Abstract
This study shows the correlation between the design methodology of the artificial neural network (ANN) and the statistical design of experiments (DOE) approach and is demonstrated for process design in various metal forming processes. After investigating the effect of each parameter upon the characteristics by the Taguchi method which is one of the DOE, orthogonal array (OA) table and characteristics are applied to ANN as experimental data and then opiimal design parameters are established. Using the rigid plastic FEM, the simulations are performed and the results of ANN are confirmed. This technique requires smaller runs than the conventional method to find the optimal condition of design parameters for the design’s aim. This new technique can be used in a wide range of metal forming process designs.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
