MULTIPLE OBJECTIVE OPTIMIZATION OF SUBMERGED ARC WELDING PROCESS PARAMETERS USING GREY BASED FUZZY LOGIC

In the present work, an attempt has been made to apply an efficient technique, Grey based fuzzy logic method to solve correlated multiple response optimization problems, in the field of submerged arc welding. This approach converts the complex multiple objectives into a single grey-fuzzy reasoning grade. Based on grey-fuzzy reasoning grade, optimum levels of parameters (Welding current, arc voltage and welding speed) are identified. Nine experiments based on an orthogonal array of Taguchi method were performed. Weld bead hardness and material deposition rate were selected as the quality targets. The optimal procedure is proposed and developed for solving the optimal multi-response problem, which applies the grey relational coefficient in each response and converts a grey-fuzzy reasoning grade so as to evaluate multiple responses. The significant contributions of parameters are estimated using Analysis Of Variance (ANOVA). Confirmation test is conducted and reported. It is found that the welding current is the most significant controlled factor for the process according to the weighted sum grade of the maximum weld bead hardness and material deposition rate. This evaluation procedure can be used in intelligent decisionmaking for a welding operator. The proposed and developed method has good accuracy and competency. The paper highlights a detailed methodology of the proposed scheme and its effectiveness. The proposed technique provides manufacturers to develop intelligent manufacturing system to achieve the highest level of automation.