FW-HTF-RL/Collaborative Research: The Future of Aviation Inspection: Artificial Intelligence and Mixed Reality as Agents of Transformation

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Globally, economies rely on safe air travel; however, with human error accounting for 70% of aircraft accidents, an emphasis needs to be placed on helping those responsible for ensuring the safety and reliability of modern and future aircrafts. Aviation maintenance technicians routinely struggle to keep pace with the needs of the aviation industry as they are impacted by a hazardous work environment, high cognitive load, a complex task, and growing worker shortages, and this struggle is only poised to grow as the need for them is slated to increase in the future. This Future of Work at the Human-Technology Frontier - Research: Large (FW-HTF-RL) award supports a collaborative research project to address this challenge, led by a group of universities, professional organizations and industry partners: Clemson University, Purdue University, Greenville Technical College, SA Technologies, National Center for Autonomous Technologies, Aviation Technician Education Council, ChooseAerospace, Frontier Airlines, AAR, Republic Airways, Atlas Air, Stevens Aerospace, Vericor, AMFA, and Lockheed Martin. The goal of this research project is to merge expertise and technological advancements in Artificial Intelligence (AI) and Extended Reality (XR) technologies to enhance the cognitive capabilities of aviation maintenance technicians during inspection tasks. The central idea is that this augmentation could increase their inspection capabilities, reduce workload, and ultimately reduce the number of aviation accidents caused by maintenance errors. In the long term, these efforts will continuously improve the overall health of both future aviation maintenance technicians and aircraft fleets. Furthermore, while this work has prioritized the immediate exploration of the aviation maintenance sector, similar domains that leverage information-rich tasks, visual inspection, and routine maintenance stand to benefit from the demonstrated technological integrations. This project brings together several disciplines, including Human Factors Engineering, Computer Science, Human-Computer Interaction, Behavioral and Social Science, Economics, and Aviation Maintenance. The investigator team is structured to achieve multiple convergent goals. First, this work leverages human factors, behavioral science, and human-computer interaction disciplines to understand the impacts that merged AI and XR technologies will have on the cognitive process of aviation maintenance technicians and the potential risks associated with the integration of these technologies into this workforce. Second, this research project leverages computer science and human-computer interaction to design and develop novel AI models that perform aircraft inspections and make maintenance recommendations based on information gathered through XR technologies. The research team will help design communication and interaction paradigms so future aviation maintenance technicians can understand and accept these recommendations. Third, the project could provide the breakthrough integration of AI and XR technology within the aviation maintenance field to help aviation maintenance technicians in real time. Finally, this effort continuously synthesizes the results of the other three goals with society and workforce-derived data to quantify the economic feasibility and impact that AI and XR technologies will have on the aviation maintenance domain and adjacent workplace sectors. This project has been funded by the Future of Work at the Human-Technology Frontier cross-directorate program to promote a deeper fundamental understanding of the interdependent human-technology partnership in work contexts by advancing the design of intelligent work technologies that operate in harmony with human workers.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.