Research on the Online Monitoring of the Service Status of Hot-Rolling Mill Work Rolls and Online Decision-Making Method for Active Remanufacturing

Yuhao Zhang; Chen Wei; Xiaoqing Tian; Shouxu Song

doi:doi:10.11648/j.ijimse.20230802.12

Research Article |

| Peer-Reviewed

Research on the Online Monitoring of the Service Status of Hot-Rolling Mill Work Rolls and Online Decision-Making Method for Active Remanufacturing

Yuhao Zhang, Chen Wei, Xiaoqing Tian^*, Shouxu Song

Published in International Journal of Industrial and Manufacturing Systems Engineering (Volume 8, Issue 2)

Received: 25 October 2023 Accepted: 9 November 2023 Published: 17 November 2023

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

The remanufacturing of rolling mill rolls offers significant economic, environmental, and societal benefits. However, the uncertainty surrounding the performance degradation of retired rolls and its associated timeline poses challenges to the efficiency and cost-effectiveness of roll remanufacturing operations. Therefore, the real-time monitoring of the degradation status of rolling mill rolls is of paramount importance. This study presents an approach that combines multi-sensor data fusion with a multilayer perceptron (MLP) model, which takes into account economic considerations to predict the degradation status of hot-rolling mill work rolls and make online decisions for active remanufacturing. The degradation process of rolling mill rolls is analyzed, and degradation performance indicators are established. Eddy current signals and torque signals from the rolling mill surface are collected during the roll degradation experiments. The friction coefficient and energy of the Hilbert spectrum of the eddy current signal are used as online input features for the MLP model, which is trained using the degradation experiment data. The superiority of the proposed MLP model is validated through rolling mill roll degradation experiments. Based on the predictions of the MLP model, the optimal timing for remanufacturing rolling mill rolls in the time domain is evaluated using Wiener and update-reward theories. This approach enables the online monitoring and quantitative characterization of the comprehensive degradation of high-speed steel work rolls and facilitates online decision-making regarding the optimal timing for active remanufacturing.

Published in	International Journal of Industrial and Manufacturing Systems Engineering (Volume 8, Issue 2)
DOI	10.11648/j.ijimse.20230802.12
Page(s)	30-41
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Hot Rolling Mill Rolls, Active Remanufacturing, Online Monitoring, Machine Learning

References

[1]	G. Singh and P. K. Singh, “Effect of process parameters on roll separating force, driving torque and end crop length during grooved hot rolling of SAE 1020 steel,” Journal of Manufacturing Processes, vol. 79, pp. 1003–1016, Jul. 2022, doi: 10.1016/j.jmapro.2022.05.015.
[2]	K. Hu, Y. Xia, F. Zhu, and N. Noda, “Evaluation of Thermal Breakage in Bimetallic Work Roll Considering Heat Treated Residual Stress Combined with Thermal Stress during Hot Rolling,” steel research int., vol. 89, no. 4, p. 1700368, Apr. 2018, doi: 10.1002/srin.201700368.
[3]	C. Wei, S. Song, and Z. Zhang, “Evaluation of elastic-plastic deformation in HSS work roll under coupling of residual stress thermal stress and contact stress during hot rolling,” Materials Today Communications, vol. 33, p. 104613, Dec. 2022, doi: 10.1016/j.mtcomm.2022.104613.
[4]	Q. Dong, Z. Wang, Y. He, L. Zhang, F. Shang, and Z. Li, “The effect of shifting modes on work roll wear in strip steel hot rolling process,” Ironmaking & Steelmaking, vol. 50, no. 1, pp. 67–74, Jan. 2023, doi: 10.1080/03019233.2022.2083929.
[5]	F. Weidlich, A. P. V. Braga, L. G. D. B. Da Silva Lima, M. B. Júnior, and R. M. Souza, “The influence of rolling mill process parameters on roll thermal fatigue,” Int J Adv Manuf Technol, vol. 102, no. 5–8, pp. 2159–2171, Jun. 2019, doi: 10.1007/s00170-019-03293-1.
[6]	S. Wu, W. Xing, Y. Liu, and Y. Shao, “Research on dynamic characteristics and identification method of local defect on the roll surface,” Engineering Failure Analysis, vol. 121, p. 105063, Mar. 2021, doi: 10.1016/j.engfailanal.2020.105063.
[7]	C. Li, H. Yu, G. Deng, X. Liu, and G. Wang, “Numerical Simulation of Temperature Field and Thermal Stress Field of Work Roll During Hot Strip Rolling,” J. Iron Steel Res. Int., vol. 14, no. 5, pp. 18–21, May 2007, doi: 10.1016/S1006-706X(07)60067-3.
[8]	N. F. Garza-Montes-de-Oca, R. Colás, and W. M. Rainforth, “On the damage of a work roll grade high speed steel by thermal cycling,” Engineering Failure Analysis, vol. 18, no. 6, pp. 1576–1583, Sep. 2011, doi: 10.1016/j.engfailanal.2011.06.001.
[9]	L. Xu, W. Song, S. Ma, Y. Zhou, K. Pan, and S. Wei, “Effect of slippage rate on frictional wear behaviors of high-speed steel with dual-scale tungsten carbides (M6C) under high-pressure sliding-rolling condition,” Tribology International, vol. 154, p. 106719, Feb. 2021, doi: 10.1016/j.triboint.2020.106719.
[10]	G. Y. Deng et al., “Theoretical and experimental investigation of thermal and oxidation behaviours of a high speed steel work roll during hot rolling,” International Journal of Mechanical Sciences, vol. 131–132, pp. 811–826, Oct. 2017, doi: 10.1016/j.ijmecsci.2017.08.024.
[11]	G. Y. Deng et al., “Evolution of microstructure, temperature and stress in a high speed steel work roll during hot rolling: Experiment and modelling,” Journal of Materials Processing Technology, vol. 240, pp. 200–208, Feb. 2017, doi: 10.1016/j.jmatprotec.2016.09.025.
[12]	C. G. Sun, S. M. Hwang, C. S. Yun, and J. S. Chung, “Investigation of thermomechanical behavior of a work roll and of roll life in hot strip rolling,” Metall Mater Trans A, vol. 29, no. 9, pp. 2407–2424, Sep. 1998, doi: 10.1007/s11661-998-0117-y.
[13]	L. Gan, L. Li, and H. Huang, “Digital Twin-Driven Sheet Metal Forming: Modeling and Application for Stamping Considering Mold Wear,” Journal of Manufacturing Science and Engineering, vol. 144, no. 121003, Jul. 2022, doi: 10.1115/1.4054902.
[14]	L. Gan, H. Huang, L. Li, W. Xiong, and Z. Liu, “IoT-enabled energy efficiency monitoring and analysis method for energy saving in sheet metal forming workshop,” J. Cent. South Univ., vol. 29, no. 1, pp. 239–258, Jan. 2022, doi: 10.1007/s11771-022-4933-9.
[15]	H. B. Lim, H. I. Yang, and C. W. Kim, “Analysis of the roll hunting force due to hardness in a hot rolling process,” J Mech Sci Technol, vol. 33, no. 8, pp. 3783–3793, Aug. 2019, doi: 10.1007/s12206-019-0721-3.
[16]	H. Xu and H. Huang, “CNN architecture-based hybrid fusion model for in-situ monitoring to fabricate metal matrix composite by laser melt injection,” J Intell Manuf, Sep. 2023, doi: 10.1007/s10845-023-02207-z.
[17]	F. Delaunois, V. I. Stanciu, A. Megret, and M. Sinnaeve, “Oxidation and wear behavior of high-speed steel and semi-high-speed steel used in hot strip mill,” Int J Adv Manuf Technol, vol. 119, no. 1, pp. 677–689, Mar. 2022, doi: 10.1007/s00170-021-08031-0.
[18]	C. Bataille, E. Luc, M. Bigerelle, R. Deltombe, and M. Dubar, “Rolls wear characterization in hot rolling process,” Tribology International, vol. 100, pp. 328–337, Aug. 2016, doi: 10.1016/j.triboint.2016.03.012.
[19]	M. Marani, M. Zeinali, V. Songmene, and C. K. Mechefske, “Tool wear prediction in high-speed turning of a steel alloy using long short-term memory modelling,” Measurement, vol. 177, p. 109329, Jun. 2021, doi: 10.1016/j.measurement.2021.109329.
[20]	P. Fermín-Cueto et al., “Identification and machine learning prediction of knee-point and knee-onset in capacity degradation curves of lithium-ion cells,” Energy and AI, vol. 1, p. 100006, Aug. 2020, doi: 10.1016/j.egyai.2020.100006.

Cite This Article

Plain Text BibTeX RIS

APA Style

Zhang, Y., Wei, C., Tian, X., Song, S. (2023). Research on the Online Monitoring of the Service Status of Hot-Rolling Mill Work Rolls and Online Decision-Making Method for Active Remanufacturing. International Journal of Industrial and Manufacturing Systems Engineering, 8(2), 30-41. https://doi.org/10.11648/j.ijimse.20230802.12

Copy | Download

ACS Style

Zhang, Y.; Wei, C.; Tian, X.; Song, S. Research on the Online Monitoring of the Service Status of Hot-Rolling Mill Work Rolls and Online Decision-Making Method for Active Remanufacturing. Int. J. Ind. Manuf. Syst. Eng. 2023, 8(2), 30-41. doi: 10.11648/j.ijimse.20230802.12

Copy | Download

AMA Style

Zhang Y, Wei C, Tian X, Song S. Research on the Online Monitoring of the Service Status of Hot-Rolling Mill Work Rolls and Online Decision-Making Method for Active Remanufacturing. Int J Ind Manuf Syst Eng. 2023;8(2):30-41. doi: 10.11648/j.ijimse.20230802.12

Copy | Download

@article{10.11648/j.ijimse.20230802.12,
  author = {Yuhao Zhang and Chen Wei and Xiaoqing Tian and Shouxu Song},
  title = {Research on the Online Monitoring of the Service Status of Hot-Rolling Mill Work Rolls and Online Decision-Making Method for Active Remanufacturing},
  journal = {International Journal of Industrial and Manufacturing Systems Engineering},
  volume = {8},
  number = {2},
  pages = {30-41},
  doi = {10.11648/j.ijimse.20230802.12},
  url = {https://doi.org/10.11648/j.ijimse.20230802.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijimse.20230802.12},
  abstract = {The remanufacturing of rolling mill rolls offers significant economic, environmental, and societal benefits. However, the uncertainty surrounding the performance degradation of retired rolls and its associated timeline poses challenges to the efficiency and cost-effectiveness of roll remanufacturing operations. Therefore, the real-time monitoring of the degradation status of rolling mill rolls is of paramount importance. This study presents an approach that combines multi-sensor data fusion with a multilayer perceptron (MLP) model, which takes into account economic considerations to predict the degradation status of hot-rolling mill work rolls and make online decisions for active remanufacturing. The degradation process of rolling mill rolls is analyzed, and degradation performance indicators are established. Eddy current signals and torque signals from the rolling mill surface are collected during the roll degradation experiments. The friction coefficient and energy of the Hilbert spectrum of the eddy current signal are used as online input features for the MLP model, which is trained using the degradation experiment data. The superiority of the proposed MLP model is validated through rolling mill roll degradation experiments. Based on the predictions of the MLP model, the optimal timing for remanufacturing rolling mill rolls in the time domain is evaluated using Wiener and update-reward theories. This approach enables the online monitoring and quantitative characterization of the comprehensive degradation of high-speed steel work rolls and facilitates online decision-making regarding the optimal timing for active remanufacturing.
},
 year = {2023}
}

Copy | Download

TY  - JOUR
T1  - Research on the Online Monitoring of the Service Status of Hot-Rolling Mill Work Rolls and Online Decision-Making Method for Active Remanufacturing
AU  - Yuhao Zhang
AU  - Chen Wei
AU  - Xiaoqing Tian
AU  - Shouxu Song
Y1  - 2023/11/17
PY  - 2023
N1  - https://doi.org/10.11648/j.ijimse.20230802.12
DO  - 10.11648/j.ijimse.20230802.12
T2  - International Journal of Industrial and Manufacturing Systems Engineering
JF  - International Journal of Industrial and Manufacturing Systems Engineering
JO  - International Journal of Industrial and Manufacturing Systems Engineering
SP  - 30
EP  - 41
PB  - Science Publishing Group
SN  - 2575-3142
UR  - https://doi.org/10.11648/j.ijimse.20230802.12
AB  - The remanufacturing of rolling mill rolls offers significant economic, environmental, and societal benefits. However, the uncertainty surrounding the performance degradation of retired rolls and its associated timeline poses challenges to the efficiency and cost-effectiveness of roll remanufacturing operations. Therefore, the real-time monitoring of the degradation status of rolling mill rolls is of paramount importance. This study presents an approach that combines multi-sensor data fusion with a multilayer perceptron (MLP) model, which takes into account economic considerations to predict the degradation status of hot-rolling mill work rolls and make online decisions for active remanufacturing. The degradation process of rolling mill rolls is analyzed, and degradation performance indicators are established. Eddy current signals and torque signals from the rolling mill surface are collected during the roll degradation experiments. The friction coefficient and energy of the Hilbert spectrum of the eddy current signal are used as online input features for the MLP model, which is trained using the degradation experiment data. The superiority of the proposed MLP model is validated through rolling mill roll degradation experiments. Based on the predictions of the MLP model, the optimal timing for remanufacturing rolling mill rolls in the time domain is evaluated using Wiener and update-reward theories. This approach enables the online monitoring and quantitative characterization of the comprehensive degradation of high-speed steel work rolls and facilitates online decision-making regarding the optimal timing for active remanufacturing.

VL  - 8
IS  - 2
ER  -

Copy | Download

Author Information

Yuhao Zhang

School of Mechanical Engineering, Hefei University of Technology, Hefei, China

Contact Email
Chen Wei

School of Mechanical Engineering, Hefei University of Technology, Hefei, China

Contact Email
Xiaoqing Tian

School of Mechanical Engineering, Hefei University of Technology, Hefei, China

Contact Email
Shouxu Song

School of Mechanical Engineering, Hefei University of Technology, Hefei, China

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Zhang, Y., Wei, C., Tian, X., Song, S. (2023). Research on the Online Monitoring of the Service Status of Hot-Rolling Mill Work Rolls and Online Decision-Making Method for Active Remanufacturing. International Journal of Industrial and Manufacturing Systems Engineering, 8(2), 30-41. https://doi.org/10.11648/j.ijimse.20230802.12

Copy | Download

ACS Style

Zhang, Y.; Wei, C.; Tian, X.; Song, S. Research on the Online Monitoring of the Service Status of Hot-Rolling Mill Work Rolls and Online Decision-Making Method for Active Remanufacturing. Int. J. Ind. Manuf. Syst. Eng. 2023, 8(2), 30-41. doi: 10.11648/j.ijimse.20230802.12

Copy | Download

AMA Style

Zhang Y, Wei C, Tian X, Song S. Research on the Online Monitoring of the Service Status of Hot-Rolling Mill Work Rolls and Online Decision-Making Method for Active Remanufacturing. Int J Ind Manuf Syst Eng. 2023;8(2):30-41. doi: 10.11648/j.ijimse.20230802.12

Copy | Download

@article{10.11648/j.ijimse.20230802.12,
  author = {Yuhao Zhang and Chen Wei and Xiaoqing Tian and Shouxu Song},
  title = {Research on the Online Monitoring of the Service Status of Hot-Rolling Mill Work Rolls and Online Decision-Making Method for Active Remanufacturing},
  journal = {International Journal of Industrial and Manufacturing Systems Engineering},
  volume = {8},
  number = {2},
  pages = {30-41},
  doi = {10.11648/j.ijimse.20230802.12},
  url = {https://doi.org/10.11648/j.ijimse.20230802.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijimse.20230802.12},
  abstract = {The remanufacturing of rolling mill rolls offers significant economic, environmental, and societal benefits. However, the uncertainty surrounding the performance degradation of retired rolls and its associated timeline poses challenges to the efficiency and cost-effectiveness of roll remanufacturing operations. Therefore, the real-time monitoring of the degradation status of rolling mill rolls is of paramount importance. This study presents an approach that combines multi-sensor data fusion with a multilayer perceptron (MLP) model, which takes into account economic considerations to predict the degradation status of hot-rolling mill work rolls and make online decisions for active remanufacturing. The degradation process of rolling mill rolls is analyzed, and degradation performance indicators are established. Eddy current signals and torque signals from the rolling mill surface are collected during the roll degradation experiments. The friction coefficient and energy of the Hilbert spectrum of the eddy current signal are used as online input features for the MLP model, which is trained using the degradation experiment data. The superiority of the proposed MLP model is validated through rolling mill roll degradation experiments. Based on the predictions of the MLP model, the optimal timing for remanufacturing rolling mill rolls in the time domain is evaluated using Wiener and update-reward theories. This approach enables the online monitoring and quantitative characterization of the comprehensive degradation of high-speed steel work rolls and facilitates online decision-making regarding the optimal timing for active remanufacturing.
},
 year = {2023}
}

Copy | Download

TY  - JOUR
T1  - Research on the Online Monitoring of the Service Status of Hot-Rolling Mill Work Rolls and Online Decision-Making Method for Active Remanufacturing
AU  - Yuhao Zhang
AU  - Chen Wei
AU  - Xiaoqing Tian
AU  - Shouxu Song
Y1  - 2023/11/17
PY  - 2023
N1  - https://doi.org/10.11648/j.ijimse.20230802.12
DO  - 10.11648/j.ijimse.20230802.12
T2  - International Journal of Industrial and Manufacturing Systems Engineering
JF  - International Journal of Industrial and Manufacturing Systems Engineering
JO  - International Journal of Industrial and Manufacturing Systems Engineering
SP  - 30
EP  - 41
PB  - Science Publishing Group
SN  - 2575-3142
UR  - https://doi.org/10.11648/j.ijimse.20230802.12
AB  - The remanufacturing of rolling mill rolls offers significant economic, environmental, and societal benefits. However, the uncertainty surrounding the performance degradation of retired rolls and its associated timeline poses challenges to the efficiency and cost-effectiveness of roll remanufacturing operations. Therefore, the real-time monitoring of the degradation status of rolling mill rolls is of paramount importance. This study presents an approach that combines multi-sensor data fusion with a multilayer perceptron (MLP) model, which takes into account economic considerations to predict the degradation status of hot-rolling mill work rolls and make online decisions for active remanufacturing. The degradation process of rolling mill rolls is analyzed, and degradation performance indicators are established. Eddy current signals and torque signals from the rolling mill surface are collected during the roll degradation experiments. The friction coefficient and energy of the Hilbert spectrum of the eddy current signal are used as online input features for the MLP model, which is trained using the degradation experiment data. The superiority of the proposed MLP model is validated through rolling mill roll degradation experiments. Based on the predictions of the MLP model, the optimal timing for remanufacturing rolling mill rolls in the time domain is evaluated using Wiener and update-reward theories. This approach enables the online monitoring and quantitative characterization of the comprehensive degradation of high-speed steel work rolls and facilitates online decision-making regarding the optimal timing for active remanufacturing.

VL  - 8
IS  - 2
ER  -

Copy | Download