15^th December 2023

PMAI – 5^th Skill Development Programme on Iron Ore Pelletizing

Digital Modelling for Process Control in Pelletizing

Meghna Mondal, Process Technology

Sristy Raj, Process Technology

Slide

Tata Steel

Process Technology

Pellet CCS Anomaly Detection �

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40% of the time in the last ~ 1 year, Pellet CCS was below 200 kg/pellet, which requires root cause analysis.

How it works

Slide

Tata Steel

Process Technology

Autoencoder usage as anomaly detection tool - Methodology��

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Tata Steel

Process Technology

A glimpse of Pellet CCS Dashboard�

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Slide

Tata Steel

Process Technology

Insightful Summary�

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As per the tool, the following parameters have an impact on pellet CCS

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• Low temperature in the Windboxes of the Preheating Zone

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• Low temperature of Cooling Zone#2 Hood

Slide

Tata Steel

Process Technology

Temperature Profile in the Induration furnace�

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The temperature profile of the Induration furnace illustrates the following

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• Low temperature of Preheating zone burners

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• Low temperature of the initial Firing Zone burners

Slide

Tata Steel

Process Technology

Benefits derived from the tool�

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• This tool narrows down the search for the root cause parameters and minimizes the time for the operator to initiate action to restore the process

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• This tool provides flexibility to select the time period for comparison of pellet quality (weekly, monthly or other custom selected duration) as per the requirement of the user, providing valuable insights to the process condition

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Way Forward�

• Clustering of alerts to find out the similar anomaly in past, so that we can highlight the actions taken in past, leading to quick restoration of pellet quality

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• Taking the theme to other processes like pellet return fines

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Slide

Tata Steel

Process Technology

Schematic of Induration Machine�

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Slide

Tata Steel

Process Technology