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Testability is a critical characteristic for fault management in Integrated System Health Engineering and Management (ISHEM). The paper promotes a general-purpose graph and matrix based approach to fault management supporting concurrent system engineering facing to ISHEM. The relationship during functions, tests, components, failure modes can be simplified to be represented by the hierarchical dependency model which is an evolution of the graph theory model. Meanwhile, there is other useful information, such as fault dictionary, conclusions of FMECA, etc, can be represented by matrix. Matrix and graph can be combined together because graph model can be represented by matrix either. Inevitably, many NP problems such as test sequencing, fault isolation strategy generation, multiple failure diagnosis, exist in fault management. Therefore, artificial intelligent algorithms should be imported to give certain optimal or near-optimal solutions to those NP problems. AI-ESTATE has provided a excellent framework for engineers to execute fault management, but the concrete solution should be developed to support AI-ESTATE. The paper tends to give out a solution to fault management facing to ISHEM from the aspect of graph theory model and multidimensional matrix based intelligent information mining, processing and verification.