SentientSystem® (by Synengco) is a sophisticated software platform which supports asset decision-making. Based on theoretical, empirical and operational data, it provides a digital replica of your complex systems, thus enabling optimisation of your assets over their whole life cycle.
Model
SentientSystem® starts by creating a detailed digital twin of your complex systems. It uses real operational data from your assets to automatically tune the copy and to accurately represent the original system’s behaviour.
For SentientSystem, the model is the digital representation of the real operation. It is the interface between the real world, where value is generated and the digital world, where management takes place.
Two of the key interface points are:
- Measurement sensor points: measurement of real world assets and translated to a digital representation
- Control points: control actions from the digital representation to the real world (human actions and process control actions)
The model explicitly aligns the domains between the real world and the digital world. It does so through a common information model, common units of measure and control actions.
Monitor
SentientSystem® connects to your devices and sensors to collect operational data. It use a variety of analysis techniques to keep an eye on the performance of assets and derive extra information about the current operation.
The ultimate model of something is the actual thing.
By having a good performance monitoring system that provided detail of performance at the component level as well as the impact at a system level provides a common means of evaluating scenarios in the digital world as well as the real world.
This allows optimisation to be carried out using a digital replica of an operation or the actual operation.
Predict
With some fundamental knowledge and historical data about operations, SentientSystem® predicts how systems and assets will perform under different circumstances, raising alerts when potential issues emerge.
Predictions are used to encapsulate and reconcile available knowledge and experience. Predictions are continuously monitored against actual measures associated with the prediction to trigger corrective actions
- The actual operation has changed from the best available knowledge and experience suggesting a potential treat or opportunity within the real operation.
- The prediction does not accurately represent the way the actual operation behaves suggesting and potential threat or opportunity to improve the encapsulated knowledge and experience within the model
Optimise
Your systems are optimised following a set of instructions that aims to efficiently manage your assets, based on previous performance, external factors, model scenario and advanced analysis techniques.
Once there is an accurate digital replication of an operation’s behaviour, it can be used to find opportunities to improve. This can be done at:
- An operations level: What if I changed this operational setting or set-up?
- An asset level: What if I changed the behaviour of this asset through maintaining, repairing, refurbishing, replacing or renewing with new technology for the asset?
- A system level: What if I changed the configuration of my system?
