Preform tool shape optimization and redesign based on neural network response surface methodology

Preform tool shape optimization using response surface method (RSM) was developed in this work. Neural network approximation model was employed for response surface construction in order to overcome the limitation of quadratic polynomial model in solving non-linear problems. A two-step axisymmetric forging problem was studied as an example using proposed method. Optimum was achieved by using pattern search optimization method to search response surface describing relationship between preform shape and die cavity fill ratio. In addition to that, with respect to the complexity of the optimum solution, the knowledge-based redesign concept was proposed. Simplified preform shape description model was built based on the knowledge extracted from previous optimization and additional shape optimization in terms of a new optimization objective was conducted to obtain a better redesign preform shape. Finally, comparison was made between the original optimal shape and redesigned one; better result was achieved by using the concept proposed.

[1]  Ramana V. Grandhi,et al.  Computer aided preform design in forging using the inverse die contact tracking method , 1996 .

[2]  Guido Berti,et al.  Thermo-mechanical fatigue life assessment of hot forging die steel , 2005 .

[3]  Nicholas Zabaras,et al.  A sensitivity analysis for the optimal design of metal-forming processes , 1996 .

[4]  A. Olsson,et al.  On Latin hypercube sampling for structural reliability analysis , 2003 .

[5]  Jean-Loup Chenot,et al.  OPTIMAL DESIGN FOR NON‐STEADY‐STATE METAL FORMING PROCESSES—I. SHAPE OPTIMIZATION METHOD , 1996 .

[6]  Somnath Ghosh,et al.  A new approach to optimal design of multi-stage metal forming processes with micro genetic algorithms , 1997 .

[7]  Tomas Jansson,et al.  Optimizing sheet metal forming processes—Using a design hierarchy and response surface methodology , 2006 .

[8]  J. Chung,et al.  Application of a genetic algorithm to process optimal design in non-isothermal metal forming , 1998 .

[9]  Farrokh Mistree,et al.  Kriging Models for Global Approximation in Simulation-Based Multidisciplinary Design Optimization , 2001 .

[10]  Naksoo Kim,et al.  Preform design in H-shaped cross sectional axisymmetric forging by the finite element method , 1990 .

[11]  Jan Kusiak.  A technique of tool-shape optimization in large scale problems of metal forming , 1996 .

[12]  Bradley N. Maker,et al.  On Drawbeads in Sheet Metal Forming , 2000 .

[13]  Robert Michael Lewis,et al.  Pattern Search Algorithms for Bound Constrained Minimization , 1999, SIAM J. Optim..

[14]  Ramana V. Grandhi,et al.  Design of forging process variables under uncertainties , 2005 .

[15]  Ramana V. Grandhi,et al.  3D preform shape optimization in forging using reduced basis techniques , 2005 .

[16]  Douglas C. Montgomery,et al.  Response Surface Methodology: Process and Product Optimization Using Designed Experiments , 1995 .

[17]  Ramana V. Grandhi,et al.  PREFORM DIE SHAPE DESIGN IN METAL FORMING USING AN OPTIMIZATION METHOD , 1997 .

[18]  P. Villon,et al.  Moving least squares response surface approximation: Formulation and metal forming applications , 2005 .