Towards Digitalization of Steel Melt shop: A model-based approach

摘要

Tracking of every ladle during the entire ladle-cycle, scheduling of ladle movement and processing in a melt shop are imperative to 1) ensure continuous operation 2) enhance productivity and 3) lower energy consumption. While tracking has recently evolved to digital with certain limitations, scheduling is limited to expertise of the operator and is applicable up to a short horizon. Dependence on operator-expertise further extends to ladle furnace operation where lift temperature fur desired superheat, a complex feature of several parameters, is decided b operator based on heat loss estimation and ladle history. Current work is a step towards digitalization of steel melt shop by minimizing the human involvement in tracking of ladle, scheduling of ladle movement and prediction of lift temperature. A novel technique is introduced for tracking of ladle in melt shop. Based on the ladle tracking and production planning, ladle transport across various units including assignment of appropriate cranes is automated. Finally, a mathematical model is developed to predict the temperature for ladle lifting to ensure desired superheat at caster and has been validated against industrial measurements. With efficient tracking, the visibility of ladles in the melt shop is improved to nearly 100%. With improved scheduling, idle time of ladles and processing units is reduced. Lastly, the numerical thermal model reduces the energy requirements, lowers the idle time and improves casting speed This improves the overall productivity ° of the melt shop. With higher level of automation and model-based decision making, dependence on human expertise is reduced and safety of melt shop is improved.