Fault dependency (D)-matrix is a systematic analytic model to catch the different system-level fault diagnostic information consisting of conditions between recognizable symptoms and failure modes connected with a system. Constructing a D-matrix from earlier principles and redesigning it utilizing the space learning is a difficult task and time intensive assignment. Further, in-time augmentation of D-matrix through the revelation of new symptoms and failure modes watched for the first run through is a testing assignment. An ontology based D-matrix depict an ontology based text mining strategy for consequently constructing and redesigning a D-matrix by mining countless repair verbatim (normally written in unstructured text) gathered during the diagnosis scenes.