Many aircraft assets are subject to both preventive (scheduled) and corrective (unscheduled) replacement policies to ensure adequate levels of reliability and availability. The problem, particularly for assets that exist in large quantities, is that preventive replacement tasks often involve removing the entire population of assets from the aircraft, regardless of whether any assets were previously replaced on a corrective basis beforehand. To avoid the costs associated with premature asset removal, this study assesses the use of a cyber-physical systems approach to the management of identified aircraft assets. This approach builds on an industrial architecture that has been implemented and deployed in the aviation maintenance environment. This study outlines how the cyber-physical based identification of assets can facilitate balancing maintenance replacement policies to optimise long-run average costs per unit time. A mathematical model is proposed, and the suggested approach is validated using industrial data.