Scholarlink

<p>Hot rolling is an important metallurgical process in which a hot steel slab undergoes thickness reduction by passing through a series of rolls in a hot-strip mill. During hot rolling, the roll at each stand experiences a tremendous amount of force which depends on the hot metal chemistry and process parameters, making their forecasting vital for optimizing the overall operation. In this context, we developed an artificial neural network model to predict these rolling loads in the finishing mill. The network is trained using industrial data with process parameters and chemical composition as inputs, and the rolling loads predicted as outputs. The trained neural network model can predict 80.76 and 97.35&#xa0;pct of rolling loads within ±&#xa0;5 and ±&#xa0;10&#xa0;pct of the corresponding actual rolling loads, respectively. Finally, the model is used to analyze the effect of carbon and major microalloying elements Nb, V, and Ti on the rolling loads.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Predictive Modeling of Rolling Loads in a Hot-Strip Mill Using Artificial Neural Networks

  • 期刊论文

  • 发表日期：

    2025年12月24日

查看全文
  • Abhishek Kumar Thakur,
  • Sanyam Nitin Totade,
  • Ravi Ranjan,
  • Appa Rao Chintha

摘要

Hot rolling is an important metallurgical process in which a hot steel slab undergoes thickness reduction by passing through a series of rolls in a hot-strip mill. During hot rolling, the roll at each stand experiences a tremendous amount of force which depends on the hot metal chemistry and process parameters, making their forecasting vital for optimizing the overall operation. In this context, we developed an artificial neural network model to predict these rolling loads in the finishing mill. The network is trained using industrial data with process parameters and chemical composition as inputs, and the rolling loads predicted as outputs. The trained neural network model can predict 80.76 and 97.35 pct of rolling loads within ± 5 and ± 10 pct of the corresponding actual rolling loads, respectively. Finally, the model is used to analyze the effect of carbon and major microalloying elements Nb, V, and Ti on the rolling loads.