Squeezing force based digital feature analysis and qualified parameter range determination for percussive riveting skills training

In manual percussive riveting training, inconsistencies often occur: either the driven head meets quality standards but rivet/hole interference does not, or vice versa. This work presents the squeezing force-based training platform to enhance trainee skills and improve training efficiency. The quantitative relationship between squeezing force and key joint quality metrics (driven head morphology and rivet/hole interference) is established through systematic experiments. Qualified squeezing force thresholds are determined via experimental design and data analysis, enabling the algorithm to ensure trainees consistently produce joints with both qualified driven head morphology and rivet/hole interference. The comparative training results proves the effectiveness of the proposed squeezing force-based training method. The squeezing force based digital feature analysis and qualified parameter range determination procedures outlined in this work are quite general and can be used for any material/rivet combinations in percussive riveting skills training.

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Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture
Published
2026-03-07
DOI
https://doi.org/10.1177/09544054261420188
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

Squeezing force based digital feature analysis and qualified parameter range determination for percussive riveting skills training

Wanjiao Dong, Xiaoyi Chen, Hua Wang, Xuewei Li
Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture
Robot Manipulation and Learning
article

Squeezing force based digital feature analysis and qualified parameter range determination for percussive riveting skills training

Wanjiao Dong, Xiaoyi Chen, Hua Wang, Xuewei Li
article en

Abstract

In manual percussive riveting training, inconsistencies often occur: either the driven head meets quality standards but rivet/hole interference does not, or vice versa. This work presents the squeezing force-based training platform to enhance trainee skills and improve training efficiency. The quantitative relationship between squeezing force and key joint quality metrics (driven head morphology and rivet/hole interference) is established through systematic experiments. Qualified squeezing force thresholds are determined via experimental design and data analysis, enabling the algorithm to ensure trainees consistently produce joints with both qualified driven head morphology and rivet/hole interference. The comparative training results proves the effectiveness of the proposed squeezing force-based training method. The squeezing force based digital feature analysis and qualified parameter range determination procedures outlined in this work are quite general and can be used for any material/rivet combinations in percussive riveting skills training.

Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture
Shanghai Institute of Technology (CN)
Quality Education
Openalex Percentile: Top 28%
Robot Manipulation and Learning
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