Competency-Based Decision-Making Framework for Predictive Maintenance in Aviation
摘要
Despite growing interest in predictive maintenance (PdM) within the aviation industry, the success of such initiatives often depends less on algorithmic performance or sensor capabilities and more on internal organizational competencies. This study examines how aviation companies’ internal structures shape the feasibility, scope, and sustainability of PdM projects. It introduces a decision-support framework that aligns the complexity of maintenance strategies with company-specific competencies across three key dimensions: technical (T), economic (E), and IT (I). A fourth dimension—Integration (M)—is added to capture the managerial ability to coordinate cross-functional collaboration effectively. The research classifies aviation companies into seven strategic groups and identifies which PdM strategies are realistically attainable based on current competency profiles. A dynamic project lifecycle model is also proposed, demonstrating how the evolution of these competencies over time influences project sustainability and return on investment. The paper makes two key contributions. First, it provides a practical framework for assessing organizational readiness and selecting PdM methods aligned with internal capabilities, thereby increasing the likelihood of project success. Second, it offers strategic recommendations for the broader aviation ecosystem—including airlines, MROs, OEMs, IT firms, and regulatory bodies—on how to build a more collaborative, standardized, and competency-driven environment for predictive maintenance adoption.