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 logistics and operations management domains. The research undertakes a structured approach that involves combining bibliometric mapping with thematic content analysis and brings together insights from 56 peer-reviewed articles from the period 2012 to 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 uses of machine learning (ML), digital twins (DTs), and blockchain technologies for predictive maintenance and traceability of systems, these technologies are typically described in isolation with weak integration into systems. The integration points to imperatives for managers of airports and stakeholders to accept predictive as well as adaptive approaches to maintenance, to raise the visibility in real-time of systems through digital means, and to link logistics planning with long-term sustainability as well as resilience objectives. The review identifies principal gaps in research, such as the underuse of stochastic modelling, the omission to develop broad-basis frameworks to reconcile between upstream and downstream operation, and the underuse of considering sustainability dimensions, as well as human-machine interaction dynamics in systems for maintenance.