First Wind’s entire fleet of gearboxes started failing suddenly after only a few months of operation.
The capability of Sentient Science’s ground truth models, called DigitalClone™, allowed First Wind to predict when each gearbox system and component would fail months to years in advance. With these predictions, the operator dramatically reduced the uncertainty in the costs of their gearbox remanufacturing program and future financial budgeting. By deploying the DigitalClone prognostic model with Sentient Science’s DigitalClone Live™ sensor and the “Industrial Internet” infrastructure, the operator could confidently make operations and maintenance decisions (such as partial de-rating, lubrication changes, or refurbishing) to extend the life of their turbines by up to ten years.
- Predict assets risk of failure with progostic ground-truth model
- Acquire data from sensor systems to confirm failures from new conditions
- Extend the assets risk of failure and quantify benefits of operations and maintenance decisions