To boost efficiency and effectiveness in failure diagnosis, defect rectification and critical maintenance processes on board the RSN’s Formidable-class stealth frigates, an inter-disciplinary DSTA team collaborated with the RSN to demonstrate the use of augmented reality (AR) technology.
STRETCHING POTENTIAL OF AUGMENTED REALITY
The project entailed the delivery of a prototype that improves maintenance workflow through the use of an electronic fault diagnosis tool on a mobile handset application and AR glasses that enable engineers to walk through the corrective maintenance process. The team overlaid step-by-step instructions and safety process reminders, as well as projected animations of the immediate process onto the actual equipment to better support process accuracy and mitigate risks of errors. The use of AR overlays on actual equipment would also serve to highlight danger zones such as regions of high temperature or components in motion.
From the outset, the team understood that ergonomics of the handset app and AR glasses would be a key consideration for user adoption. To determine the best approach, the team studied how other organisations have successfully applied AR in equipment maintenance, and the benefits gained from its implementation. Although AR technology has been applied in industries such as oil, manufacturing, medical and sports for several years, the eyewear models available were limited as market demand for them was still growing. Hence, the team benchmarked theoretical performances of AR eyewear models in the market, as well as sought hardware performance feedback from other teams within DSTA which had explored the use of AR in maintenance training. Thereafter, the DSTA team conceptualised the user experience design, functional requirements, as well as the application and development of AR for the RSN.
ENGAGING STAKEHOLDERS FOR BETTER FIT
To derive user requirements and to frame the approach better, the team conducted interviews with the frigate’s marine engineers and RSN personnel who were attached to DSTA. In doing so, they managed to experience the actual working environment, and appreciate the strengths and weaknesses of the current workflow which supported the uncovering of user needs through observation and experiential learning. As an example, the prototype concept was originally focused only on demonstrating AR technology. However, by examining the complete workflow involved in corrective maintenance tasks, it was clear that a significant amount of time was spent on arriving at a correct diagnosis of the causes of failure. The team also found that much of the diagnosis process was tacit, and knowledge was transferred through on-the-job training. As such, the prototype concept was then broadened to encompass a diagnosis support tool that could help an engineer filter through possible causes of failure by entering the system error codes seen on the system consoles. Digitising this expertise would allow it to be retained and transferred over time. DSTA then developed a system design workflow to crystallise the broad functionalities that would benefit the frigate’s marine engineers, and to define a comprehensive scope of work.
With a baseline prototype that was viable and scoped to be delivered within three months, the RSN could quickly assess the applicability of AR glasses in increasing baseline competency of the frigate’s marine engineers carrying out complex corrective maintenance on the vessels’ diesel engines. Diagnosis support tools and step-wise walkthroughs would also boost first-time fixes, reduce maintenance turnaround time by approximately 30 per cent and mitigate risks of mistakes. Safety in maintenance was increased with live overlays projected onto the equipment from the engineers’ field of view, and footage captured by the AR glasses could be remotely streamed to a supervisor or recorded for archival.
To support the engineers’ typical workflow comprehensively, the team introduced an electronic logbook function that would enable them to log system parameters, and be reminded automatically when the equipment is due for preventive maintenance. Data received through this module would then support back-end performance and predictive analytics. In addition, notes recorded in the electronic logbook could be assessed by other engineers so that a common understanding could be achieved within the engineering team. DSTA delivered the maintenance mobile application and AR glasses module prototype to the RSN in March 2018.