Process Parameters Optimization for Isothermal Forging of Ti-6Al-4V Alloy using Taguchi Method and Artificial Neural Network

Enabling and developing the required „Process‟ efficiency in an Input-Process-Output System, is bound to provide effective solutions for today‟s need for maximized production especially in dwindling Input conditions. Process optimization is a significant and contributing step towards such process efficiency as it paves way for improved overall productivity. The present work involves, an approach using soft computing paradigm for the process parameter optimization of multiple input single output isothermal forging of Ti-6Al-4V alloy. In this paper a combination of Taguchi‟s L27 Orthogonal Array (OA-L27) along with back- propagation artificial neural network and engineering optimization concepts to determine the optimal process parameter settings of forging temperature, strain rate and strain for the isothermal forging. The optimum solution is valid in the ranges of forging process parameters that were used for training the artificial neural network.