. The welded piece of the spot welding of the work piece after testing shown in the figure 2. The values of weld strength obtained from trials and those predicted from response surface model along with design matrix for the used 0.3mm-thick Al 8011 and 1.2 mm diameter copper wire specimens are stated in the table. Evaluation of the predicted values of strengths with experimental values, reveals that the nonconformities are less except for a few combinations of parameters. Figure 2 : welded work piece after tensile testing 2220

5 Figures 3 shows the weld strength comparison obtained from experiments and predicted weld strengths for spot welded samples of aluminium 8011 sheet and copper wire. From the graph, it can be perceived that the deviations between weld strengths obtained from experiments and those predicted by RSM is close enough and the eccentricity is less. S. No Weld pressure (bar) period (sec) Amplitude (µm) Avg. Strength (N/mm 2 ) Experimental Predicted Table 3 : Comparison between RSM predicted vs Experimental values Figure 3: comparison of weld strength between Exp and RSM Predicted 2221

6 Mean of WS International Journal of Pure and Applied Mathematics Figure 4 shows that weld strength increases with decreases in pressure for a certain limit thereafter it increases,there is not much significance in time and for amplitude it decreases for certain limit and then it increases. Main Effects Plot for WS Fitted Means 21.5 P T A Figure 4: Effect of parameters on weld strength CONCLUSION The design matrix established using response surface methodology (RSM) offers the optimal combination of weld factors for copper wire to Al 8011 sheet joint. The variance is minimum between weld strengths obtained from trials and those anticipated by RSM was perceived. Enormous amount of energy to vibrate a heavy part at the essential frequency to join with fairly light material. From the results it is decided that RSM Model gives a good agreement with the trial results. References 1. S. Elangovan, S. Semeer, K. Prakasan, Temperature and stress distribution in ultrasonic metal welding An FEA-based study, journal of materials processing technology 209 (2009) Ganesh M, Praba Rajathi R, EXPERIMENTAL STUDY ON ULTRASONIC WELDING OF ALUMINUM SHEET TO COPPER SHEET, International Journal of Research in Engineering and Technology, 02 (2013) S. Elangovan, K. Anand, K. Prakasan, Parametric optimization of ultrasonic metal weldingusing response surface methodology and genetic algorithm, Int J Adv Manuf Technology s

7 4. V. Gunaraj, N. Murugan, Application of RSM for predicting weld bead quality in submerged arc welding of pipes, Journal of Materials Processing Technology 88 (1999) Marius Pop-Calimanu, Traian Fleser, THE INCREASING OF WELD STRENGTH BY PARAMETERS OPTIMIZATION OF ULTRASONIC WELDING FOR COMPOSITE MATERIAL BASED ON ALUMINIUM USING DESIGN OF EXPERIMENTS, nanocon, J.PRADEEP KUMAR, K.PRAKASAN, EXPERIMENTAL STUDIES ON JOINING COPPER WIRE - COPPER SHEET USING ULTRASONIC METAL WELDING, International Journal of Mechanical and Production Engineering Research and Development (IJMPERD ) ISSN Vol.2, Issue 3 Sep

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