Audience
Designers and analysts of gearboxes, gears, bearings and associated materials and lubricants.
About DC-E DigitalClone for Engineering
DigitalClone® for Engineering is the world's only gearbox reliability prediction solution integrating multiple scales of analysis in a single software package. In addition to modeling and analysis capabilities at the gearbox and gear/bearing levels, DC-E is the only solution available that models fatigue life based on detailed, physics-based models of the material microstructure (US Patent 10474772B2).
DC-E enables construction of a gearbox digital twin with high value across all stages of the lifecycle of the physical asset - from design and manufacturing optimization to component supplier selection to failure root cause analysis to condition-based maintenance and to prognostics. This computational environment drives down the time and cost to bring new designs to the market and to sustain them over time.
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🔍 Verified Results: Check out our performance history—just search for auvoriaprimeinc on MyFXBook.
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Pricing
Starting Price:
Upon request
Pricing Details:
Depending on AWS based non-government and government operations
Free Version:
Free Version available.
Integrations
No integrations listed.
Company Information
Sentient Science Corporation
Founded: 2001
United States
sentientscience.com
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Product Details
Platforms Supported
Cloud
Training
Documentation
Live Online
Webinars
In Person
Support
Phone Support
DC-E DigitalClone for Engineering Frequently Asked Questions
DC-E DigitalClone for Engineering Product Features
Engineering
2D Drawing
3D Modeling
Design Analysis
Mechanical Engineering
Chemical Engineering
Civil Engineering
Collaboration
Design Export
Document Management
Electrical Engineering
Mechatronics
Presentation Tools
Structural Engineering
Statistical Analysis
Statistical Process Control
Statistical Simulation
Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Survival Analysis
Time Series
Visualization
