• Gaurav Patel
• Jigar Shah
• Jatin Makwana
• Purvi Chauhan

MIG Welding is widely used by engineers and production personnel as a quick and effective welding process for joining metals. Process parameters of MIG welding are considered as the utmost significant influences that affects the quality, productivity and cost of welding process. The work presents effect of such welding parameters like welding current, welding voltage, gas flow rate, wire feed rate, etc. on weld strength, ultimate tensile strength and hardness of weld joint using design of experiments method. The above mentioned parameters were optimized using Genetic Algorithm and suitable combination of parameters were proposed for target quality using ANOVA. A prediction model is also developed using Artificial Neural Network. The analysis provides significance of said process parameters and its effect on the quality and strength of joint.

Optimization, MIG Welding, ANN, GA, UTS, hardness

"Optimization and Prediction of MIG Welding Process Parameters using ANN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 11, page no.1011-1016, November-2018, Available :http://www.jetir.org/papers/JETIRK006153.pdf

"Optimization and Prediction of MIG Welding Process Parameters using ANN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 11, page no. pp1011-1016, November-2018, Available at : http://www.jetir.org/papers/JETIRK006153.pdf