Open AccessOptimization and Prediction of Melting Efficiency of Mild Steel Weldment, Using Genetic Algorithm
Author(s) -
Godfrey Ayeabu Sibete,
T Eyitemi.
Publication year - 2021
Publication title -
international journal of research and review
Language(s) - English
Resource type - Journals
eISSN - 2454-2237
pISSN - 2349-9788
DOI - 10.52403/ijrr.20210615
Subject(s) - welding , materials science , gas tungsten arc welding , genetic algorithm , inert gas , tungsten , metallurgy , algorithm , mechanical engineering , computer science , composite material , mathematical optimization , mathematics , engineering , arc welding
Melting efficiency which indicates how much of the heat deposited by the welding operation is used to produce melting is one of the most important parameters considered in Tungsten Inert Gas (TIG) welding when assessing the performance of welds. In the field of welding, a good melting efficiency results in the development of a dense weld pool. This study is conducted to optimize and predict the melting efficiency of mild steel weldment, using Genetic Algorithm. Genetic Algorithm (GA), which is an optimization method that mimics the evolution process and operates on the basis of the theory of natural selection and evolution was used to analyse the results. The result shows that a combination of current 239.03A, voltage 29.87V, welding speed 56.59mm/s, welding time 79.15 sec, feed rate 130mm/s, will produce optimal melting efficiency of 44.72.Keywords: Melting Efficiency, Mild Steel Weldment, Genetic Algorithm, Optimization and Prediction.