ABB Profile Mill Fingerprint service boosts yield and productivity for top Indian steelmaker

Leading steel producer employs ABB’s performance auditing service to identify and address areas for improvement for the third-party control system at one of its rolling mills

ABB’s Metals team has run its Profile Mill Fingerprint service at a steel mill in Northern India to help the global steel giant tackle operational issues related to mill speed, variation in tail cut length, and the spread of bar alignment in the cooling bed.

A highly skilled team of engineers from ABB was onsite for eight days to ensure the successful completion of the study on the third-party mill control system. With long-term experience and extensive technical know-how, ABB’s engineers got the required logics in the mill’s control system to verify study findings and provide solutions and recommendations to the customer.

“We had conducted the Profile Mill Fingerprint service at another of the customer’s mills, with great results. Leveraging the knowledge gained from that project, ABB’s Metals team quickly identified the pain points in this facility and suggested corrective actions to improve yield and productivity,” said Nilabja Ash, Product Manager, Profile Mills for ABB’s Metals business 

ABB’s Profile Mill Fingerprint, which is a diagnostic service for long product rolling mills, includes a full lifecycle audit of mill equipment to identify areas that require upgrading or modernization. It also conducts a detailed technical study with statistical algorithms to audit various performance parameters. 

The service was implemented for product 25 mm dia rebar at the steel mill to detect and analyze issues affecting performance. The customer was given an in-depth report, which demonstrated gaps and included recommended actions which will facilitate improvements in productivity, quality, yield and mill availability.

Higher yield

One of the issues the customer was experiencing was that variation in tail cut length in C&C (crop and cut) shear was too high, deviating more than 500mm from setpoint. The fingerprint tool revealed that cut signal generation from the third-party control system was inconsistent and a logical modification was performed during the study to rectify this problem.

“The shear now makes consistent tail cuts with a variation of less than 50 mm, and the steel rolling mill is benefitting from higher yield as a result of this adjustment,” noted Nilabja Ash.


Improved productivity

Another issue standing in the way of higher profitability was the spread of bar alignment position, which was too wide with a range of 2.5-3.0 m, for a mill speed of 9.2 m/s. ABB’s study observed that there were issues with handling and distribution of control logics between different controllers. Recommendations were provided to reduce the spread to less than 2 m for the existing control system and mill speed, to allow the customer to unlock higher levels of productivity.


Potential for further optimization

“We were able to provide the customer with a number of suggestions and recommendations for further tests and analyses to help the them better understand the areas and systems of the mill that require improvement or upgrades, which will provide additional opportunities for optimizing mill operations,” remarked Nilabja Ash.

The fingerprint service indicated the potential to increase mill speed from the current 9.2 m/s to 11 m/s for higher yield and optimum productivity. New digital technology solution ABB AbilityTM Data Analytics for long product rolling mills was run to obtain a detailed analysis of various mill parameters, such as pace time, billet temperature, stand performance, loop performance and divide shear performance along with manual analysis of certain problem statements.

Currently, while the mill is running it is the operator who decides when to discharge a billet based on mill light signals and other conditions. The ABB team recommended automation of the furnace discharge process to reduce both standard deviation and average pace time. However, further discussion is required with the customer’s operations team to determine the root causes and define corrective actions.

The fingerprint also found that temperature the variation of 120 ‎°C (from 980 to 1100), which is on the higher side, and the cyclic pattern before and after stoppage, are not desirable. The furnace control philosophy must be checked further to improve mill performance. Additional testing is also suggested for the drive tuning and encoder coupling/mounting for stand 10 and stand 16 for more current oscillation. Even drive tuning for stands 7 and 8 should be checked for higher impact drop.

Settling time and overshoot for all three loopers in the steel mill indicate that the loopers are not tuned aggressively, and a thorough investigation is required for optimization. Overall cut cycle repeatability shows a deviation greater than 50 ms for many billets; a complete study and analysis of the control system and drives control of the mill is suggested.

ABB also offers Performance Optimization Service for long product rolling mills which combines process-specific, AI-based analytics solution with continuous monitoring and expert, remote support helping metals manufacturers to predict and prevent faults and achieve as yet unprecedented levels of yield, quality and productivity in long product rolling.

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