The Pipeline System optimization Application more accurately predicts the demand water volume compared to current expert systems. It supplies this data to operators to enable them to make the best decision even during busy schedules. This allows mines to implement the most energy efficient pumping schedule on a continuous basis.
The Pipeline System optimization Application integrates directly with existing data historian systems. Virtual Flow Sensors are generated using an asset specific library of mathematical models to determine missing engineering parameters in real time. This data is assimilated into a data lake that enables a complete understanding of the Pipeline System in real time.
The Pipeline System Optimization Application algorithm simulates pipeline operation in real time. By modelling the finite combination of pump station configurations against the Target Flow Rate, an optimized pumping schedule can be generated to deliver the required water through the pipeline.
Engineers can test various operational scenarios for training purposes in a process simulation environment. This is enabled through the creation of a digital twin to create a safe environment for testing which accurately replicates the variables present in the live operational process. This can also be done remotely through the creation of an IntelliSense.io ROC (Remote Operations Center).
The brains.app optimization engine uses Machine Learning techniques to balance operational and financial optimization by proactively providing control variables required for continuous optimization. Pipeline stability and optimization is delivered via the implementation of an Optimised Pump on/off schedule. The Dynamic Pumping Schedule is delivered directly into the SCADA control system and supports the Operator by continuously implementing the most energy efficient pumping schedule.
- Reduced fresh water consumption
- Reduced energy consumption with up to 50% less pump switches
- Lower maintenance costs
- Pipeline stability
- Optimised system performance during high variable flow demand (Summer Months) and low variability (Winter Months)
- Increase pump life expectancy by reducing the number of pumps switches
- Reduce risk of tanks being overfilled or emptying