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Intelligent planning of product assembly sequences based on spatio-temporal semantic knowledge

Hongjuan Yang (School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan, China)
Jiwen Chen (School of Mechanical and Electrical Engineering, Shandong Jianzhu University, Jinan, China)
Chen Wang (School of Mechanical and Electrical Engineering, Shandong Jianzhu University, Jinan, China)
Jiajia Cui (School of Mechanical and Electrical Engineering, Shandong Jianzhu University, Jinan, China)
Wensheng Wei (School of Mechanical and Electrical Engineering, Shandong Jianzhu University, Jinan, China)

Assembly Automation

ISSN: 0144-5154

Article publication date: 14 July 2020

Issue publication date: 15 September 2020

308

Abstract

Purpose

The implied assembly constraints of a computer-aided design (CAD) model (e.g. hierarchical constraints, geometric constraints and topological constraints) represent an important basis for product assembly sequence intelligent planning. Assembly prior knowledge contains factual assembly knowledge and experience assembly knowledge, which are important factors for assembly sequence intelligent planning. This paper aims to improve monotonous assembly sequence planning for a rigid product, intelligent planning of product assembly sequences based on spatio-temporal semantic knowledge is proposed.

Design/methodology/approach

A spatio-temporal semantic assembly information model is established. The internal data of the CAD model are accessed to extract spatio-temporal semantic assembly information. The knowledge system for assembly sequence intelligent planning is built using an ontology model. The assembly sequence for the sub-assembly and assembly is generated via attribute retrieval and rule reasoning of spatio-temporal semantic knowledge. The optimal assembly sequence is achieved via a fuzzy comprehensive evaluation.

Findings

The proposed spatio-temporal semantic information model and knowledge system can simultaneously express CAD model knowledge and prior knowledge for intelligent planning of product assembly sequences. Attribute retrieval and rule reasoning of spatio-temporal semantic knowledge can be used to generate product assembly sequences.

Practical implications

The assembly sequence intelligent planning example of linear motor highlights the validity of intelligent planning of product assembly sequences based on spatio-temporal semantic knowledge.

Originality/value

The spatio-temporal semantic information model and knowledge system are built to simultaneously express CAD model knowledge and assembly prior knowledge. The generation algorithm via attribute retrieval and rule reasoning of spatio-temporal semantic knowledge is given for intelligent planning of product assembly sequences in this paper. The proposed method is efficient because of the small search space.

Keywords

Acknowledgements

This research is supported by the Key Research and Development project of Shandong Province (No. 2016GGX103042, 2019GGX104095), National Natural Science Foundation of China (NSFC Grant No.61303087). Thanks to the senior editor from American Journal Experts, for linguistic advise.

Citation

Yang, H., Chen, J., Wang, C., Cui, J. and Wei, W. (2020), "Intelligent planning of product assembly sequences based on spatio-temporal semantic knowledge", Assembly Automation, Vol. 40 No. 5. https://doi.org/10.1108/AA-11-2018-0196

Publisher

:

Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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