Improving Maintenance Efficiency with an Adaptive AR-assisted Maintenance System

Abstract

The lack of adaptability of existing Augmented Reality (AR) assisted maintenance systems has prevented the implementation of many existing AR systems in real industrial maintenance scenarios. This paper presents an adaptive Augmented Reality human-machine interface (AR-HMI) framework that can provide suitable sets of maintenance information and guidance to an operator during maintenance to enhance efficiency and safety. A human-centric framework has been developed to determine the most suitable types of information to be augmented and presented to the user. During maintenance, the AR-assisted system allows a user to request for a change in the types of augmentation via an explicit request or an implicit mechanism, which is based on the head-gaze of the user. To demonstrate the viability of the AR-HMI framework and AR-assisted system, a case study based on an industrial robot has been conducted.