Application of digital twin for industrial process control: A case study of gauge-looper-tension optimized control in strip hot rolling DOI Creative Commons
Jie Sun, Chen Shang,

Chengyan Ding

et al.

Digital Twin, Journal Year: 2024, Volume and Issue: 4, P. 10 - 10

Published: Oct. 14, 2024

Background During the hot rolling process, performance of most control systems gradually degrades due to equipment aging and changing process conditions. However, existing gauge-looper-tension method remain restricted by a lack intelligent parameter maintenance strategies. Methods To address this challenge enhance smart manufacturing capabilities strip rolling, based on digital twin method, paper proposes data-driven optimized for system rolling. First, model is constructed serve as an evaluation optimization platform. Subsequently, relevant data are collected calculate Hurst index identifying controller during process. Additionally, controllers with poor values, crayfish algorithm employed adjusting parameters maximum index. Results A real case steel production was used validate proposed method. Experimental results demonstrate that can effectively recognize state controller. Moreover, after optimizing through (COA), value showed significant improvement. Conclusions The -based capability maintain strategy production. Through increasing from 0.574 0.862.

Language: Английский

Application of digital twin for industrial process control: A case study of gauge-looper-tension optimized control in strip hot rolling DOI Creative Commons
Jie Sun, Chen Shang,

Chengyan Ding

et al.

Digital Twin, Journal Year: 2025, Volume and Issue: 4, P. 10 - 10

Published: Feb. 7, 2025

During the hot rolling process, performance of most control systems gradually degrades due to equipment aging and changing process conditions. However, existing gauge-looper-tension method remain restricted by a lack intelligent parameter maintenance strategies. To address this challenge enhance smart manufacturing capabilities strip rolling, based on digital twin method, paper proposes data-driven optimized for system rolling. First, model is constructed serve as an evaluation optimization platform. Subsequently, relevant data are collected calculate Hurst index identifying controller during process. Additionally, controllers with poor values, crayfish algorithm employed adjusting parameters maximize index. Experimental results demonstrate that effectively recognized state successfully enhances system. Therefore, platform, proposed can maintain performance-degraded systems.

Language: Английский

Citations

0
A generic digital twin model construction strategy for cross-field implementations with comprehensiveness, operability and scalability DOI
Xiaojun Liu,

Chongxin Wang,

Feng Wang

et al.

Journal of Manufacturing Systems, Journal Year: 2025, Volume and Issue: 80, P. 366 - 379

Published: March 25, 2025

Language: Английский

Citations

0
Application of digital twin for industrial process control: A case study of gauge-looper-tension optimized control in strip hot rolling DOI Creative Commons
Jie Sun, Chen Shang,

Chengyan Ding

et al.

Digital Twin, Journal Year: 2024, Volume and Issue: 4, P. 10 - 10

Published: Oct. 14, 2024

Background During the hot rolling process, performance of most control systems gradually degrades due to equipment aging and changing process conditions. However, existing gauge-looper-tension method remain restricted by a lack intelligent parameter maintenance strategies. Methods To address this challenge enhance smart manufacturing capabilities strip rolling, based on digital twin method, paper proposes data-driven optimized for system rolling. First, model is constructed serve as an evaluation optimization platform. Subsequently, relevant data are collected calculate Hurst index identifying controller during process. Additionally, controllers with poor values, crayfish algorithm employed adjusting parameters maximum index. Results A real case steel production was used validate proposed method. Experimental results demonstrate that can effectively recognize state controller. Moreover, after optimizing through (COA), value showed significant improvement. Conclusions The -based capability maintain strategy production. Through increasing from 0.574 0.862.

Language: Английский

Citations

2