Intelligent evaluation and operation recommendation system of sintering process based on analytic hierarchy process–entropy weight method–technique for order preference by similarity to an ideal solution (AHP–EWM–TOPSIS)

Fluctuations in the sintering process have a significant impact on the overall performance and outcomes of sintering production. It is crucial to gain a comprehensive understanding of the sintering operation in a timely manner in order to minimise process fluctuations and ensure the stability of sinter production. In this paper, a sintering process evaluation model is presented, which is based on the analytic hierarchy process–entropy weight method–technique for order preference by similarity to an ideal solution (AHP–EWM–TOPSIS) and is constructed using data from a steel plant sintering production process. Firstly, the evaluation indices input to the system are selected by combining the principle of the sintering process and actual production requirements. The subjective and objective weights of the indices are then calculated using the AHP–EWM method, and the weights are combined through the principle of minimum discriminatory information to construct the set of weighted indices. Subsequently, the sintering process was evaluated by the TOPSIS model, and the results of this evaluation were compared with the actual fluctuation situation at the sintering site. This was done by combining the model results with the differential level method. It was found that the model can accurately reflect the fluctuation situation that occurs in the sintering process. Furthermore, the comprehensive matching rate reached 95.42%, which demonstrates that the model is capable of accurately evaluating the operation of the sintering process. The statistical analysis of historical data provides a basis for the optimised operation of the sintering production process by summarising the optimal range of each parameter when the sintering operates efficiently. Ultimately, a sintering process evaluation system is constructed through the use of computer technology, thereby facilitating the transformation of sintering production into an intelligent system. The model is capable of rapidly ascertaining the actual status of the sintering process in real time. The established system is designed to facilitate the optimisation of sintering production operations and to promote long-term stability in sintering.

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Publication Details

Journal
Ironmaking & Steelmaking Processes Products and Applications
Published
2024-12-10
DOI
https://doi.org/10.1177/03019233241298180
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
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article

Intelligent evaluation and operation recommendation system of sintering process based on analytic hierarchy process–entropy weight method–technique for order preference by similarity to an ideal solution (AHP–EWM–TOPSIS)

Hongyang Li, Qing Lv, Yifan Duan, Yifan Li et al.
Ironmaking & Steelmaking Processes Products and Applications
Manufacturing Process and Optimization
article

Intelligent evaluation and operation recommendation system of sintering process based on analytic hierarchy process–entropy weight method–technique for order preference by similarity to an ideal solution (AHP–EWM–TOPSIS)

Hongyang Li, Qing Lv, Yifan Duan, Yifan Li, Xin Li, Hongwei Li, Z. Yujie, Liu Xiaojie
article en

Abstract

Fluctuations in the sintering process have a significant impact on the overall performance and outcomes of sintering production. It is crucial to gain a comprehensive understanding of the sintering operation in a timely manner in order to minimise process fluctuations and ensure the stability of sinter production. In this paper, a sintering process evaluation model is presented, which is based on the analytic hierarchy process–entropy weight method–technique for order preference by similarity to an ideal solution (AHP–EWM–TOPSIS) and is constructed using data from a steel plant sintering production process. Firstly, the evaluation indices input to the system are selected by combining the principle of the sintering process and actual production requirements. The subjective and objective weights of the indices are then calculated using the AHP–EWM method, and the weights are combined through the principle of minimum discriminatory information to construct the set of weighted indices. Subsequently, the sintering process was evaluated by the TOPSIS model, and the results of this evaluation were compared with the actual fluctuation situation at the sintering site. This was done by combining the model results with the differential level method. It was found that the model can accurately reflect the fluctuation situation that occurs in the sintering process. Furthermore, the comprehensive matching rate reached 95.42%, which demonstrates that the model is capable of accurately evaluating the operation of the sintering process. The statistical analysis of historical data provides a basis for the optimised operation of the sintering production process by summarising the optimal range of each parameter when the sintering operates efficiently. Ultimately, a sintering process evaluation system is constructed through the use of computer technology, thereby facilitating the transformation of sintering production into an intelligent system. The model is capable of rapidly ascertaining the actual status of the sintering process in real time. The established system is designed to facilitate the optimisation of sintering production operations and to promote long-term stability in sintering.

Ironmaking & Steelmaking Processes Products and Applications
North China University of Science and Technology (CN)
Reduced inequalities, Peace, Justice and strong institutions
Openalex Percentile: Top 68%
Manufacturing Process and Optimization
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