Optimization of an aluminum profile extrusion process based on Taguchi’s method with S/N analysis

Self Cite

Aluminum profile extrusion involves complex thermal, tribological, and mechanical interactions; thus, material flow and thermal behavior during extrusion process are very complicated. In this work, the material flow and thermal behavior of a 7 × × × aluminum alloy profile during an entire extrusion cycle are investigated numerically and experimentally. Hot compression tests are firstly carried out, and inverse analysis method is used to identify the material parameters of AA7N01 in Arrhenius constitutive model. The calculated global error is only 6.2 % between the predicted and experimental force-displacement curves, which verifies that the proposed model and obtained material parameters can describe well the rheological behavior of this alloy at elevated temperatures. Then a thermo-mechanical finite element model based on DEFROM-3D is built, and the transient extrusion process of the profile is simulated. By numerically analyzing the nose-end shape of the extruded profile, the evolution curves of exit temperature and of extrusion load, material flow and thermal behavior during extrusion process are investigated, respectively. Practical extrusion experiments verify the numerical model and results. Additional microstructure examination with electron backscatter diffraction (EBSD) technique also shows fine grains with the uniform grain size of about 9 μm on different locations of the extruded profile. Therefore, the material constitutive model and numerical model of extrusion process built in this work are capable enough to provide theoretical guidance in optimizing process parameters and designing extrusion dies.Keywords Thermo-mechanical behavior . Transient extrusion process . Arrhenius constitutive model . Inverse analysis method . High-strength 7 × × × aluminum alloy

Section: Introductionmentioning

confidence: 99%

Numerical and experimental investigation on thermo-mechanical behavior during transient extrusion process of high-strength 7 × × × aluminum alloy profile

Yang

Wang

Zhao

et al. 2016

Self Cite

“…By using the signal to noise (S/N) ratio, they optimized the control factors. Zhang et al [18] used the Taguchi method to design the experiments. They studied 32 combinations of process parameters to simulate the extrusion process to produce the hollow aluminum profile with HyperXtrude.…”

Section: Introductionmentioning

confidence: 99%

Simulation and optimization of hot extrusion process to produce rectangular waveguides

Sharififar

Mousavi

2015

In this study, the Taguchi method and genetic algorithm are employed to optimize the die geometry in order to obtain the minimum magnitude of extrusion force to produce the rectangular waveguides. Waveguides are hollow metal tubes for transporting electromagnetic energy from one region to another. A combination of process parameters was selected using orthogonal array Taguchi method. The results were then simulated by finite element method (FEM). By using the analysis of variance (ANOVA) method, the effective parameters and their interactions were determined. By using the FEM results, an artificial neural network (ANN) model was trained, and the effects of die factors on the extrusion force were studied for constant thermal and frictional conditions. Moreover, the optimum conditions were predicted by means of genetic algorithm (GA) method which was verified by experimental procedure. The optimum die length and billet hole diameter were obtained at L=20 and D=3 cm, respectively, for the initial billet temperature of 450°C and friction coefficient of 0.1.

“…Qamar et al [10] analyzed the effect of the shape complexity on the dead metal zone and metal flow through the flat-faced dies by experimental and numerical methods using Ansys-LS-Dyna. Zhang et al [11] applied Taguchi's design to optimize the aluminum extrusion process of hollow sections based on experimental data and the results of numerical simulations.…”

Section: Introductionmentioning

confidence: 99%

Extrusion load prediction of gear-like profile for different die geometries using ANN and FEM with experimental verification

Bingöl

Ayer

Altinbalik

2014

This paper deals with the extrusion of gear-like profiles and uses of finite element method (FEM) and artificial neural network (ANN) to predict the extrusion load. In the study, gear-like components has been manufactured by forward extrusion for the AA1070 aluminum alloy and the process was simulated by using a DEFORM-3D software package to establish a database in order to provide the data for ANN modeling. Serious experiments were performed for only one die set and four teeth gear profile to obtain data for comparing with DEFORM-3D results. After verifying a highly appropriate FEM simulation with the experiment at the same conditions, Results were enhanced for different die lengths, extrusion ratios, and two extra teeth number as three and six using FEM simulations. Subsequently, the data from the performed FEM simulations were submitted for the best obtained ANN model. Finally, a good agreement between FEsimulated and ANN-predicted results was obtained. The proposed ANN model is found to be useful in predicting the forming load of the different die set variations based on the reliable test data.