Fast and Accurate Quality Prediction for Injection Molding: An Improved Broad Learning System Method-Reference-Cited by-同舟云学术

Fast and Accurate Quality Prediction for Injection Molding: An Improved Broad Learning System Method

Published:2024-06-01 Issue:11 Volume:24 Page:18499-18510
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Lin Jianghao¹^ORCID,Ren Zhigang²^ORCID,Wu Zongze³^ORCID,Ouyang Zhouhao⁴^ORCID,Yang Aimin⁵

Affiliation:

1. School of Automation, Guangdong University of Technology, Guangzhou, China

2. School of Automation and Guangdong Key Laboratory of IoT Information Technology, Guangdong University of Technology, Guangzhou, China

3. College of Mechatronics and Control Engineering and Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen University, Shenzhen, China

4. Future Tech, South University of Technology, Guangzhou, China

5. School of Computer Science and Intelligence Education, Lingnan Normal University, Zhanjiang, China

Funder

Key-Area Research and Development Program of Guangdong Province

National Natural Science Foundation of China

Open Research Fund from Guangdong Laboratory of Artificial Intelligence and Digital Economy

14th Five-Year Plan for Philosophy and Social Sciences Project of Guangdong

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7361/10546898/10472417.pdf?arnumber=10472417

Reference29 articles.

1. Multiobjective optimization of process parameters for plastic injection molding via soft computing and grey correlation analysis

2. In-Mold Sensors for Injection Molding: On the Way to Industry 4.0

3. Learning quality characteristics for plastic injection molding processes using a combination of simulated and measured data

4. Monitoring, prediction and control of injection molding quality based on tie-bar elongation

5. Deep Feature Selection Framework for Quality Prediction in Injection Molding Process