A digital twin-enhanced collaborative maintenance paradigm for aero-engine fleet

Abstract

Maintenance of aero-engine fleets is crucial for the efficiency, safety, and reliability of the aviation industry. With the increasing demand for air transportation, maintaining high-performing aero-engines has become significant. Collaborative maintenance, specifically targeting aero-engine fleets, involves the coordination of multiple tasks and resources to enhance management efficiency and reduce costs. Digital Twin (DT) technology provides essential technical support for the intelligent operation and maintenance of aero-engine fleets. DT maps physical object properties to the virtual world, creating high-fidelity, dynamic models. However, DT-enhanced collaborative maintenance faces various challenges, including the construction of complex system-layer DT models, management of massive integrated DT data, and the development of fusion mechanisms and decision-making methods for DT data and models. Overcoming these challenges will allow the aviation industry to optimize aero-engine fleet maintenance, ensuring safety, efficiency, and cost-effectiveness while meeting the growing demand for air transportation.

Graphical abstract

Keywords

aero-engine fleet / collaborative maintenance / Digital Twin (DT) / complex system

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