A Systematic Review of Advances, Challenges, and Optimization Strategies in Maintenance Logistics for Airside Operations

The increased complexity and operational imperatives of airside systems in modern aviation require robust, efficient, and sustainable logistics for maintenance. This study presents a systematic review of the literature on maintenance logistics in airside operations, focusing on its treatment within the domains of logistics and operations management. The research employs a structured approach that combines bibliometric mapping with thematic content analysis, drawing insights from 56 peer-reviewed articles published between 2012 and 2025. The research maps the intellectual structure and evolving thematic orientations of the discipline, demonstrating that most studies remain founded upon deterministic planning models, notwithstanding the uncertain nature of the aviation ecosystem. While existing studies integrate new applications of machine learning (ML), digital twins (DTs), and blockchain technologies for predictive maintenance and system traceability, these technologies are typically described in isolation with limited integration into existing systems. The integration highlights imperatives for airport managers and stakeholders to adopt both predictive and adaptive approaches to maintenance, to enhance real-time visibility of systems through digital means, and to integrate logistics planning with long-term sustainability and resilience objectives. The review identifies principal gaps in research, such as the underuse of stochastic modelling, the omission of developing broad-based frameworks to reconcile upstream and downstream operations, and the underuse of considering sustainability dimensions, as well as human-machine interaction dynamics in maintenance systems.