摘要: With the ever increasing complexity of airborne systems, it is becoming extremely hard to identify, analyze and resolve problems during the life-cycle of aircraft. Increasing the reliability of future air vehicles designed for the... 展开 With the ever increasing complexity of airborne systems, it is becoming extremely hard to identify, analyze and resolve problems during the life-cycle of aircraft. Increasing the reliability of future air vehicles designed for the airspace with rapidly growing traffic, collecting data during the system design and manufacturing phases and fetching information about the product's future from this data is becoming critical. Digital Twin is defined as a virtual copy of a product that is created starting from the very first moment when the product idea materializes. The virtual copy reflects the real one by using all of the available data. Digital Twin also promises understanding, learning and reasoning from the real-time product data. Nowadays, data collection, data analytics, machine learning and Big Data are gaining importance within Digital Transformation. These technological improvements are also pushing the Digital Twin concept. This paper aims at, while not exclusive, a comprehensive review of the available approaches and technologies, in addition to the challenges facing Digital Twin and the future of Digital Twin for aircraft. 收起