Physics. Digitalization. Life Extension.
DigitalClone® Software predicts the short and long-term failure rates of mechanical systems like additively manufactured parts, automotive, wind turbines and rotorcrafts to identify life extension actions that reduce cost.
for Additive Manufacturing
DC-AM is a physics-based ICME platform that links process-microstructure-fatigue performance for metal additive manufacturing that virtually examines AM parts at microscale level, including grain size, grain morphology, porosity. Customers indicate that DC-AM can reduce iterations for design optimization by 75% and decrease cost for AM part qualification by up to 50%.
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.
DigitalClone Uses Physics to Predict the Life of Major and Minor Components for Life Extension
DigitalClone predicts the life of complex rotating equipment. The software builds materials-based models and simulates how the unique loading conditions and operational events impact the long-term reliability of the major systems and critical components. Both operators and suppliers in the electrification and transportation markets use the software for its materials science-based computational testing.
“A front-end to our physical testing process with the newest computational test technology matches with our rigorous test and validation process, always with the final aim of increasing the reliability of the turbine. Using DigitalClone is a first step in our extensive validation program. It will contribute to having a faster certification process and, finally, a more reliable turbine available in serial production in 2018.”
“We are very proud to be the first major European wind power operator to use the Sentient Science’s reputed technology in our assets. This represents a big step forward in our Turbine for Life program to obtain the maximum performance from our turbines and be ever more competitive.”