An ontology-based knowledge representation framework for aircraft maintenance processes to support work optimization

As a critical business activity in the aircraft life cycle, maintenance processes are highly complex and require multidisciplinary knowledge. Knowledge integration and representation oriented toward aircraft maintenance processes are necessary to improve work efficiency. Nonetheless, conventional approaches lack effective unified management, which obstructs domain knowledge sharing and ultimately impedes maintenance work. In this context, this paper proposes a knowledge representation framework based on the benefits of ontology, which formalizes multidisciplinary knowledge for aircraft maintenance processes. An ontology of aircraft maintenance processes is developed for knowledge conceptualization and reuse. On this basis, a domain knowledge extraction model based on the bidirectional encoder representation from transformers (BERT) is constructed to automatically extract entities and relationships related to maintenance processes. With a series of Semantic Web Rule Language (SWRL) rules, a knowledge reasoning method is proposed based on the aircraft maintenance process ontology to mine hidden knowledge. We evaluate the developed ontology and demonstrate the feasibility and usefulness of the proposed knowledge reasoning method in a case study. The results show that the proposed knowledge representation framework provides an effective knowledge formalization method for complex knowledge in aircraft maintenance processes to support work optimization.