Theses and Dissertations

Issuing Body

Mississippi State University


Motoyama, Keiichi

Committee Member

Bammann, Douglas J.

Committee Member

Rais-Rohani, Masoud

Date of Degree


Document Type

Graduate Thesis - Open Access


Computational Engineering (Program)

Degree Name

Master of Science


James Worth Bagley College of Engineering


Computational Engineering Program


An effective approach to determine optimum welding process parameters is implementation of advanced computer aided engineering (CAE) tool that integrates efficient optimization techniques and numerical welding simulation. In this thesis, an automated computational methodology to determine optimum arc welding process parameters is proposed. It is a coupled Genetic Algorithms (GA) and Finite Element (FE) based optimization method where GA directly utilizes output responses of FE based welding simulations for iterative optimization. Effectiveness of the method has been demonstrated by predicting optimum parameters of a lap joint specimen of two thin steel plates and automotive structure of nonlinear welding path for minimum distortion. Three dimensional FE models have been developed to simulate the arc welding process and subsequently, the models have been used by GA as the evaluation model for optimization. The optimization results show that such a CAE based methodology can contribute to facilitate the product design and development.