AMI Automation will participate at the Electric Steelmaking Webinar organized by SteelTimes International, September 8, 2022, 14:00 (GMT).

About one-quarter of the world’s steel today is produced by the electric-arc method, which uses high-current electric arcs to melt steel scrap and convert it into liquid steel of a specified chemical composition and temperature. Join us for a breakdown of the operational challenges, processes, and innovations of the most sustainable method to produce steel.

The webinar will talk about:

• How artificial intelligence enhances electric steelmaking.
• Optimization strategies.
• Scrap melting.
• Charged material.

Learn more about how our technology can help improve your process efficiency and safety at the Electric Steelmaking Webinar where Jesus Andrade will be presenting the Off Gas Technology for EAF Operations.

Jesus Andrade is a chemical engineer with a master degree in materials science and sensors Systems. He began his career as a process engineer at AMI Automation, taking part in Electric Arc Furnace optimization projects in North America, Europe, and Asia. He has also taken full time roles in the steel industry in USA and Mexico. His abilities include material and energy balance modelling, and real time estimation of steel conditions and slag optimization. As a subscription leader, he coordinates the AMI optimization group efforts to identify the areas of opportunity in the melt shop, both in terms of safety and performance.

We invite you to see our technical presentation:

Off Gas Technology for EAF Operations presented by Jesús Andrade, AMI Automation, September 8 at 14:00 PM (GMT).

Abstract: Since the introduction of Off Gas analysis instrumentation in the Electric Arc Furnace, different applications have been developed using this information to improve the process efficiency and safety.

Using the CO, CO2, temperature, and flow of the of gas, the AMI SmartFurnaceTM modules for Chemical Energy optimization calculates the optimal setpoints of the EAF burners and lances. The chemical energy modules are complemented dynamic process models and algorithms for electrical energy providing an integral furnace control of the Oxygen, Natural Gas and Carbon Injection, as well as continuous raw material feeding.

Using artificial intelligence, the Abnormal Water Vapor Detection module uses the gas temperature, flow, and water vapor content to identify unexpected sources of water in the off gas which could pose a potential safety hazard, distinguishing it from the normal amount of water present in the furnace environment.

Finally, the efforts to reduce emissions in the steel industry require accurate and reliable measurement of CO2. Understanding the influence of different conditions such as raw materials, melting profiles and practices, plays a major role in defining strategies to lower the environmental impact of the production.
The latest implementations of this technology in plants with a wide range of raw materials, EAF mechanical characteristics and production needs are described in this paper, and the achieved results.

For more information please visit: Electric Steelmaking Webinar (adobeconnect.com)