In the most of steelmaking plant, the steelmaking operation in converter still depend on the artificial experience mode, the artificial experience are different from each other, so that the accurate of [C] and [T] hit rate are not high at the endpoint, and the reboiling rate is generally more than 30%, which cause the steel liquid peroxided, the consumption increasing and taping to taping time...
Abstract
The proposed study aims to reduce the analysis time for on-site liquid steel characterization, facilitating quicker adjustments in scrap use to enhance steel production efficiency. Reducing the overall analysis time enables steelmakers to better control the primary steelmaking process.
The direct analysis (DA) approach focuses on developing an optimized sampler geometry...
Although EAF-based steelworks produce steel from recycled ferrous scrap and inherently implement the concept of circularity, they are challenged to reduce their overall environmental impact and take actions to reduce CO2 emissions and maximize energy and resource efficiency. Advanced digital technologies, including artificial intelligence-based techniques, can significantly contribute to...
The steel industry is undergoing a transformative phase driven by digital and green transitions, known as the Twin Transition. Automation solutions are a core of the Twin Transition, seamlessly integrating digital innovations to enhance efficiency and precision while enabling sustainable practices that reduce emissions, optimize resource use, and drive decarbonization in industrial operations....
The number of deformed steel bars is checked visually by human at the end of each product in each bundle. For this reason, in the case of thin-diameter product bundles in which the number of products in one bundle is large, not only is the burden on workers high, but the time required for the work also leads to a decline in shipping efficiency.
This time, by utilizing this technology and...
Continuous casting is often hindered by the clogging of submerged entry nozzles (SEN), caused due to the agglomeration of non-metallic inclusions (NMIs). SEN clogging is challenging to monitor and requires probabilistic models for online predictions of ‘castability’. In this context, data-driven models emerged as a promising tool to be used in the existing industrial settings. Despite the...
The steel industry is a major contributor to global greenhouse gas emissions. As the world transitions to a low-carbon economy, the steel sector faces increasing pressure to reduce its environmental impact.
In this presentation, we will explore how process digital twins, powered by advanced modelling and simulation tools, can be leveraged throughout the steel manufacturing lifecycle to...
The mold level fluctuation plays an important role in controlling the quality of the slab. Abnormal fluctuations can easily increase the frequency of entrainment slag, directly affecting the proportion of defects in hot-rolled and cold-rolled steel sheets. In addition, it will affect the uniform growth of the shell of hypo-peritectic steel and raise the incidence of center segregation and...
Process optimization in industries, particularly steel, is a fundamental priority for enhancing productivity and reducing costs. In this study, an advanced system for the identification and localization of molten material transfer ladles has been designed and implemented using image processing and deep learning technologies. By integrating into various levels of process control (Level 2 and...
