Prognostics and Health Management (PHM) and Cyber-Physical System (CPS) are major technologies in smart factory research. In PHM, the fault diagnosis and remaining useful life (RUL) prediction of several manufacturing systems including the industrial welding robot, 3D printer and CNC machining center have been studied based on appropriate artificial intelligence (AI) algorithms. In addition, CPS development is carried out via a digital twin of the physical mechanical system. For instance, the digital twin of the industrial welding robot has been developed through the kinematic modeling and synchronization between physical and cyber signals.

Manufacturing automation is another important area of research for successful smart factory implementation. In this work, the automatic fabric gripping and transfer system has been realized. In particular, the vision-based fabric recognition module and the adaptive gripping module with movable grippers are newly developed. The developed modules are attached to the industrial robot to perform automated grip and transfer of fabrics by considering their shape, thickness and position.