Our Industrial AI applications include Maintenance Digital Twin and Performance Digital Twin.
Maintenance Digital Twin provides insights into Maintenance and Repairs Operations (MRO) for high-value industrial assets starting from failures (reliability) through maintenance, repairs, and part flows (reverse logistics) to supply of spares (logistic demand).
Performance Digital Twin allows monitoring and predictive maintenence for fleets of heavy industrial assets, such as jet engines and aircraft.
The Analytics Engine for Performance Digital Twin (PDT) provides unique functionality for multi-level analysis of the sensor data. It analyses large sets of data images recorded across the asset fleet over many time periods; each image contains multivariable time-series data for a time period. The time period could be a single aircraft flight, car trip, one day of industrial plant operation, etc.
Our Reliability Digital Twin (RDT) analytics extracts valuable information from reliability event data. The RDT analyzes reliability event data, such as replacement and repair dates, collected in maintenance, repair, & operations (MRO) for the assets. The RDT Analytics Engine provides unique functionality for multi-level analysis of the MRO data for asset fleet.
Business Case Analysis relies on the Digital Twin models for optimized exploitation of current data. The goal of Business Case Analysis is to specify a preferred course of action, recommend a decision, or provide decision support information.