Product innovation design approach driven by implicit relationship completion via patent knowledge graph

Product innovation design process involves a great deal of discrete engineering knowledge, limiting the ability of designers to quickly utilize this knowledge to support design innovation. Nowadays, innovation design based on knowledge graphs has enhanced the ability to explore design knowledge, improving the efficiency of knowledge retrieval. Previous studies have focused on mining more design knowledge to enrich the knowledge graph overlooks the implicit relationships with potential value among design knowledge, wasting design resources. To address these issues, an approach for product innovation design based on implicit knowledge relationship completion in the patent knowledge graph is proposed, which explores the implicit relationships between design knowledge to provide new knowledge satisfying design preferences and enhance the innovativeness of solutions. First, a requirements-function-structure-benefit (RFSB) knowledge ontology is constructed and extracted from the benefit knowledge of patents to build the knowledge graph. Second, an implicit relationship completion model based on the similarity of function or benefit entities explores the implicit relationships, replacing structure entities directly connected to similar function or benefit entities to generate new relationships and outputs novel ideas. Third, a scheme improvement process based on the co-occurrence frequency of requirement and structure knowledge supplements neglected design preferences. Final, a pipeline inspection robot case study is further employed to verify the proposed approach, and a patent knowledge graph assisted design solution prototype system is developed to assist in the utilization of innovative design knowledge. Evaluation results show the significant design potential of the proposed approach in inspiring innovative thinking and knowledge reuse.