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Numerical Evaluation and Influence of Product Quality and its defects Measures on the drawing of Stainless Steel Cross Member for Automobiles


Affiliations
1 Dept. of Mech. Engg., SRM Institute of Sci. and Tech., Tamil Nadu, India
2 Dept. of Mechatronics Engg., ISHIK University, ERBIL, KRG, Iraq
3 Dept. of Mechatronics Engg., SRM Institute of Sci. and Tech., Tamil Nadu, India
 

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Industrial enterprises increasingly demand optimum quality of products keeping in consideration a strict adherence where forming parameters are concerned. As far as incorporating the vital forming process upon an assortment of materials is concerned, it has grown excruciatingly challenging for industrial enterprises for laying out the adequately precise and suitable parameters. The flaws that are engendered during the process of sheet metal forming are inevitable. Flaws of this nature can be, however, kept within minimal proportions by introducing variations into the process parameters by Trial and Error methodology. This evidently results in a subsequent financial loss, not to mention an irrevocable loss of time and material. Dynaform simulation of defects combined with optimization is carried out with the help of Minitab. This method, as can be conjectured with considerable ease, yields optimum results, for it replaces much to our convenience the need for specialist industrial expertise besides leading to considerable savings in cost, time and material. This study would optimize the SS304sheet metal forming parameters FLD, thickness and thinning with three input parameters, namely, the lower binder force, tool travel velocity and binder close velocity.

Keywords

Sheet Metal Forming, Binder Close Velocity, Taguchi Orthogonal Array, Defect Measurements.
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  • G. Taguchi and S. Konishi. 1987. Taguchi method, orthogonal arrays and linear graphs, Tools for Quality Engg., American Supplier Institute, 35-38.
  • X. Duan and T. Sheppard. 2002. Influence of forming parameters on the final sub grain size during hot rolling of aluminium alloys, J. Mater. Process. Tech., 130-131, 245-249. https://doi.org/10.1016/S0924-0136(02)008117.
  • S.P.S.S. Sivam, S.M. Karuppaiah, B.K. Yedida, J.R. Atluri and S. Mathur. 2017. Multi response optimization of setting input variables for getting better product quality in machining of magnesium AM60 by grey relation analysis and ANOVA, Periodica Polytechnica Mech. Engg., 62(2), 118-125. https://doi.org/10.3311/PPme.11034.
  • S.W. Lee. 2002. Study on the forming parameters of the metal bellows, J. Mater. Process. Tech., 130-131, 47-53. https://doi.org/10.1016/S0924-0136(02)00787-2.
  • D.C. Ko, D.H. Kim, B.M. Kim and J.C. Choi. 1998. Methodology of perform design considering workability in metal forming by the artificial neural network and Taguchi method, J. Mater. Process. Tech., 80-81, 487-492. https://doi.org/10.1016/S0924-0136(98)00152-6.
  • D.C. Koa, D.H. Kim and B.M. Kim. 1999. Application of artificial neural network and Taguchi method to perform design in metal forming considering workability, Int. J. Mach. Tools Manuf., 39, 771-785. https://doi.org/10.1016/S0890-6955(98)00055-8.
  • K. Park, Y. Kim. 1995. The effect of material and process variables on the tamping formability of sheet materials, J. Mater. Process. Tech., 51, 64-78. https://doi.org/10.1016/0924-0136(94)01578-O.
  • S.P.S.S. Sivam, V.G. Umasekar, A. Mishra, S. Mishra, and A. Mondal. 2016. Orbital cold forming technologycombining high quality forming with cost effectiveness:A review, Indian J. Sci. and Tech., 9(38), 1-7. http://dx.doi.org/10.17485/ijst/2016/v9i38/91426.
  • S.P.S.S. Sivam, V.G. Umasekar, K. Saravanan, S. Rajendrakumar, P. Karthikeyan and K.S. Moorthy. 2016. Frequently used anisotropic yield criteria for sheet metal applications: A review, Indian J. Sci. and Tech., 9(47), 1-6.
  • R.S. Chen, H.H. Lee, C.Y. Yu. 1997. Application of Taguchi’s method on the optimal process design of an injection moulded PC/PBT automobile bumper, Compos. Struct., 39(3-4), 209-214. https://doi.org/10.1016/S0263-8223(97)00110-4.
  • M. Colgan and J. Monaghan. 2003. Deep drawing process: Analysis and experiment, J. Mater. Process. Tech., 132, 35-41. https://doi.org/10.1016/S0924-0136(02)00253-4.
  • E.J. Obermeyer and S.A. Majlessi. 1998. A review of recent advances in the application of blank-holder force towards improving the forming limits of sheet metal parts, J. Mater. Process. Tech., 75, 222-234. https://doi.org/10.1016/S0924-0136(97)00368-3.
  • S.P.S.S. Sivam, M. Gopal, S. Venkatasamy and S. Singh. 2015. An experimental investigation and optimisation of ecological machining parameters on aluminium 6063 in its annealed and unannealed form, J. Chemical and Pharm. Sci., 9(9), 46-53.
  • S.P.S.S. Sivam, M. Gopal, S. Venkatasamy and S. Singh. 2015. Application of forming limit diagram and yield surface diagram to study anisotropic mechanical properties of annealed and unannealed SPRC 440E steels, J. Chemical and Pharm. Sci., 15-22.
  • M. Traversin and R. Kergen. 1995. Closed-loop control of the blank-holder force in deep-drawing: Finite-element modelling of its effects and advantages, J. Mater. Process. Tech., 50, 306-317. https://doi.org/10.1016/0924-0136(94)01389-I.
  • L. Gunnarsson and E. Schedin. 2001. Improving the properties of exterior body panels in automobiles using variable blank holder force, J. Mater. Process. Tech., 114, 168-173. https://doi.org/10.1016/S0924-0136(01)00727-0.
  • N. Krishnan and J. Cao. 2003. Estimation of optimal blank holder force trajectories in segmented binders using an ARMA model, J. Mech. Sci. Engg., 125(4), 763-770. https://doi.org/10.1115/1.1616948.
  • Z.Q. Sheng, S. Jirathearanat and T. Altan. 2004. Adaptive FEM simulation for prediction of variable blank holder force in conical cup drawing, Int. J. Mach. Tools Manuf., 44(5), 487-494. https://doi.org/10.1016/j.ijmachtools.2003.11.001.
  • S. Yoshihara, K.I. Manabe and H. Nishimura. 2005. Effect of blank holder force control in deep-drawing process of magnesium alloy sheet, J. Mater. Process. Tech., 170(3), 579-585. https://doi.org/10.1016/j.jmatprotec.2005.06.028.
  • D.K. Leu. 1999. The limiting drawing ratio for plastic instability of the cup drawing process, J. Mater. Process. Tech., 86(1-3), 168-176. https://doi.org/10.1016/S09240136(98)00307-0.
  • L. Duchene and A.M. Habraken. 2005. Analysis of the sensitivity of FEM predictions to numerical parameters in deep drawing simulations, Eur. J. Mech. A/Solids, 24(4), 614-629. https://doi.org/10.1016/j.euromechsol.2005.04.007.
  • R.K. Verma and S. Chandra. 2006. An improved model for predicting limiting drawing ratio, J. Mater. Process. Tech., 172(2), 218-224. https://doi.org/10.1016/j.jmatprotec.2005.10.006.
  • D.W.A. Rees. 1996. Sheet orientation and formability limits under diffuse necking, Appl. Math. Modelling, 20(8), 624-635. https://doi.org/10.1016/0307-904X(96) 00010-8.
  • D. Ravikumar. 2002. Formability analysis of extra-deep-drawing steel, J. Mater. Process. Tech., 130-131, 31-41. https://doi.org/10.1016/S0924-0136(02)00789-6.
  • A.G. Mamalis, D.E. Manolakos and A.K. Baldoukas. 1997. Simulation of sheet metal forming using explicit finite-element techniques: effect of material and forming characteristics, Part 1. Deep- drawing of cylindrical cups, J. Mater. Process. Tech., 72(1), 48-60. https://doi.org/10.1016/S0924-0136(97)00128-3.
  • L.F. Menezes and C. Teodosiu. 2000. Three-dimensional numerical simulation of the deep-drawing process using solid finite elements, J. Mater. Process. Tech., 97(1-3), 100-106. https://doi.org/10.1016/S0924-0136(99)003453.
  • J.M. Antunes, L.F. Menezes, M.F. Vieira, J.V. Fernandes, B. Trindade, A.S. Ramos and M.T. Vieira. 2002. On the evaluation of the ductility of thin films, Mater. Sci. Engg.: A, 337(1-2), 97-103. https://doi.org/10.1016/S0921-5093(01)01991-8
  • R. Hill. 1948. A theory of the yielding and plastic flow of anisotropic metals, Proc. R. Soc. London Ser. A, 193, 281-297. https://doi.org/10.1098/rspa.1948.0045.
  • S.H. Park. 1996. Robust Design & Analysis for Quality Engg., Chapman & Hall, London.
  • S.P.S.S. Sivam, A. Lakshmankumar, K.S. Moorthy and Rajendra kumar. 2015. Investigation exploration outcome of heat treatment on corrosion resistance of aa 5083 in marine application, Int. J. Chemical Sci., 15-22.
  • S.P.S.S. Sivam, K. Saravanan, N. Pradeep, K. Moorthy and S. Rajendra kumar. 2018. The grey relational analysis and anova to determine the optimum process parameters for friction stir welding of Ti and Mg alloys, Periodica Polytechnica Mech. Engg., 62(4), 277-283. https://doi.org/10.3311/PPme.12117.
  • S.P.S.S. Sivam, M.D.J. Bhat, S. Natarajan, N. Chauhan. 2018. Analysis of residual stresses, thermal stresses, cutting forces and other output responses of face milling operation on Ze41 magnesium alloy, Int. J. Modern Manuf. Tech., X(1), 92-100.

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  • Numerical Evaluation and Influence of Product Quality and its defects Measures on the drawing of Stainless Steel Cross Member for Automobiles

Abstract Views: 496  |  PDF Views: 152

Authors

S. P. Sundar Singh Sivam
Dept. of Mech. Engg., SRM Institute of Sci. and Tech., Tamil Nadu, India
Ganesh Babu Loganathan
Dept. of Mechatronics Engg., ISHIK University, ERBIL, KRG, Iraq
K. Saravanan
Dept. of Mechatronics Engg., SRM Institute of Sci. and Tech., Tamil Nadu, India
V. G. Umasekar
Dept. of Mech. Engg., SRM Institute of Sci. and Tech., Tamil Nadu, India
S. Rajendrakumar
Dept. of Mech. Engg., SRM Institute of Sci. and Tech., Tamil Nadu, India

Abstract


Industrial enterprises increasingly demand optimum quality of products keeping in consideration a strict adherence where forming parameters are concerned. As far as incorporating the vital forming process upon an assortment of materials is concerned, it has grown excruciatingly challenging for industrial enterprises for laying out the adequately precise and suitable parameters. The flaws that are engendered during the process of sheet metal forming are inevitable. Flaws of this nature can be, however, kept within minimal proportions by introducing variations into the process parameters by Trial and Error methodology. This evidently results in a subsequent financial loss, not to mention an irrevocable loss of time and material. Dynaform simulation of defects combined with optimization is carried out with the help of Minitab. This method, as can be conjectured with considerable ease, yields optimum results, for it replaces much to our convenience the need for specialist industrial expertise besides leading to considerable savings in cost, time and material. This study would optimize the SS304sheet metal forming parameters FLD, thickness and thinning with three input parameters, namely, the lower binder force, tool travel velocity and binder close velocity.

Keywords


Sheet Metal Forming, Binder Close Velocity, Taguchi Orthogonal Array, Defect Measurements.

References





DOI: https://doi.org/10.4273/ijvss.11.1.19