Augmented Reality (AR) technology facilitates interactions with information and understanding of complex situations. Aeronautical Maintenance combines complexity induced by the variety of products and constraints associated to aeronautic sector and the environment of maintenance. AR tools seem well indicated to solve constraints of productivity and quality on the aeronautical maintenance activities by simplifying data interactions for the workers. However, few evaluations of AR have been done in real processes due to the difficulty of integrating the technology without proper tools for deployment and assessing the results. This paper proposes a method to select suitable criteria for AR evaluation in industrial environment and to deploy AR solutions suited to assist maintenance workers. These are used to set up on-field experiments that demonstrate benefits of AR on process and user point of view for different profiles of workers. Further work will consist on using these elements to extend results to AR evaluation on the whole aeronautical maintenance process. A classification of maintenance activities linked to workers specific needs will lead to prediction of the value that augmented reality would bring to each activity.
Augmented Reality (AR) enhances the comprehension of complex situations by making the handling of contextual information easier. Maintenance activities in aeronautics consist of complex tasks carried out on various high-technology products under severe constraints from the sector and work environment. AR tools appear to be a potential solution to improve interactions between workers and technical data to increase the productivity and the quality of aeronautical maintenance activities. However, assessments of the actual impact of AR on industrial processes are limited due to a lack of methods and tools to assist in the integration and evaluation of AR tools in the field. This paper presents a method for deploying AR tools adapted to maintenance workers and for selecting relevant evaluation criteria of the impact in an industrial context. This method is applied to design an AR tool for the maintenance workshop, to experiment on real use cases, and to observe the impact of AR on productivity and user satisfaction for all worker profiles. Further work aims to generalize the results to the whole maintenance process in the aeronautical industry. The use of the collected data should enable the prediction of the impact of AR for related maintenance activities.
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