Accelerating Design Schedules
DigitalClone technology is an advanced digital twin solution that uses engineering-based and physics-based models to predict remaining useful life (RUL) of critical systems and components. Using this new cloud-based technology, it is possible to predict how operational loading conditions will eventually cause part failures within rotating mechanical systems (such as transmissions) by analyzing the accumulation of stresses at the microstructure level of the materials.
Reduce Risk, Cost & Uncertainty with long-term visibility of component remaining useful life
Original Equipment Manufacturers
Create internal drivetrain DigitalClone models that generate Component Life Predictions for bearings, gears and drivetrain systems using material science and physics-based analysis based on planned operational profiles and loading conditions.
Test data points through computational test, including operational profiles, design alternatives & material options, to meet competitive design requirements.
Accelerate marketing and sales schedules to meet market timing requirements.
Objectively compare competing technologies and designs to make data-driven decisions.
Host complimentary technologies as a single place to manage a heterogeneous fleet.
Evaluate risk & extend MFOP of next generation aircraft through multi-physics-based simulations of designs under realistic mission profiles.
Forecast sustainment costs for new using Multiphysics modeling techniques, including scenarios where no historical data is available or limited.
Leverage high-fidelity physics based models to support condition maintenance to reduce cost per flight hour revenue.
Provide more accurate forecasts and budget inputs for upcoming services and inventory demand from the OEM/ third party service providers.
Leverage certified DigitalClone models to assess options that extend time between overhaul, leveraging alternate supplier technologies.
Provide early warning of emerging reliability issues within fleets.
We have an industry (aerospace) that is ripe to get there… we have to stop talking about diagnostics and more about prognostics and how we get out to a accurate future view.
The aerospace industry is looking for better analytics and a better way to put the answers into the hands of the person that is maintaining the aircraft.
“Under current paradigm, every system is so unique that going through the qualification process is costly. Computational testing holds promise to reduce the costs, but there are still any uncertainties. Eventually, we’ll get there”
“We’re trying to help make better helicopters for the general public, and in the helicopter world, gears are very important. When the DigitalClone results came in, and the correlation was so good, the company president got very excited about what his guys had been developing.”
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