Businesses strive to maximize the performance of their assets, whether to improve output or increase efficiency. DataV is able to aggregate information from an entire population of assets, using machine learning to develop accurate data models that reflect how a piece of equipment operates.
The data models can then be used to identify assets that are underperforming and providing prescriptive, corrective actions. They can also be used to simulate various operating conditions.
In the event that prescriptions actions are warranted, the information can be used to modify calibration or configuration settings immediately by sending commands directly to the equipment.
Alternatively, this information can serve as input to the R&D process, improving future versions of the equipment.