Automated Predicitive Analytics For Steel/Metals Industry
- Analytics & Modeling - Predictive Analytics
- Application Infrastructure & Middleware - Data Exchange & Integration
- Automation & Control - Programmable Logic Controllers (PLC)
- Functional Applications - Enterprise Asset Management Systems (EAM)
- Sensors - Pressure Sensors
- Predictive Maintenance
Asset to be monitored: Wire Compactor that produces Steel Rebar
Customer Faced The Following Challenges:
- Dependent upon machine uptime.
- Pressure cylinders within the compactor fail to control compression and speed causing problems in binding the coil.
- Equipment failure occurs in the final stage of production causing the entire line to stop, can you say bottleneck?
- Critical asset unequipped with sensors to produce data.
About The Customer
A Steel Manufacturing Plant Produces Ponstruction Grade Rebar. 24 Hours a Day, 7 Days a Week, Scrap Metal is Converted into Steel. Each Year the Plant Produces 1.1 Billion Pounds of Steel Rebar Used in Concrete. That’s Enough Rebar to Circle the Glo
- SORBA-SDC (Smart Data Collector) connected to a Siemens PLC, collecting months of time series data to analyze behavior of equipment.
- Eliminated unplanned downtime for critical plant assets.
- Improved asset utilization rates, thus optimizing or reducing CapEx/OpEx costs.
- Minimized cost but not engaging IT personnel to connect into the enterprise network.
- SORBA does not require any firewall ports to open.
- Detected anomalies with lead times up to 20 days. Correlated all potential issues with work order events.
- Achieved an operational savings, in one application, of over $100,000 annually at just one site.
Downtime, Equipment Status, Fault Detection, Machine Performance, Process Procedure
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