Optimization using genetic algorithm of GMAW parameters for Charpy impact test of 080M40 steel

Gas Metal Arc Welding popularly known as Metal Inert Gas (MIG) is a welding technique widely in the industries for the joining purposes. The objective of this paper is to explore near-optimal MIG welding parameters such as voltage and current using genetic algorithm technique. These optimized parameters will result in maximum impact energy of the weldment which is determined using Charpy impact test. Initially an experimental study was conducted on EN8 (080M40) steel specimens through MIG welding process. The samples were machined, prepared and organized for tests. One specimen was cut and polished as per the requirement of Charpy impact test. Remaining samples were first cut then welded using different values of welding parameters (voltage and current). After wards these welded samples also went through Charpy impact testing. The filler wire used is AWSA5.18, ER70S-6 for welding purposes. Further, the other samples were machined for the Charpy impact test as suggested by American Society for Testing and Materials A370 10 mm × 10 mm ×55 mm with a 45°, 2 mm deep V notch at the center having a base radius of 0.25 mm. For analyzing the results through MATLAB, the neural network is utilized. The Analysis of Variance (ANOVA) is applied to find the optimal welding quality of the material. Further, Genetic Algorithms is using current as 70A–100A and voltage with the range from 9.6 to 10.7 V to find optimum weld parameters. ANOVA was implemented to get the most significant factors which affect the response parameters. The value of R2 is greater than 0.90 which implies that welding parameters were optimum. The optimum parameter for welding current and voltage is 100A and 9.6 V. Further, after implementing optimum parameters the optimal result for impact energy is 32.82 J.