Real Time Data Source Integration
brains.app starts by providing real time automated assimilation of multiple existing data sources and software. These data sources cover the geological, mining and processing information required to generate the variables used in the rest of the platform.
Data Assimilation and Data Quality
The data is organised into a connected virtual asset/metric structure. In this structure; data of varying resolution is filtered both practically and statistically through the IntelliSense.io Data Quality Model.
The feed variables required for the digital process model come from four unique models:
Digital Asset Library and Virtual Sensors
A Virtual Sensor is a real time model output based on both dynamic and static inputs. They are used in operational decision making, automated control and both machine learning and empirical simulation based prediction models.
The Virtual Sensor is processed in the cloud, allowing it to be constantly re-trained and re-calibrated. The accuracy and robustness of the outputs are cross verified using equivalent outputs of parallel models. The Virtual Sensor suite is asset specific and replaces expensive instrumentation capital costs.
The Intellisese.io Financial Model accurately calculates and, when paired with the Digital Process Model, predicts asset based operating unit costs in real time using dynamic financial variables.
Asset Performance Management
Specific digital assets are pre-loaded with a configurable Design-Installation-Point of Failure-Failure Curve (DIPF Curve) which is used in Asset Maintenance. The brains.app platform assesses where on the curve the asset lies in real time.
Material Transport and Influence Models
This combination of models accurately track and predict the geometallurgical and physical properties of the material in real time. These models use a system-wide dynamic mass balance. The brains.app platform predicts the exact properties of the material entering the process and exactly how it will affect that process; operators have adequate time to make proactive changes to maximise throughput.
The data generated across the digital mine and plant can be reconciled back into a dynamic geological block model. This dynamic model can be used in enhanced re-optimisation of medium and long-term planning to increase confidence of delivering asset value. From this holistic view, brains.app will provide a set of system-level recommendations to both mine and plant.
Reporting and Alerts
All of the data generated through the digital mine and plant can be manipulated using custom dashboards and report subscriptions. This gives the user one platform to view traditionally individually siloed data.
Any data, including the virtual sensors and financial model outputs, can be downloaded in raw csv form. The platform provides configurable push notifications to alert users once reports are ready.