Revolutionizing aircraft maintenance: The role of predictive maintenance in aviation

Abstract

This literature review synthesizes existing knowledge on the crucial role of data in predictive maintenance (PdM) within the aviation sector, examining its significance, benefits, and technological foundations. The review also investigates the broader relevance of PdM across various industries, drawing upon case studies related to PdM in aviation as practical examples. Through an extensive analysis of academic papers, industry reports, and empirical evidence, this review offers a comprehensive overview of the current state of research and practice in data-driven PdM, emphasizing its impact on reliability, safety, cost-efficiency, and the adoption of advanced data analytics and predictive models. This research investigates the pivotal role of data in predictive maintenance (PdM) within the aviation sector, elucidating its significance and benefits. Three primary research questions guide this study:

Why is PdM important for aviation? This question highlights the unique challenges faced by airlines in maintaining a fleet of aircraft, emphasizing the criticality of PdM in ensuring safety, reliability, and cost-efficiency.

What technologies are used in conducting PdM? This question delves into the technological foundations of PdM, elucidating the data sources, analytics tools, and predictive models employed in proactive maintenance practices.

Is PdM relevant in other industries? This inquiry explores the transferability of PdM principles and methodologies to diverse industries beyond aviation, shedding light on the broader implications of data-driven maintenance strategies.

The research draws upon an array of case studies related to PdM in the aviation industry and other industries, providing empirical evidence of its effectiveness and showcasing real-world applications. These case studies serve as valuable sources of practical insights and examples.