Loading...

An optimization method for radial forging process using ANN and taguchi method

Sanjari, M ; Sharif University of Technology | 2009

466 Viewed
  1. Type of Document: Article
  2. DOI: 10.1007/s00170-008-1371-2
  3. Publisher: 2009
  4. Abstract:
  5. In this study, the artificial neural network (ANN) and the Taguchi method are employed to optimize the radial force and strain inhomogeneity in radial forging process. The finite element analysis of the process verified by the microhardness test (to confirm the predicted strain distribution) and the experimental forging load published by the previous researcher are used to predict the strain distribution in the final product and the radial force. At first, a combination of process parameters are selected by orthogonal array for numerical experimenting by Taguchi method and then simulated by FEM. Then the optimum conditions are predicted via the Taguchi method. After that, by using the FEM results, an ANN model was trained and the optimum conditions are predicted by means of ANN (using genetic algorithm as global optimization procedure) and compared with those achieved by the Taguchi method. The optimum conditions are verified by FEM, and good agreement is found between the two sets of results. © 2008 Springer-Verlag London Limited
  6. Keywords:
  7. Backpropagation ; Finite element method ; Forging machines ; Forgings ; Global optimization ; Metal forming machines ; Neural networks ; Optimization ; Process control ; Taguchi methods ; ANN ; FEM Analysis ; Inhomogeneity ; Process optimization ; Radial forging ; Taguchi method ; Forging
  8. Source: International Journal of Advanced Manufacturing Technology ; Volume 40, Issue 7-8 , 2009 , Pages 776-784 ; 02683768 (ISSN)
  9. URL: https://link.springer.com/article/10.1007/s00170-008-1371-2