Detection of weld defects using real-time monitoring and controlling algorithm is of the significant task in manufacturing industries due to the increased production and liability costs that result when weld defects are not identified early in the production cycle. Monitoring and controlling for robotic arc welding process employed should be reliable, flexible and cost-effective in non-clean, high-volume production environments. Also, the robotic welding system has been utilized a complex jigging and mechanical devices to move the workpiece which related to the stationary welding head for getting higher efficiency and lower costs. To develop the fully robotic welding system, people make use of their senses of sound and/or sight to collect welding information, and take the necessary... corrective measurements to ensure the weld quality after processing is satisfactory. Therefore, it is really required that the monitoring and controlling algorithm of sensors for increasing effectiveness in the robotic welding process has been developed.In this paper, bead-on-plate welding using an infrared thermography in the robotic GMA (Gas Metal Arc) welding process has been performed to study the effects of welding parameters on thermal profile characteristics and find the optimal offset distance which applied for monitoring and controlling of welding quality such as bead height. The analysis for correlation between temperature distributions at three offset distance and bead height which based on the regression analysis such as Standard Error of Estimate (SEE), the coefficient of correlation (R) and coefficient of determination (R2) and (Predictive Ability of Model) has been done. The infra-red sensor is useful for monitoring the isotherm radii that arise during the robotic welding process and identifying bead height as welding quality.