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What is GE Digital Twin?
Employing advanced analytics and machine learning methodologies is vital for reducing operational costs and alleviating risks. Digital twins, a key element of the digital transformation journey, offer exact virtual models of physical assets, systems, and objects that aim to improve productivity, streamline processes, and boost profitability. Generally, a digital twin is seen as a software representation of a tangible asset or system designed to identify, prevent, forecast, and enhance operations through real-time data analysis, ultimately providing considerable advantages for businesses. At GE Digital, we focus on utilizing digital twin software to support our clients across three essential areas: Asset, Network, and Process. By adeptly overseeing, simulating, and controlling an asset or process, organizations can greatly improve system performance. Moreover, it is imperative to prioritize the health and safety of employees and the environment while pursuing business objectives, which entails reducing incidents associated with assets and processes and avoiding unexpected downtimes, thus nurturing a more robust operational structure. The adoption of digital twin technology not only boosts efficiency but also opens doors for innovation across numerous industries. As organizations embrace this technology, they position themselves for sustained growth and competitive advantage in an ever-evolving marketplace.
What is AWS IoT TwinMaker?
Utilize your existing IoT, video, and enterprise application data directly from its original source, thus avoiding the complications of data reingestion or transfer. Boost your productivity through an automatically generated knowledge graph that connects your data sources with virtual representations of physical systems, facilitating accurate simulations of real-world environments. Enjoy an engaging 3D visualization of your operations and systems, which enables you to improve efficiency, increase production, and enhance overall performance. With AWS IoT TwinMaker, developers can easily create digital twins for real-world systems such as buildings, factories, industrial equipment, and production workflows. This robust toolset equips you to optimize building management, enhance production capacity, and improve equipment performance. Furthermore, by leveraging existing data from multiple sources, you can construct virtual models of any physical environment while marrying contemporary 3D designs with real-time data for deeper insights and improved operational efficiency. The integration of these technologies not only streamlines processes but also fosters innovation in how businesses manage their physical assets.
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
$1.50 per million calls
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
GE Digital
Date Founded
2015
Company Location
United States
Company Website
www.ge.com/digital/applications/digital-twin
Company Facts
Organization Name
Amazon
Date Founded
1994
Company Location
United States
Company Website
aws.amazon.com/iot-twinmaker/
Categories and Features
Simulation
1D Simulation
3D Modeling
3D Simulation
Agent-Based Modeling
Continuous Modeling
Design Analysis
Direct Manipulation
Discrete Event Modeling
Dynamic Modeling
Graphical Modeling
Industry Specific Database
Monte Carlo Simulation
Motion Modeling
Presentation Tools
Stochastic Modeling
Turbulence Modeling
Categories and Features
Industrial IoT
Condition Monitoring
Data Visualization
Factory Data Analytics
Machine Learning
Machine Workflow Creation
Predictive Maintenance
Production Line / Factory Insights
Real-Time Monitoring
Reporting / Analytics
Smart Alerts / Notifications
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization