Abstract
With the development of information technology, the goal of complex system maintenance and support is to be scientific prediction and precise logistics. There is an urgent need to build a flexible networked logistics architecture, to utilize the equipment's real-time health information efficiently and to schedule logistics resources successfully in a complex and dynamic logistics environment. In order to establish a precise, dynamic and networked maintenance system, the characteristics of logistics networks are analyzed entirely to improve logistics organization flexibility, a method of state collaborative analysis and intelligent support decision-making is proposed. This method generates test data through offline and online execution of fault test cases; based on online state monitoring and historical data of sensors, the equipment state is estimated and judged, thereby providing intelligent guarantee decision-making services.