This paper proposes a data-based prediction method to predict the cycle time for robotic arm spot welding process using artificial intelligence model. Since the prediction of the cycle time of robotic arm is crucial for its utilization in documentation of an engineering plan, as it is closely associated with overall production efficiency and safety consideration. In this paper three meth- ods for estimating cycle time are introduced; 1) Estimation method based on a standard engi- neering cycle time table, 2) Cycle time calculation method using real time simulation data, and 3) Cycle time prediction method based on artificial neural network using robotic arm process information. We provide a comparative analysis of three methods, showcasing their respective performance. Additionally, through the application of the proposed approach. we elucidate the anticipated factors that can be expected to enhance overall effectiveness.
