Evaluating Prototype Augmented and Adaptive guidance system to support Industrial Plant Maintenance

We evaluate AR for Plant maintenance by measuring how a prototype guidance system, tested under representative conditions, impacts performance. We are motivated to determine the cost-benefit of interactive guidance for hazardous, repetitive tasks and we observe an improvement of 21% efficiency, 50% accuracy and 19% reduced task load. AR has already been shown to deliver improvements in task performance, however, there is limited research exploring the integration of AR into complete task routines which presents a barrier to adoption. We apply mixed reality guidance via two within-group experiments. We measure efficiency and accuracy over a complete routine conducted under simulated conditions. Results compare AR versus Static and AR versus Adaptive. We conclude AR is best suited to demanding spatial translation and completion under pressure. We suggest AR offers potential in similar routines and propose further work to integrate in a live setting.