Case Study: Embracing advanced modelling techniques for furnace optimisation

 

 

 

 

 

The Novelis plant at Rogerstone in South Wales produces hot mill coil, paintstock and foilstock and flat sheet. Material from here is supplied to their other European operations, and direct to third party external customers for further processing.

Novelis Rogerstone enlisted the help of Dr. Chris Davenport to drive more production through their pre-heat furnaces, and at the same time reduce energy losses per kg of metal processed. Chris is Innoval Technology's expert in thermal modelling, and he has considerable industrial experience.

The team at Rogerstone wished to optimise their furnace practices to ensure they were making the best use of their pre-heat furnaces. In response to this, Chris created thermal and energy models of the furnaces which would enable the cycles to be reduced in length without risking the quality of the product. The models accurately predict the temperature at any point throughout the ingot, enabling a more rapid heat-up to be used which doesn't melt any part of the ingot. The models also make sure the ingot is not soaked for any longer than required - it's almost like having temperature probes everywhere in the ingot throughout the heating cycle. The models are carefully calibrated against plant data and are therefore accurate enough to remove the need for unduly conservative heating cycles. They drive the process to its limit, making it extremely efficient. Furthermore, due to minimised heat loss from reduced cycle times, the energy used per kg of ingot is reduced.

Chris estimates that models such as the one employed at Novelis, Rogerstone, can give a reduction in cycle time of up to 25%, together with a 10% reduction in energy usage.

Commenting on this project, John Evans, Hot Line Manager at Rogerstone, says:

Innoval Technology's expertise in the area of thermal modelling is well-known, so we knew they were the right people to help us get more throughput from our furnaces. The model they have generated should help us to optimise our rolling process, and we are looking to use it to increase production through our hot line without any compromise in product quality.

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This case study appears as an article in the 2007 edition of 'innform'; the newsletter of Innoval Technology.

 

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