Online grading and piece tracking for continuous casting machines

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Information about Online grading and piece tracking for continuous casting machines

Published on November 20, 2013

Author: rakeshniranjan



There’s an adage which says “Even the best can be bettered.” It perfectly applies to Continuous casting. Industry leaders always work on this concept of “there is a better way” and don’t settle for less. One of the thought processes is how to get more from the investments on continuous casters by optimization of the operations. This thought process is vital in the current tough market conditions. Evolution of manufacturing processes through perfect application of technology provides the right platform to optimized manufacturing operations. Steel manufacturers consistently focus on to attend high quality of the yield and reduce scrap. This article contains the overview of all the processes involved to get more from your caster.

Online Grading And Piece Tracking For Continuous Casting Machines - By Rakesh Niranjan

Let’s Think …

Challenges Know the quality levels of grade while casting on real-time? How do we obtain and improve higher quality levels of steel grade Bring corrective actions that enables continuous improvements of quality levels ? How do we leverage existing investments to gain more production & reduce wastage ?

Solution Approach A real time probabilistic system that does grading by identifying and segregating different quality levels while casting. Input Grading Solution Overview Processing Output Rules Grading Actual Process Signals Assign Quality level Enables optimization of production by reducing wastage Best processes are defined from the knowhow of the steel casting process and any deviation while casting is recorded Indentifies defects and takes corrective actions to achieve better quality of steel.

Solution Approach: Assign Quality Levels Input: Grading Rules & Actual Process Signal Provides standard set points for categorizing quality, which can be customized for the different customers and grades. Process signals like • • • • • • • Liquid metal temperature (especially the superheat value) Level of liquid steel in the mould Quality of electromagnetic stirring Casting speed Tundish weight Tundish temperature Spray cooling act as inputs for grading system. Output: Grading & Assign Quality Levels Process signals are weighed against the predefined rules System identifies the quality level Provides opportunity to take corrective actions for upgrading the quality of bloom/billet/slab Resulting in higher price of the yield

Implementation Layers Key Performance Details Production Quality Process Spray control : reduces deviations in water flow levels and ensures optimal cooling based on specific grade of steel Grading System : Tracking Grading Spray Control Data Acquisition System SCADA PLC Monitor and track inventory system production Key Performance details: Define better pricing strategy based on quality levels achieved during production. &

Identification and segregation quality levels Quality level of each bloom produced can be segregated as • 1st Best • 2nd best • 3rd best and so on based on event generation Identify process deviations of process for specific affected areas in blooms / billets / Slabs

Optimization Increase In Production Optimization of Steel Waste Change Optimization  Tundish Reduction?  End Of Sequence Optimization  Strand Stoppage Optimization Production Wastages

Deployment Architecture

Solution Benefits Increased price realization by knowing & improving quality levels of grade Higher profitability by reducing scrap Advanced spray cooling system to avoid sudden changes in the strand thermal history resulting in more consistently better quality of steel and reduce incidents of surface defects and cracks Customer specific configurations casting, quality, strand cutting etc for Informed decision making through improved real time visibility

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