Forward and reverse modeling in MIG welding process using fuzzy logic-based approaches

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.