We propose BL.MixedR, a context-aware augmented maintenance system designed to assist technicians during field maintenance work. BL.MixedR is directly interfaced with our existing CMMS ecosystem composed of a desktop version and a mobile one to assist field technicians. This allows it to directly fetch work order data and support files (documentation, videos, images, etc.) from the CMMS, thus, eliminating the need to recreate the work orders specifically for an AR usage. BL.MixedR enhances traditional work orders in many ways to fully exploit the capabilities of augmented reality. It allows maintenance managers in charge of creating work orders to configure the behavior of the support files during maintenance work, such as which information to show the technician, when to show it and in which format. Moreover, the maintenance manager can anchor the support files near the location of the current task in the workspace of the technician, which allows him to access the right information, at the right time and at the right location, while keeping his hands free to do the maintenance work. Furthermore, technicians have access to a guidance system that allows them to orient themselves in their workspace and identify the location of the next task.
BL.MixedR is the result of several iterations of user-centered design and multiple evaluations by maintenance experts in real conditions on the field. The prototype was designed in collaboration with some of our biggest maintenance management solutions clients and evaluated in the field in various contexts such as the maintenance of manufacturing plants and several services of a big hospital. Experts found the prototype “very useful”, “attractive and original”, “easy to learn” and “a great tool to improve the overall maintenance work”. Overall, technicians found added value in the enhanced work orders. The information displayed was “pertinent” and they particularly appreciated having access to the relevant information contained in each support file, as opposed to having to find it themselves. The automatic positioning of these information near the location of each task seemed to help in reducing the cognitive load as well as the time to access pertinent information, which can have positive effects on task completion time. Report features such as taking pictures, recording videos, and recording audio were found “useful”. Finally, the technicians appreciated having their hands free all the time.