Weld residual stress prediction using artificial neural network and Fuzzy logic modeling

Abstract

intelligent tools such as expert systems, artificial neural network and fuzzy logic support decision-making are being used in intelligent manufacturing systems. Success of intelligent manufacturing systems depends on effective and efficient utilization of intelligent tools. <span style="mso-bidi-font-weight:bold">Weld residual stress depends on different process parameters and its prediction and control is a challenge to the researchers. In this paper, intelligent predictive techniques artificial neural network (ANN) and fuzzy logic models are developed for weld residual stress prediction. The models are developed<span style="mso-bidi-font-weight:bold"> using Matlab toolbox functions<span style="mso-bidi-font-weight:bold">. Data set required to train the models are obtained through finite element simulation. Results from the fuzzy model are compared with the developed <span style="mso-bidi-font-weight: bold">artificial neural network model, and these models are also validated.

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