The new generation information technology, such as Big Data, artificial intelligence, has an important role in promoting the digital transformation of the aviation manufacturing industry. In view of the characteristics of multisource and heterogeneity, few samples, and strong correlation of data in the aviation manufacturing industry, utilizing a new generation of knowledge engineering technologies such as knowledge graph with the ability of structured description and efficient management of data, this paper established a technical system and process for aviation data intelligence based on the event graph. The research focused on the technical methods such as ontology modeling, event relationship recognition, event extraction, and event disambiguation for aviation data. With a selection of aviation product quality data for data intelligence technology validation, the research team carried out a series of work pertinent to application and prototype system developments, including classification of quality problem causes, construction of quality event graph, logic knowledge push, etc., to assists the identification of quality problem and the rapid response to quality issues. The results indicated that the technical system and path of using data and knowledge to carry out digital intelligent quality management are feasible, and the quality knowledge extraction algorithm based on event graph has strong practicality, and provided support for promoting the application of digital intelligence in the whole life cycle of aviation manufacturing industry.