Online grading and piece tracking for continuous casting machines
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Online Grading And Piece Tracking For Continuous Casting Machines - By Rakesh Niranjan
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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.
Transcript of Online grading and piece tracking for continuous casting machines
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.
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.
Grading
Rules
Grading
Rules
Actual Process Signals
Actual Process Signals
Assign Quality level
Assign Quality level
Input
Processing Output
Solution Overview
GradingGrading
Input: Grading Rules & Actual Process Signal
Output: Grading & Assign Quality Levels
Solution Approach: Assign Quality Levels
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.
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
Spray control : reduces deviations in water flow levels and ensures optimal cooling based on specific grade of steel
Grading System : Monitor and track production & inventory system
Key Performance details:Define better pricing strategy based on quality levels achieved during production.SCADASCADA
Data Acquisition SystemData Acquisition System
TrackingTracking GradingGrading Spray ControlSpray Control
Key Performance DetailsKey Performance Details
ProductionProduction QualityQuality ProcessProcess
PLCPLC
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
Production Wastages
Waste Reduction? Tundish Change Optimization End Of Sequence Optimization Strand Stoppage Optimization
Increase In Production Optimization of Steel
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 for casting, quality, strand cutting etc
Informed decision making through improved real time visibility
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