Towards an ontology-supported case-based reasoning approach for computer-aided tolerance specification

Yuchu Qin, Wenlong Lu, Qunfen Qi, Xiaojun Liu, Meifa Huang, Paul J. Scott, Xiangqian Jiang

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

In this paper, an ontology-supported case-based reasoning approach for computer-aided tolerance specification is proposed. This approach firstly considers the past tolerance specification problems and their schemes as previous cases and the new tolerance specification problems as target cases and uses an ontology to represent previous and target cases. Then certain ontology-based similarity measure is used to assess the similarity between the toleranced features of target and previous cases, the similarity between the part features of target and previous cases, and the similarity between the topological relations of target and previous cases. Based on these similarities, an ontology-based similarity measure for computing the similarity between target and previous cases is designed, and an algorithm for establishing such similarity measure with high accuracy and retrieving similar previous cases for a target case with this similarity measure is presented. This algorithm shows how to linearly combine the similarity of toleranced features, the similarity of part features, and the similarity of topological relations to assess the similarity between target and previous cases to implement retrieval of previous cases under the prerequisite of ensuring the highest accuracy of the similarity measure. The paper also reports a prototype implementation of the proposed approach, provides an example to illustrate how the approach works, and evaluates the approach via theoretical and experimental comparisons.

LanguageEnglish
Pages129-147
Number of pages19
JournalKnowledge-Based Systems
Volume141
Early online date14 Nov 2017
DOIs
Publication statusPublished - 1 Feb 2018

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Case based reasoning
Ontology
Specifications
Tolerance
Case-based reasoning
Similarity measure

Cite this

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title = "Towards an ontology-supported case-based reasoning approach for computer-aided tolerance specification",
abstract = "In this paper, an ontology-supported case-based reasoning approach for computer-aided tolerance specification is proposed. This approach firstly considers the past tolerance specification problems and their schemes as previous cases and the new tolerance specification problems as target cases and uses an ontology to represent previous and target cases. Then certain ontology-based similarity measure is used to assess the similarity between the toleranced features of target and previous cases, the similarity between the part features of target and previous cases, and the similarity between the topological relations of target and previous cases. Based on these similarities, an ontology-based similarity measure for computing the similarity between target and previous cases is designed, and an algorithm for establishing such similarity measure with high accuracy and retrieving similar previous cases for a target case with this similarity measure is presented. This algorithm shows how to linearly combine the similarity of toleranced features, the similarity of part features, and the similarity of topological relations to assess the similarity between target and previous cases to implement retrieval of previous cases under the prerequisite of ensuring the highest accuracy of the similarity measure. The paper also reports a prototype implementation of the proposed approach, provides an example to illustrate how the approach works, and evaluates the approach via theoretical and experimental comparisons.",
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Towards an ontology-supported case-based reasoning approach for computer-aided tolerance specification. / Qin, Yuchu; Lu, Wenlong; Qi, Qunfen; Liu, Xiaojun; Huang, Meifa; Scott, Paul J.; Jiang, Xiangqian.

In: Knowledge-Based Systems, Vol. 141, 01.02.2018, p. 129-147.

Research output: Contribution to journalArticle

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