Optimization of porthole die geometrical variables by Taguchi method

Porthole die extrusion is commonly used to manufacture hollow profiles made of lightweight alloys for numerous industrial applications. The reliability of extruded parts is affected strongly by the quality of the longitudinal and transversal seam welds. According to that, the die geometry must be designed correctly and the process parameters must be selected properly to achieve the desired product quality. In this study, numerical 3D simulations have been created and run to investigate the role of various geometrical variables on punch load and maximum pressure inside the welding chamber. These are important outputs to take into account affecting, respectively, the necessary capacity of the extrusion press and the quality of the welding lines. The Taguchi technique has been used to reduce the number of the required numerical simulations necessary for considering the influence of twelve different geometric variables. Moreover, the Analysis of variance (ANOVA) has been implemented to individually analyze the effect of each input parameter on the two responses. Then, the methodology has been utilized to determine the optimal process configuration individually optimizing the two investigated process outputs. Finally, the responses of the optimized parameters have been verified through finite element simulations approximating the predicted value closely. This study shows the feasibility of the Taguchi technique for predicting performance, optimization and therefore for improving the design of a porthole extrusion process.Porthole die extrusion is commonly used to manufacture hollow profiles made of lightweight alloys for numerous industrial applications. The reliability of extruded parts is affected strongly by the quality of the longitudinal and transversal seam welds. According to that, the die geometry must be designed correctly and the process parameters must be selected properly to achieve the desired product quality. In this study, numerical 3D simulations have been created and run to investigate the role of various geometrical variables on punch load and maximum pressure inside the welding chamber. These are important outputs to take into account affecting, respectively, the necessary capacity of the extrusion press and the quality of the welding lines. The Taguchi technique has been used to reduce the number of the required numerical simulations necessary for considering the influence of twelve different geometric variables. Moreover, the Analysis of variance (ANOVA) has been implemented to individually analyze th...

[1]  Francesco Gagliardi,et al.  On the die design in AA6082 porthole extrusion , 2012 .

[2]  Elisabetta Ceretti,et al.  A new approach to study material bonding in extrusion porthole dies , 2009 .

[3]  Byung-Min Kim,et al.  A non-steady state FE analysis of Al tubes hot extrusion by a porthole die , 2006 .

[4]  Patrick Ulysse Optimal extrusion die design to achieve flow balance , 1999 .

[5]  A. Erman Tekkaya,et al.  Modeling Approach for the Determination of Material Flow and Welding Conditions in Porthole Die Extrusion with Gas Pocket Formation , 2013 .

[6]  Tanveer Hussain,et al.  Multi-response optimization in the development of oleo-hydrophobic cotton fabric using Taguchi based grey relational analysis , 2016 .

[7]  Hao Chen,et al.  Multiobjective optimization design of porthole extrusion die using Pareto-based genetic algorithm , 2013 .

[8]  Yuin Wu,et al.  Taguchi Methods for Robust Design , 2000 .

[9]  Henry Valberg,et al.  Extrusion welding in aluminium extrusion , 2002 .

[10]  Alexander Brosius,et al.  Experimental and Numerical Analysis of Material Flow in Porthole Die Extrusion , 2011 .

[11]  Lorenzo Donati,et al.  The prediction of seam welds quality in aluminum extrusion , 2004 .

[12]  Guoqun Zhao,et al.  Optimization of an aluminum profile extrusion process based on Taguchi’s method with S/N analysis , 2012 .

[13]  Hao Chen,et al.  Optimization of porthole extrusion dies with the developed algorithm based on finite volume method , 2016 .