International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 INTERNATIONAL JOURNAL OF MECHANICAL ENGINEERING

Transcription

1 INTERNATIONAL JOURNAL OF MECHANICAL ENGINEERING AND TECHNOLOGY (IJMET) ISSN (Print) ISSN (Online) Volume 4, Issue 5, September - October (2013), pp IAEME: Journal Impact Factor (2013): (Calculated by GISI) IJMET I A E M E BRANCH HEIGHT OPTIMIZATION OF COPPER TUBE HYDROFORMING USING SIMULATION THROUGH TAGUCHI TECHNIQUE PARTHASARATHY GARRE Department of Mechanical Engineering, MLR Institute of Technology, Affiliated to JNTUH, Hyderabad, India ABSTRACT Tubehydroforming is a process in which a hollow work piece is expanded into a useful form in a die under high internal hydraulic pressure until the work piece balloons out to reach a desired final shape. Though the process is used for manufacturing complex parts, predictions of wall thickness and branch height development of tube are quite limited. Also, it is quite expensive to experimentally validate a process and thus finite element simulation alone can provide a valuable insight. In this work, + shaped component was taken up for tubehydroforming with boundary conditions available from the literature and the process was simulated using HYPERFORM and LSDYNA. After conducting simulation for the process, Taguchi technique was selected to determine the optimum branch height of the copper tubehydroforming. KEYWORDS: ANOVA, FEA, HYPERFORM, LSDYNA, L9, THF. 1. INTRODUCTION 1.1 Tubehydroforming In tube hydroforming (THF), a tubular blank is placed between two dies, sealed and filled by injecting pressurized water up to 1200MPa into it, deforming its walls and calibrating them to shape the die cavities [1]. The process sequence from 1 to 6 for a typical tubehydroforming operation follows as shown in Fig.1. The typical process cycle includes placing the blank onto the lower tool, closing the die, and applying fluid pressure into tubular section. The pressure is sufficient to cause the blank to deform plastically and take the shape of the tool cavity. 250

2 Fig.1.1: The process sequence for a typical hydroforming operation 1.2. Failure Modes of Tubehydroforming It is required that the tubular blank should be formed into a die cavity of desired shape without any kind of defects such as bursting, wrinkling or buckling. Since bursting is a consequence of necking, which is a condition of local instability under excessive tensile stresses, prediction of necking initiation is an important issue before designing the details of processes [2]. The potential of the expansion process for forming work pieces is limited by the failure modes of Buckling, Wrinkling and Bursting as shown in Fig.1.2. The tube hydroforming processes has two loading variables, i.e. the internal pressure and the axial feeding distance [3]. Fig.1.2: Common failure modes in THF process are wrinkling, buckling, and bursting 251

3 A successful tubular hydroforming depends on a reasonable combination of the internal pressure and the axial compression force at the tube ends. Thus, the information on the tubular hydroforming limit, the final wall thickness distribution and the final contact quality between the deformed tube and the tools is necessary for a designer [4]. Determining the range of values for each of the above parameters and getting a right combination of them is taken up as the problem for this work. Finite element analysis in conjunction with experimental validation can provide a better understanding of the process. It should be noted, however, that it is quite expensive to experimentally validate a process where the geometry is complex in nature, and thus finite element simulation alone can provide a valuable insight and understanding of the process and help in new prototype or product design and development [5]. Thus the process is to be simulated using Altair s HYPERFORM and LSDYNA. Taguchi method is used to determine the process parameters with optimal branch height [6] without any defect. In the process of THF, which is usually characterized by the reduction in wall thickness and increase in internal volume and surface area of the tube, the internal pressure will drop quickly if no extra fluid flows into the tube timely with the augment of the tube volume, and then the overall process has to be suspended in the case of free bulge forming (FBF) operation when it drops to a minimal pressure level required for the plastic forming, or when severe buckling or wrinkling takes place in the case of bulge forming with axial loading (BFAL) operation. In fact, metal tube is strain-hardened in cold THF process, in which a climbing pressure is required to continue the plastic forming. Therefore, the timely supply of pressurized fluid into the deforming tube and proper control of the internal pressure are critical to carry the process to the end [7]. The material properties, that are generally required to assess the component stiffness and strength characteristics under various loading conditions, as such copper is considered as material in tubehydroforming Finite Element Analysis FEA simulations provide insights on the necessary process parameters/ loading paths (i.e. internal pressure and axial feed), part geometry, and part formability by analyzing the thinning, thickening, and strain distribution in the deformed tube. Tubehydroforming process can be simulated using Hyperform with incremental analysis and LS-DYNA software Taguchi Technique In the present work, the Taguchi Technique has been applied to Tubehydroforming process. The application steps are selecting projects, planning the experiment, designing the experiment, conducting the trail run of experiment, analyzing the results (ANOVA) and confirmation test. An orthogonal array is a matrix of numbers arranged in columns and rows. The array is called orthogonal because the levels of various factors are balanced and can be separated from the effects of the other factors within the experiment. In this case L9 standard orthogonal array is considered. 2. RESULTS AND DISCUSSION The first objective of Taguchi methods is to reduce the variability in quality. In order to find out variability, standard L9 array was chosen and formulated and then simulation results were included in it and then conducting ANOVA to determine the contribution of each variable for the optimized process parameters. The formulated orthogonal array TABLE 2.1 is shown below. Column I represents the internal pressure, column II represents axial pressure and column III represents thickness of the blank. The number below the roman letters represents the levels of each factor. 252

4 Table 2.1: Formulated L9 array table for all factors Experiment columns I II III Results of Simulation The simulation results from the above L9 array table for values internal pressure, axial feed and thickness as (190, 8, 0.8) to get branch height as is shown in Fig.2.1. Fig.2.1: Deformed blank and FLD at ip=190; af=8; t=0.8 The simulation results for values internal pressure, axial feed and thickness as (190, 10, 1) to get branch height as is shown in Fig.2.2. Fig.2.2: Deformed blank and FLD at ip=190; af=10; t=1 Similarly the simulation results for values for the rest of the internal pressure, axial feed and thickness as in the L9 array TABLE 2.2 shown below Formulated Array with Response Factor The formulated L9 array with all factors and response factor that is branch heights are shown in the following table. The response factors are from simulation results as said above. 253

5 Table 2.2: Formulated L9 array of all factors and response factor Experiments Factor I Factor II Factor III Response Factor(Y) ANOVA Generating the response table as per the standard format of L9 array for various factors and levels are as shown in TABLE 2.3. Table 2.3: Calculated response table Levels Factor I Factor II Factor III Preparing the ANOVA table as per standard L9 array and included in the following TABLE 2.4 as shown below. Table 2.4: Final results in ANOVA table SOURCE DOF SS MSS F ratio Internal pressure Axial feed Thickness Error RESPONSE GRAPHS The response graphs are drawn as shown in GRAPHS 2.1, 2.2 and 2.3 with the appropriate confidence intervals for the factors and levels. This gives a graphical representation of the differences between the factor levels. 254

6 Response factor I graph Branch height Series Series Internal pressue Graph 2.1: Graph between branch height Vs internal pressure Response factor II graph Branch height Series Series Axial feed Graph 2.2: Graph between branch height Vs axial feed Response factor III graph Branch height Series Series Thickness Graph 2.3: Graph between branch height Vs thickness 3. CONCLUSION The inference from the results obtained from the application of Taguchi technique to the THF process is discussed here. The predicted mean value (190, 12, 1.5) of the branch height is and the confirmation experiment value (190, 12, 1.5) of the branch height is as shown in the Fig.3.1. Fig 3.1: Deformed blank and FLD at ip=190; af=12; t=1.5 Here the range overlaps and then the experiment can be regarded as reproducible. Hence by using Taguchi technique we can determine the optimized process parameters. 255

7 REFERENCES [1]. J.P. Abrantes, A. Szabo-Ponce, and G.F. Batalh, Experimental and numerical simulation of tube hydroforming (THF), Journal of Materials Processing Technology, , 2005, [2]. Jeong Kim, Sang-Woo Kim, Woo-Jin Song, and Beom-Soo Kang, Analytical and numerical approach to prediction of forming limit in tube hydroforming, International Journal of Mechanical Sciences, 47, 2005, [3]. L. Gao, and M. Strano, FEM analysis of tube pre-bending and hydroforming, Journal of Materials Processing Technology, 151, 2004, [4]. H.L. Xing, A. Makinouchi, Numerical analysis and design for tubular hydroforming, International Journal of Mechanical Sciences, 43, 2001, [5]. P. Ray and B.J. Mac Donald, Experimental study and finite element analysis of simple X- and T-branch tube hydroforming processes, International Journal of Mechanical Sciences, 47, 2005, [6]. Avinash S. Sangwikar1 & S. B. Chandgude, Process Parameter Optimization during Blanking of Low Carbon Steel using Taguchi Method, International Conference on Advanced Research in Mechanical Engineering, 2012, ISBN : [7]. Yang Lianfa, Guo Chenga, A simple experimental tooling with internal pressure source used for evaluation of material formability in tube hydroforming, Journal of Materials Processing Technology, 180, 2006, [8]. Dr.R.Uday Kumar and Dr.P.Ravinder Reddy, Influence of Viscosity on Fluid Pressure in Hydroforming Deep Drawing Process, International Journal of Mechanical Engineering & Technology (IJMET), Volume 3, Issue 2, 2012, pp , ISSN Print: , ISSN Online: [9]. Dr.R.Uday Kumar, Mathematical Modeling and Analysis of Hoop Stresses in Hydroforming Deep Drawing Process, International Journal of Advanced Research in Engineering & Technology (IJARET), Volume 3, Issue 2, 2012, pp , ISSN Print: , ISSN Online: [10]. Dr.R.Uday Kumar, Mathematical Modeling and Evaluation of Radial Stresses in Hydroforming Deep Drawing Process, International Journal of Mechanical Engineering & Technology (IJMET), Volume 3, Issue 2, 2012, pp , ISSN Print: , ISSN Online: