Construction of an Industrial Product Maintenance Knowledge Base Based on Crowdsensing and Knowledge Graph

With the rapid development of intelligentization and servitization in the manufacturing industry, higher demands are being placed on the maintenance of industrial products. As an information medium, knowledge graphs can efficiently organize and manage knowledge. Currently, data in industrial product maintenance knowledge bases typically come from official manuals, which do not consider users’ real industrial product usage experience. However, user experience encompasses foundational knowledge of industrial product maintenance, which is more specific and flexible. To address this gap, this paper proposes the combined use of crowdsensing and knowledge graphs for constructing an industrial product maintenance knowledge base. First, the basic framework of this method is presented. Next, an ontology model for industrial product maintenance is created, and the industrial product manual is instantiated to form the basic knowledge graph for industrial product maintenance. Then, a user experience reliability evaluation method is proposed, and user experiences are filtered by combining them with the basic industrial product maintenance knowledge graph. Finally, the filtered user experiences are added to the industrial product maintenance knowledge graph. The effectiveness of this process is illustrated through an example.