An ontology-based knowledge framework for engineering material selection

Yingzhong Zhang, Xiaofang Luo, Yong Zhao, Hong Chao Zhang

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

Engineering material selection intensively depends on domain knowledge. In the face of the large number and wide variety of engineering materials, it is very necessary to research and develop an open, shared, and scalable knowledge framework for implementing domain-oriented and knowledge-based material selection. In this paper, the fundamental concepts and relationships involved in all aspects of material selection are analyzed in detail. A novel ontology-based knowledge framework is presented. The ontology-based Semantic Web technology is introduced into the semantic representation of material selection knowledge. The implicit material selection knowledge is represented as a set of labeled instances and RDF instance graphs in terms of the concept model, which provides a formal approach to organizing the captured material selection knowledge. A knowledge retrieval and reasoning approach integrating ontology concepts, instances, knowledge rules, and semantic queries encoded with Query-enhanced Web Rule Language (SQWRL) is proposed. The presented knowledge framework can provide powerful knowledge services for material selection. Finally, based on this knowledge framework, a case study on constructing a mold material selection knowledge system is provided. This work is a new attempt to build an open and shared knowledge framework for engineering material selection.

Original languageEnglish
Pages (from-to)985-1000
Number of pages16
JournalAdvanced Engineering Informatics
Volume29
Issue number4
DOIs
StatePublished - Oct 2015

Keywords

  • Engineering materials
  • Knowledge representation
  • Material selection
  • Ontology

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