This paper presents a simulation of a 6 degrees-of-freedom (6R) articulatedrobot arm using back propagation neural network to solve the problem regardinginverse kinematics for the industrial articulated robot. The Denavit – Hartenberg modelis used to analyze the robot arm movement. Next, the forward kinematics is used toidentify the relationships for each joint of the robot arm and to determine variousparameters for learning system of random neural network for 5,000 data points. Thesimulation results show that the robot arm can move to target positions with precision,and the average error for the entire 6 joints is at approximately 4.03 degrees.