Multi-working condition performance assessment based on knowledge extraction of optimal operating states for continuous annealing processes

Performance assessment is a key to strip quality improvement and energy consumption reduction of Continuous Annealing Processes (CAP). However, existing methods focus on performing the assessment under a single working condition, and the assessment accuracy must be improved. This study proposes a ne...

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Bibliographic Details
Published in:International journal of systems science 2024-04, Vol.55 (5), p.894-908
Main Authors: He, Jiang, Cao, Weihua, Hu, Wenkai, Song, Wenshuo, Wu, Min
Format: Article
Language:English
Subjects:
benchmark library
Continuous annealing
Continuous annealing process
Data integration
Energy consumption
key parameter selection
multiple working conditions
Performance assessment
Performance evaluation
Reduction
Strip
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Summary:Performance assessment is a key to strip quality improvement and energy consumption reduction of Continuous Annealing Processes (CAP). However, existing methods focus on performing the assessment under a single working condition, and the assessment accuracy must be improved. This study proposes a new multi-working-condition performance assessment method based on the knowledge extraction of the optimal operating states for CAP. First, a mechanism-data fusion-based assessment index construction method is proposed for the key parameter selection. Second, a knowledge extraction strategy for the optimal operating states under multiple working conditions is proposed to construct a benchmark library. Third, a knowledge-enhanced assessment model is built to achieve qualitative performance evaluation and quantitative non-optimal traceability. The experiment based on the process data shows the effectiveness of assessing the operating performance, providing decision guidance for strip quality improvement and energy consumption reduction.
ISSN:0020-7721
1464-5319
DOI:10.1080/00207721.2023.2300718