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Optimizing Steel Production with IoT: A Case Study of BlueScope Steel Limited
Technology Category
- Sensors - Air Pollution Sensors
- Sensors - Environmental Sensors
Applicable Industries
- Metals
Use Cases
- Time Sensitive Networking
The Challenge
BlueScope Steel Limited, a division in New Zealand, produces 650,000 tons of steel annually from locally sourced iron sand and coal. A crucial part of this process involves the direct reduction of iron sand by char in four rotary kilns. These kilns, large structures with 65 meter-long revolving cylinders, are used to remove oxygen from iron sand to produce a partially reduced material containing the correct amount of carbon for feeding into downstream melters. However, the company faced challenges in understanding the flow patterns, temperature, and concentration contours inside these kilns. Accretion layers or rings, derived mainly from impurities, occasionally form on the inner face of the kiln shell, limiting the production rate. The company needed a solution to this complex problem involving highly turbulent flows, chemical reactions, heat transfer, and a very large geometry in a reasonable time. They also needed to test a range of operating conditions and geometries efficiently.
About The Customer
BlueScope Steel Limited is a steel production company operating a division in New Zealand. The company produces 650,000 tons of steel per year from locally sourced iron sand and coal. A key component of their production process involves the direct reduction of iron sand by char in four rotary kilns. These kilns are large structures, about 4.2 meters in diameter with 65 meter-long revolving cylinders. The primary function of the kilns is to remove oxygen from iron sand to produce a partially reduced material containing the correct amount of carbon for feeding into downstream melters. The reduction process requires energy which is supplied by the combustion of carbon monoxide and char.
The Solution
BlueScope Steel Limited turned to ANSYS CFX and ANSYS DesignModeler software to provide a solution to their challenges. These software solutions were run on a 64-bit workstation to carry out the computations. The solution showed good stability and converged in less than 200 iterations. The computational fluid dynamics (CFD) results were qualitatively validated against available experimental data. The flexibility of both software packages allowed for quick implementation of changes in geometry and/or operating conditions. This provided full details of the predicted temperature, velocity, and concentration contours throughout the kiln in a relatively short time frame. The effects of air flow rates and other operating parameters were also examined readily, contributing to a better understanding of kiln operation and optimization of plant production.
Operational Impact
Quantitative Benefit
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