DigitalClones®
Digital Twins of mechanical systems, such as wind turbines, rotorcraft, and railroad rails, that enable cost effective prediction of the short- & long-term failure rates and identification of life extension actions that reduce operational cost.
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for Engineering
DC-E is a multi-body dynamics digital twin that uses physics-based models to make statistical life predictions of drive train components. It is the world’s only integrated solution from system modeling to bearing and gear detailed analysis to simulation-based component life prediction. No other solution incorporates microstructure-based life predictions. Customers using this technology have achieved up to 35% cost savings and 65% schedule compression for drive system development programs.
for Wind Operations & Maintenance
DC-OM is a digital twin of two major individual turbine major components at scale, gearbox and main bearing, using machine learning to deliver health prediction capability superior to CMS. A unique orchestration functionality is under development to host 3rd party health prediction models for other individual turbine major components at scale such as blades, towers, hub, etc. to provide a holistic management of a wind turbine.
for Rail Operations & Maintenance
DC-RM is a new product category of "Precise Maintenance” tools to enable railroads to determine their best rail maintenance scenarios, including grinding, rail profiling, load allocation etc. . Sentient is the first company to commercialize a proprietary precise physics-based model with proprietary rail simulation to enable "What If" scenarios for rail applications; its life extension simulator enables railroads to make data-based budgeting decisions. DC-RM is integrated with the North American renown Rail Vehicle and Track Optimization (RVTO) program from NRC’s Data Analytics Centre.
