The solution proposed involved the digitalization of processes and the development of a data-driven environment of the wind farm. This solution aimed to improve data collecting and processing, increasing energy efficiency through an authentic Digital Twin.
To do this, the first step was to treat and upload 3D models of the targeted assets within the Vidya platform.
In this phase, our engineering and asset management specialist team was responsible for processing and contextualizing all the already existing information and data from the industrial plant, just as attributes of each structural component, TAGs, workflows, inspection, and maintenance plans. This task employs OCR Optical Character Recognition, a technology used to extract information from documents, create shortcuts and link them into the respective assets.
To complete the data collection structure, our team integrated the platform with the client’s PIMS (Plant Information Management System) to process data regarding the residual life of the equipment and efficiency over time. This allowed us to supply our AI algorithms with the available historical data to generate equipment failure predictions.
All this data generated in the operation was also organized and presented in complete customizable dashboards, being able to operate and navigate through all this information with just a few clicks.
Finally, with the combination of all technologies mentioned before, it was possible to:
- Contextualize constantly generated data from all equipment by sensors, such as energy efficiency;
- Use of Artificial Intelligence and Machine Learning to generate equipment efficiency forecasts, allowing a much more intelligent and predictive monitoring;
- Triggering automatic visual alerts in the system when an efficiency problem occurs in one of the assets, or is predicted by the AI algorithm, enabling faster resolution of the problem and reducing unscheduled downtime in the operation.
- Use the platform planner tool to manage maintenance activities at the facility, allowing better control and prioritization of the processes carried out by the workers in the field.