Design and evaluation of augmented reality for nuclear power plant maintenance based on Cognitive activity analysis

Abstract

The goals of maintenance in nuclear power plants (NPPs) are to reduce the number of plant shutdowns, to decrease the shutdown time, to minimize the maintenance costs, and to improve nuclear safety. Furthermore, it is difficult for maintenance personnel to conduct work in NPPs due to the complexity of NPPs, safety issues and time constraints. Human errors should be prevented to achieve maintenance goals in NPPs. Therefore, it is necessary to improve working conditions by introducing support systems. Augmented Reality (AR) has the potential to assist with maintenance tasks and make maintenance personnel concentrate on the tasks, which will then the reduced human error and improve human performance. The working procedure for AR systems was designed based on the characteristics of cognitive activity, and an experiment was conducted to estimate the effectiveness of AR. The results indicated that a well-designed working procedure for AR systems was more effective than a conventional paper-based working procedure. In addition, participants made fewer errors using the designed working procedure. AR systems as maintenance support systems are beneficial technology that can improve maintenance performance by reducing cognitive loads and unnecessary movements. An AR application can be attractive and effective at supporting maintenance task.