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A Hypergraph-Based Knowledge Representation Model for Smart Product-Service System Development

Authors :
Li Xinyu
Chen Chun-Hsien
Zheng Pai
Wang Zuoxu
Source :
Volume 2: 41st Computers and Information in Engineering Conference (CIE).
Publication Year :
2021
Publisher :
American Society of Mechanical Engineers, 2021.

Abstract

In the trend of digital servitization, manufacturing companies have been transforming their business paradigms to Smart product-service systems (Smart PSS) by integrating products and associated services as bundles. To support the knowledge-intensive process of Smart PSS development, massive domain knowledge should be well-organized and reused. However, due to the existence of non-binary relations caused by product-service bundles (PSB) and context-awareness concerns in the Smart PSS development activities, conventional graph-based approaches for knowledge representation may lose essential information in transforming non-binary relations into binary ones, and hence cause incorrect results in the subsequent knowledge queries. To mitigate this problem, a hypergraph-based knowledge representation model for Smart PSS was proposed, which represents the non-binary relations among multiple entities with hyperedges. Technically, the knowledge source and the typical hyperedge schema in Smart PSS development are identified in this paper. A detailed case study in the scenarios of 3D printing troubleshooting and PSB recommendation was conducted to showcase the proposed hypergraph-based knowledge representation model and demonstrate its validity. The results show that the hypergraph-based knowledge model significantly relieves the sparsity in the ordinary KG by adding multiple hyperedges. It is anticipated that the proposed hypergraph knowledge representation model can serve as a fundamental study for further knowledge reasoning activities.

Details

Database :
OpenAIRE
Journal :
Volume 2: 41st Computers and Information in Engineering Conference (CIE)
Accession number :
edsair.doi...........07a5f2d4176afa694c1fe74dea935050
Full Text :
https://doi.org/10.1115/detc2021-66732