OPTIMIZATION OF PROCESS PARAMETERS IN SUBMERGED ARC WELDING USING CUCKOO ALGORITHM

Welding of heavy thickness plates is always a challenging job for a production engineer for applications like ship building and heavy pressure vessels. Submerged arc welding is the best possible solution among other alternative possible solution. Granular flux completely covered with arc in order to avoid oxidation and this will help to produce good quality of the joint with less skilled manpower. In recent years, there has been a tremendous increase in the interest of submerged arc welding to weld very thick materials. This is not only a robust and efficient process but it also holds great scope of research and improvement. These areas of improvement include increase in weld bead width, weld penetration, weld reinforcement, tensile strength and weld hardness are the response parameters, whereas welding current, voltage, weds speed, wire feed rate are the input parameters in the present study. One such area of improvement that has been gaining quite some momentum in the recent years is the use of different optimization methods in order to obtain the perfect combinations of process parameters to obtain the desired results. In the present work Welding aspects of mild steel AISI 1040 is investigating in the present work. Using L9 orthogonal array experiment are carried using the input parameters and response parameters are evaluated. Optimization carried one such powerful tool is Cuckoo Optimization Algorithm (COA), is a computational method that optimizes a problem by iteratively trying to improve a candidate solution regarding a given measure of quality.