Energy-Based Prognosis of the Remaining Useful Life of the Coating Segments in Hot Rolling Mill
The field of prognostic maintenance aims at predicting the remaining time for a system or component to continue being used under the desired performance. This time is usually named as Remaining Useful Life (RUL). The current study proposes a novel approach for the RUL estimation of coating segments...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-09-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/19/6827 |
| _version_ | 1827705167150055424 |
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| author | Ioannis Anagiannis Nikolaos Nikolakis Kosmas Alexopoulos |
| author_facet | Ioannis Anagiannis Nikolaos Nikolakis Kosmas Alexopoulos |
| author_sort | Ioannis Anagiannis |
| collection | DOAJ |
| description | The field of prognostic maintenance aims at predicting the remaining time for a system or component to continue being used under the desired performance. This time is usually named as Remaining Useful Life (RUL). The current study proposes a novel approach for the RUL estimation of coating segments placed on a hot rolling mill machine. A prediction method was developed, providing real-time updates of the RUL prediction during the rolling milling process. The proposed approach performs energy analysis on measurements of segment surface temperatures and hydraulic forces. It uses nonparametric statistical processes to update the predictions, within a prediction horizon/window, indicating the number of remaining products to be processed. To assess the probability of failure within the defined prediction window, Maximum Likelihood Estimation is used. The proposed methodology was implemented in a software prototype in the MATLAB environment and tested in an industrial use case coming from a steel parts manufacturer, facilitating testing and validation of the suggested approach. Real-world data were acquired from the operational machine, while the validation results support that the proposed methodology demonstrates reasonable performance and robustness against product type variations. |
| first_indexed | 2024-03-10T15:58:25Z |
| format | Article |
| id | doaj.art-019df536492149459a2e9a71738e6a71 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T15:58:25Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-019df536492149459a2e9a71738e6a712023-11-20T15:28:27ZengMDPI AGApplied Sciences2076-34172020-09-011019682710.3390/app10196827Energy-Based Prognosis of the Remaining Useful Life of the Coating Segments in Hot Rolling MillIoannis Anagiannis0Nikolaos Nikolakis1Kosmas Alexopoulos2Laboratory for Manufacturing Systems and Automation, Department of Mechanical Engineering and Aeronautics, University of Patras, 26504 Patras, GreeceLaboratory for Manufacturing Systems and Automation, Department of Mechanical Engineering and Aeronautics, University of Patras, 26504 Patras, GreeceLaboratory for Manufacturing Systems and Automation, Department of Mechanical Engineering and Aeronautics, University of Patras, 26504 Patras, GreeceThe field of prognostic maintenance aims at predicting the remaining time for a system or component to continue being used under the desired performance. This time is usually named as Remaining Useful Life (RUL). The current study proposes a novel approach for the RUL estimation of coating segments placed on a hot rolling mill machine. A prediction method was developed, providing real-time updates of the RUL prediction during the rolling milling process. The proposed approach performs energy analysis on measurements of segment surface temperatures and hydraulic forces. It uses nonparametric statistical processes to update the predictions, within a prediction horizon/window, indicating the number of remaining products to be processed. To assess the probability of failure within the defined prediction window, Maximum Likelihood Estimation is used. The proposed methodology was implemented in a software prototype in the MATLAB environment and tested in an industrial use case coming from a steel parts manufacturer, facilitating testing and validation of the suggested approach. Real-world data were acquired from the operational machine, while the validation results support that the proposed methodology demonstrates reasonable performance and robustness against product type variations.https://www.mdpi.com/2076-3417/10/19/6827cyber–physical systemsdata analysisenergy analysishot rolling millpredictive maintenanceRemaining Useful Life |
| spellingShingle | Ioannis Anagiannis Nikolaos Nikolakis Kosmas Alexopoulos Energy-Based Prognosis of the Remaining Useful Life of the Coating Segments in Hot Rolling Mill Applied Sciences cyber–physical systems data analysis energy analysis hot rolling mill predictive maintenance Remaining Useful Life |
| title | Energy-Based Prognosis of the Remaining Useful Life of the Coating Segments in Hot Rolling Mill |
| title_full | Energy-Based Prognosis of the Remaining Useful Life of the Coating Segments in Hot Rolling Mill |
| title_fullStr | Energy-Based Prognosis of the Remaining Useful Life of the Coating Segments in Hot Rolling Mill |
| title_full_unstemmed | Energy-Based Prognosis of the Remaining Useful Life of the Coating Segments in Hot Rolling Mill |
| title_short | Energy-Based Prognosis of the Remaining Useful Life of the Coating Segments in Hot Rolling Mill |
| title_sort | energy based prognosis of the remaining useful life of the coating segments in hot rolling mill |
| topic | cyber–physical systems data analysis energy analysis hot rolling mill predictive maintenance Remaining Useful Life |
| url | https://www.mdpi.com/2076-3417/10/19/6827 |
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