Abstract
Data-driven predictive aircraft maintenance approach typically results in lower maintenance costs, avoiding unnecessary preventive maintenance actions and reducing unexpected failures. Information provided by a reliability analysis of aircraft components and systems can improve an existing maintenance strategy and ensure an optimal maintenance task interval. For reliability work, the exponential distribution is typically used; however, this approach requires substantial amounts of data, which often may not be generated by aviation operations. Therefore, this study proposes a method for reliability analysis given a small dataset. Real-life historical data of an aircraft operating in Nigeria validate the proposed approach and prove its applicability.
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