Pattern recognition of control charts based on data feature enhancement and ensemble learning of classifiers for dimensional accuracy of products-Reference-Cited by-同舟云学术

Pattern recognition of control charts based on data feature enhancement and ensemble learning of classifiers for dimensional accuracy of products

Published:2024-08-22 Issue: Volume: Page:1-20
ISSN:0020-7543
Container-title:International Journal of Production Research
language:en
Short-container-title:International Journal of Production Research

Author:

Chu Hongyan¹²,Dong Yuefeng¹²,Cheng Qiang¹²,Yan Jun¹²^ORCID,Zhao Yongsheng¹²,Cao Jianqiang¹²,Zhang Caixia¹²,Chen Xuehan³

Affiliation:

1. Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, People’s Republic of China

2. Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing, People’s Republic of China

3. Jiangxi Tianyue Auto Electric Co, Jiangxi, People’s Republic of China

Funder

Beijing Municipal Science and Technology

China Postdoctoral Science Foundation

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207543.2024.2387095

Reference42 articles.

1. A mixed control chart to monitor the process

2. Azamfirei, V., Y. Lagrosen, and A. Granlund. 2021. “Harmonising Design and Manufacturing: A Quality Inspection Perspective.” In 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), September, 1–7. Vasteras: IEEE.

3. Application of automation for in-line quality inspection, a zero-defect manufacturing approach

4. An expert system for control chart pattern recognition

5. Recognition of control chart patterns using a neural network-based pattern recognizer with features extracted from correlation analysis