The mathematical model for carbon steel pickling helps to maximize the overall production efficiency and throughput with assuring the required product quality also in cases of varying material properties and process conditions.
The model is based on a real-time chemical optimization that directly controls the process state and acid concentrations in fully autonomous way.
End user
• Automation engineer
• Control engineer
• Maintenance engineer
• Maintenance manager
• Maintenance technician
• Operator (Control room)
• Operator (Field)
• Plant manager
• Process engineer
• Production manager
Benefits
Digital Capability• Analytic Modeling
• Data Integration
Operating Costs• Maximize energy production
• Maximize reuse of raw materials
• Minimize chemicals usage
• Minimize energy usage
• Minimize fuel usage
• Minimize raw materials
• Minimize total cost of ownership (TCO)
Production• Faster startup or setup/grade changes
• Maximize Maximum Sustainable Rate (MSR)
• Maximize process availability
• Maximize process stability
• Maximize production uptime
• Minimize production disturbances
• Set production closer to constraints
Productivity• Cross-functional collaboration
• Enable mobile worker efficiency
• Maintains technical expertise and knowledge
• Maximize engagement and productivity of personnel
• Maximize field visibility
• Maximize human effectiveness
• Maximize response and better decision-making
• Reliable remote startup
• Standardize enterprise best practices
Quality• Drive consistency in product manufacturing
• Maximize product quality
• Minimize cost with desired quality
• Minimize process variability
• Minimize quality losses
• Minimize start-up losses
Security
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Plant Lifecycle Management
• Commissioning
• Design
• Improve/Modify
• Install
• Learning curve
• Maintain
• Operate
• Shutdown
Group
Advanced Process Control
Industries
• Metals
