Case study in utilizing the Internet of Things as a PHM architecture for aerospace applications

Abstract

A significant challenge in creating an operational prognostic health management (PHM) system in the aerospace industry is building a secure, reliable system architecture that is capable of gathering, organizing, and processing large amounts of relevant data from numerous potentially disparate assets. This is further complicated by capturing the information whether the assets are co-located or geographically distributed over a large area. This is one of the reasons that historically PHM has not been utilized on individual aerospace assets, resulting in systems that have either limited or no PHM capabilities requiring a fleet-based statistical PHM approach. Advanced PHM systems that provide tracking for individual assets have the potential for large lifecycle cost reductions and the ability to better understand the current state of each asset and assess the overall readiness of the fleet. This is driving a search for technologies in other comparative industries that can assist in overcoming this problem in the aerospace industry. This paper presents the Internet of Things (IoT) as a potential solution to this problem. Background information on IoT including history, current state-of-the-art, limitations, and the ecosystem of IoT are provided. The applicability of IoT technologies to PHM in the aerospace industry is discussed. A case study where commercially available IoT technologies were used as the framework on which a prototype PHM system was developed, including diagnostic and prognostic capabilities, for monitoring the health of a fleet of aerospace launch system assets is presented. Challenges and lessons learned from this case study are enumerated, and future work in the areas of system scalability and security are further elucidated.