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Operational performance evaluation based on cloud-edge collaboration for the coking process
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DOI：10.1016/j.conengprac.2026.106857.png)
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Abstract
En 中文
The operational performance of the coking process reflects its energy utilization and production efficiency, and its evaluation is a prerequisite for achieving optimal operation. However, the coking process faces several challenges, including multi-source data integration, reliance on manual performance evaluation, and low efficiency in model deployment. To address these issues, this paper proposes an intelligent evaluation method for coking process operational performance, based on a practical cloud-edge collaborative framework. First, an improved temporal fusion transformer is developed to accurately predict comprehensive production indicators. Then, based on the prediction results, a performance indices system is constructed, and a dual-scale fuzzy performance evaluation mechanism is introduced to assess the operational performance. Finally, a cloud-edge deployment architecture is established, where the cloud layer is responsible for model training and updating, and the edge layer enables accurate prediction and evaluation. The proposed method is validated on real industrial data, demonstrating its effectiveness and accuracy, and providing strong support for subsequent optimization and control.
Keywords:
coking process
cloud-edge collaboration
performance evaluation
temporal fusion transformer
fuzzy evaluation
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