Sentient Science

Sentient Science, founded in 2001, provides digital twin technology to predict the life of mechanical systems. Sentient's DigitalClone? SaaS solutions use proprietary physics-based modeling and machine learning AI to unlock insights that lower the costs of designing, operating, and sustaining high value assets. This visibility also helps customers optmize parts inventories and increase profitability. Furthermore, Sentient Science offers professional scientific services that enable us to partner with customer experts in industries such as Wind Energy, Aerospace, and Rail to develop cost-optimized life extension actions. Sentient Science is a leader in prognostic solutions with one patent awarded in 2019 for physics-based life prediction and six additional patents pending. Sentient has won more than $22 million in SBIR/STTR funding from the U.S. Government ? with agencies including Dept of Energy, Dept of Defense, and NASA. The technology has been recognized by the SBIR program with the 2014 Tibbetts Award, by Bloomberg as New Energy Pioneer Award in 2016, and Frost & Sullivan in 2017 with the New Product Innovations Award for Wind Prognostics. DigitalClone has 4 Product Offerings: DigitalClone for Engineering (DC-E) is a physics-based patented SaaS design solution to model drivetrains and predict individual component life under real-world operating conditions. DC-E delivers a unified workflow for a multiscale analysis from system level to component level through microstructure modeling in a single software package. Customers using this technology have achieved up to 35% cost savings and 65% schedule compression for drive system development programs. DigitalClone for Wind Operations and Maintenance (DC-OM) is an AI/ML-based digital twin SaaS that detects damage based on the current ?as-maintained? configuration of a wind turbine in operation. DC-OM provides a holistic view of the health and remaining useful life (RUL) of an asset?s critical systems and identifies components that may be operating with damage. This enables asset-level health risk assessments that support predictive maintenance programs to reduce O&M costs and extend asset life. DigitalClone for Rail Maintenance (DC-RM) is a physics-based SaaS scenario planning tool to compare and select best rail maintenance actions based on rail life extension and financial return on investment. DC-RM provides railroads with ?Precision Scheduled Maintenance? to maximize the utilization of the rail asset and optimize capital efficiency over the lifecycle. DigitalClone for Additive Manufacturing (DC-AM) is a multi-scale and multi-physics SaaS model to computationally assess quality and performance of additive manufacturing built-parts. DC-AM uniquely links the process, microstructure and fatigue to provide design and computational testing. Customers indicate that DC-AM can reduce iterations for design optimization by 75% and decrease cost for AM part qualification by up to 50%. Mission:?Sentient missions is to lower the cost of operating rotating mechanical equipment through the digitalization of assets as digital twins aka DigitalClone and providing tools to achieve life extension, sustainability and reliability. DigitalClones? are digital twins of mechanical systems, such as wind turbines, rotorcraft, and railroad rails, that enable cost effective prediction of the short- and long-term failure rates and identification of life extension actions that reduce operational cost.