Enhancing the efficiency of a gas-fueled reheating furnace of the steelmaking industry: assessment and improvement

João Eduardo Sampaio Brasil, F. Piran, D. P. Lacerda, M. I. Morandi, Debora Oliveira da Silva, M. Sellitto
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Abstract

PurposeThe purpose of this study is to evaluate the efficiency of a Brazilian steelmaking company’s reheating process of the hot rolling mill.Design/methodology/approachThe research method is a quantitative modeling. The main research techniques are data envelopment analysis, TOBIT regression and simulation supported by artificial neural networks. The model’s input and output variables consist of the average billet weight, number of billets processed in a batch, gas consumption, thermal efficiency, backlog and production yield within a specific period. The analysis spans 20 months.FindingsThe key findings include an average current efficiency of 81%, identification of influential variables (average billet weight, billet count and gas consumption) and simulated analysis. Among the simulated scenarios, the most promising achieved an average efficiency of 95% through increased equipment availability and billet size.Practical implicationsAdditional favorable simulated scenarios entail the utilization of higher pre-reheating temperatures for cold billets, representing a large amount of savings in gas consumption and a reduction in CO2 emissions.Originality/valueThis study’s primary innovation lies in providing steelmaking practitioners with a systematic approach to evaluating and enhancing the efficiency of reheating processes.
提高炼钢业气体燃料再加热炉的效率:评估与改进
本研究的目的是评估巴西一家炼钢公司热轧厂再加热工艺的效率。主要研究技术包括数据包络分析、TOBIT 回归和人工神经网络支持的模拟。模型的输入和输出变量包括坯料平均重量、批量加工的坯料数量、耗气量、热效率、积压量和特定时期内的产量。分析时间跨度为 20 个月。主要结论包括当前平均效率为 81%,确定了影响变量(钢坯平均重量、钢坯数量和气体消耗量)并进行了模拟分析。在模拟方案中,最有前景的方案通过提高设备利用率和钢坯尺寸,实现了 95% 的平均效率。原创性/价值这项研究的主要创新点在于为炼钢从业人员提供了评估和提高再加热工艺效率的系统方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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