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

Authors :
Qin, Yuchu
Lu, Wenlong
Qi, Qunfen
Liu, Xiaojun
Huang, Meifa
Scott, Paul J
Jiang, Xiangqian
Source :
Knowledge-Based Systems. Feb2018, Vol. 141, p129-147. 19p.
Publication Year :
2018

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09507051
Volume :
141
Database :
Academic Search Index
Journal :
Knowledge-Based Systems
Publication Type :
Academic Journal
Accession number :
126977454
Full Text :
https://doi.org/10.1016/j.knosys.2017.11.013