In recent years, Prognostic & Health Management (PHM) has become a topic of strong interest in the aerospace domain. Health assessment and remaining useful life estimation for on-board systems provide several advantages, mainly related to the increased analysis capabilities and the reduction of maintenance interventions (and, consequently, of operating costs). For this reason, it is of interest for the aerospace industry to identify and define efficient strategies both for the introduction of native PHM capabilities in new generation on-board systems and for the retrofit of existing ones. This paper proposes a strategy for the scalable deployment of PHM techniques for on-board systems, with particular focus on edge computing capabilities. Different reference scenarios (ranging from cloud-based processing to local-only processing) are presented, and an edge-focused PHM architecture is discussed in detail, with the relative challenges addressed. The design and validation of proposed edge-based solution is described, with specific reference to its support for an existing data analytics framework. The solution is then assessed against a reference aerospace use case involving a representative aircraft braking system, focusing on computational aspects to highlight the compatibility of the proposed deployment strategy with efficient on-board computations.
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PHM, remaining useful life, Health assessment, estimation, on-board systems, aerospace
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