Construction and implementation of extraction rules for assembly hierarchy information of a product based on OntoSTEP

Gong, Hanqing; Shi, Lingling; Liu, Dongmei; Qian, Jiahui; Zhang, Zhijing

doi:10.1016/j.procir.2020.08.008

Cited by 6 publications

(2 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Different from ifcOWL, "OntoSTEP" from Krima et al (2009) serves a broader scope, based on which Barbau et al (2012) developed a plug-in for ontology editor Protégé. OntoSTEP integrates the concepts and semantic relationships into the geometry-enhanced ontology model and has been used to build a semantic-rich product model for a range of applications, such as program-generation for robotic manufacturing systems (Zheng et al, 2022), knowledge graph establishment for product quality assurance (Kwon et al, 2020), and feature extraction for assembly sequence planning (Gong et al, 2021).…”

Section: Related Workmentioning

confidence: 99%

A semantic similarity-based method to support the conversion from EXPRESS to OWL

Liu,

Jian,

Eckert

2023

AIEDAM

View full text Add to dashboard Cite

Product data sharing is fundamental for collaborative product design and development. Although the STandard for Exchange of Product model data (STEP) enables this by providing a unified data definition and description, it lacks the ability to provide a more semantically enriched product data model. Many researchers suggest converting STEP models to ontology models and propose rules for mapping EXPRESS, the descriptive language of STEP, to Web Ontology Language (OWL). In most research, this mapping is a manual process which is time-consuming and prone to misunderstandings. To support this conversion, this research proposes an automatic method based on natural language processing techniques (NLP). The similarities of language elements in the reference manuals of EXPRESS and OWL have been analyzed in terms of three aspects: heading semantics, text semantics, and heading hierarchy. The paper focusses on translating between language elements, but the same approach has also been applied to the definition of the data models. Two forms of the semantic analysis with NLP are proposed: a Combination of Random Walks (RW) and Global Vectors for Word Representation (GloVe) for heading semantic similarity; and a Decoding-enhanced BERT with disentangled attention (DeBERTa) ensemble model for text semantic similarity. The evaluation shows the feasibility of the proposed method. The results not only cover most language elements mapped by current research, but also identify the mappings of the elements that have not been included. It also indicates the potential to identify the OWL segments for the EXPRESS declarations.

show abstract

Section: Related Workmentioning

confidence: 99%

A semantic similarity-based method to support the conversion from EXPRESS to OWL

Liu,

Jian,

Eckert

2023

AIEDAM

View full text Add to dashboard Cite

show abstract

“…The typical case representation methods include object-oriented notation (Yehuda et al, 2013), frame notation (Zhu and Xia, 2006) and semantic web notation (Imran and Young, 2015). Among them, the semantic web notation method has more advantages in terms of representing semantic relationships and discrete knowledge (Gong et al, 2021;Qian et al, 2021). Therefore, ontology technology with the advantages of semantic representation is used to perform assembly knowledge modeling and a new concept of MLAO is proposed in this paper.…”

Section: Multilevel Assembly Ontologymentioning

confidence: 99%

Assembly process case matching based on a multilevel assembly ontology method

Gong

Shi

Zhai

et al. 2021

Self Cite

View full text Add to dashboard Cite

Purpose The purpose of this study is to achieve accurate matching of new process cases to historical process cases and then complete the reuse of process knowledge and assembly experience. Design/methodology/approach By integrating case-based reasoning (CBR) and ontology technology, a multilevel assembly ontology is proposed. Under the general framework, the knowledge of the assembly domain is described hierarchically and associatively. On this basis, an assembly process case matching method is developed. Findings By fully considering the influence of ontology individual, case structure, assembly scenario and introducing the correction factor, the similarity between non-correlated parts is significantly reduced. Compared with the Triple Matching-Distance Model, the degree of distinction and accuracy of parts matching are effectively improved. Finally, the usefulness of the proposed method is also proved by the matching of four practical assembly cases of precision components. Originality/value The process knowledge in historical assembly cases is expressed in a specific ontology framework, which makes up for the defects of the traditional CBR model. The proposed matching method takes into account all aspects of ontology construction and can be used well in cross-ontology similarity calculations.

show abstract

Research on management informatization construction of electric power enterprise based on big data technology

Zhao

2022

Energy Reports

View full text Add to dashboard Cite

Construction and implementation of extraction rules for assembly hierarchy information of a product based on OntoSTEP

Cited by 6 publications

References 4 publications

A semantic similarity-based method to support the conversion from EXPRESS to OWL

A semantic similarity-based method to support the conversion from EXPRESS to OWL

Assembly process case matching based on a multilevel assembly ontology method

Research on management informatization construction of electric power enterprise based on big data technology

Contact Info

Product

Resources

About