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Article type: Research Article
Authors: Ganjigatti, J.P. | Pratihar, Dilip Kumar
Affiliations: Department of Industrial Engineering and Management, Siddaganga Institute of Technology, Tumkur – 572 103, Karnataka, India | Department of Mechanical Engineering, Indian Institute of Technology, Kharagpur – 721 302, India
Note: [] Corresponding author: Associate Professor, Department of Mechanical Engineering, Indian Institute of Technology, Kharagpur – 721 302, India. Tel.: +91 3222 282992; Fax: +91 3222 282278; E-mail: [email protected]
Abstract: Metal inert gas welding is a multi-input and multi-output process. In forward modeling, the outputs (also known as the responses) are expressed as the functions of input variables (also called the process parameters), whereas in reverse modeling, the latter are represented as the functions of the former. The above modeling may be required for an effective on-line control of a process. Statistical regression analysis can tackle the problem of forward modeling efficiently but it may not be always able to solve the problem of reverse modeling. The present work is a novel attempt to carry out the forward and reverse modeling of the said welding process using fuzzy logic-based approaches. The developed soft computing-based approaches are found to solve the above problem efficiently.
Keywords: MIG welding, forward modeling, reverse modeling, fuzzy logic, genetic algorithm
Journal: Journal of Intelligent & Fuzzy Systems, vol. 19, no. 2, pp. 115-130, 2008
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