A novel approach for developing a flexible automation system for rewinding an induction motor stator using robotic arm

Abstract

Electric motor rewinding is a traditional restorative and regenerative process, which is lagging in adopting new and current market trends. Stator rewinding is a crucial task in electric machine manufacturing and is the most challenging operation. This has raised the need to automate the system. In this light, this paper aims to develop a concept for developing a flexible automation system for rewinding an induction motor stator using a robot arm. To achieve this, a bottom-up approach and model predictive control (MPC) has been utilized in the design due to manufacturers' specification disparities. The results reveal that the system can be trained successfully, to perform the remanufacturing process 6 times faster than the manual process. The system also allows for data mining. Successful application of this approach will demonstrate the importance of using flexible automated systems for induction motor stator rewinding and reduce time and winding steps.