• Is producing different pellet types with the customized properties needed for your iron and steelmaking processes having a negative effect on plant efficiency?

 

• Are your operators manually changing the rotation speed and ore load after visual analysis of pellet agglomeration?

 

• Are you observing variations in pellet properties due to insufficient drying or as a result of firing zone temperature fluctuations?

 

• Are you looking to reduce your plant's environmental impact?

 

By their nature ore grinding, pellet drying and firing processes are very complex  and have always been dependent on operator expertise. By combining plant models and operator experience with carefully selected and calibrated sensor data and estimated system state, Advanced Process Control (APC) systems are able to determine the current state of the process, predict system behavior some steps into the future, and decide how it should be adjusted to deliver the desired operating conditions.  It allows faster and more accurate action in response to changes in production, to directly impact on pellet quality and output, fuel, electricity and refractory consumption.

While APC systems have been proven to work very well since 1980's, their use was for some time limited to a minority of applications, where plants were big enough and similar enough to get a return on the enormous development effort and cost required to implement them. However, the new generation of intelligent automation, advanced analytics and AI technologies work in a fundamentally different way from previous technologies, elevating APC and process performance at a fraction of its cost and complexity.

See also: Advanced Process Control of steam generation via energy recovery from byproduct gas usage eg, blast furnace gas for a steel manufacturing plant. APC enables higher level of automation and optimization of steam power, as energy and fuel recovery is subject to upstream unit’s availability and cycles

As APC technology continues to evolve with new components and features, ABB scientists and engineers are exploring the potential of artificial intelligence (AI) with the use of reinforcement learning neural networks as well as edge and cloud technologies for digital analytics and optimization.

Model predictive control (MPC) is a well-established technology for Advanced Process Control (APC) in many industrial applications like mills, kilns and burners, outperforming classical control schemes. Advanced controllers and analytic models used for monitoring, predictive analytics and closed-loop control optimize operations in real-time and make predictions and estimations even in absence of reliable measurements.

Why ABB?

• Experienced provider OT and IT stack
• Third party and legacy integration
• Domain knowledge and metals industry knowledge
• Efficient transformation projects, focus on ROI
• New tools such as cloud, analytics
• Development model with partners to jointly develop solutions

>> ABB references in metals industry