Research Information System
APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, no.2, 2025 (SCI-Expanded)
As an emerging technology, digital twin (DT) studies are gaining momentum in both academia and industry. Specifically, the aerospace industry can benefit significantly from the implementation of DT technology since its products and processes are complex, technically challenging, and costly. DTs enable a comprehensive technology integration capacity and holistic approach in the product life cycle. However, for simplification, implementations of DT to processes in the aerospace industry are often handled independently without integration with other related processes. In this study, we propose a methodological framework to integrate different processes throughout the essential parts of aircraft's life cycle. In pursuit of creating a DT of the system for managing the life cycle of aircraft, all aspects and processes have been thoroughly examined. Ten main components for the management of DTs are identified. Statistical and stochastic approaches for enhancing the analytical capabilities of DTs are discussed. Within the scope of Product Life Cycle Management and from the perspective of Systems Engineering, we advocate creating the DT of an aircraft by combining the DTs for each component through a digital thread.