Materials Science. Digitalization. Life Extension.

DigitalClone Software predicts the short and long-term failure rates of mechanical systems like wind turbines, rotorcraft & rail to identify life extension actions that reduce cost.

Launch Demo




Monitoring


60,000
Wind Turbines
120
GW
1,000,000+
Bearings
250,000
Gears
350
Wind Farms

A Digital Platform Connecting Operators and Suppliers

for Operations & Maintenance

Identify additional 2% of fleet failures not identified by CMS systems

for Asset Management

Reduce Field Failure Rates from 6% to 3% with Life Extension Actions

for Supply Chain

Increase volume and decrease costs of selling and buying parts

for Engineering

Reduce field failure rates from 6% to 1% through design upgrades

for Operations & Management

  1. Identify the 6% fleet failures
  2. Incremental gain from field failures not detected by current capabilities – “Super Hits” – beyond installed CMS system.
  3. Based on individual turbine loading conditions, identify underperforming sub-components for action.
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Asset Management

  1. Life extension options based on life and lifecycle cost for action that meets corporate business rules – long term planning and budgeting.
  2. Reduce fleet failure rates from 6% to 3% through sub-component replacement strategy and life extension action – control failure propagation.
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for Supply Chain

  1. Reduce Component purchasing costs by 30% with economies of scale.
  2. Aggregated demand forecasts for economies of scale that lowers costs for the entire industry, making wind more competitive than other energy sources.
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for Engineering

  1. Complement physical testing requirements with computational testing to reduce failure rates from 6% to 1% through understanding operational loads during design phase.
  2. Supplier trade off and sensitivity studies for optimal asset configuration – Accelerate new product to market schedules by 50% to 75%.
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DigitalClone Uses Materials Science 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.


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