Digital Twin-Enabled Predictive Maintenance and Supply Chain Optimization for Fighter Aircraft

Abstract

This paper examines how a digital twin can support predictive maintenance and improve supply chain performance in fighter aircraft operations. The study reviews existing practices in condition monitoring and identifies the limitations of conventional maintenance and inventory planning methods used for military aviation fleets. A conceptual framework is then proposed to show how sensor data, aircraft health models, maintenance planning tools, and supply chain systems can interact as a single ecosystem. The framework demonstrates how real-time information can be used to anticipate component degradation, schedule maintenance more effectively, and align spare-parts procurement with predicted requirements. The findings highlight the potential of digital-twin technology to enhance aircraft readiness and reduce operational disruptions by improving both technical decision-making and material availability.