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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 Azure Digital Twins?
Azure Digital Twins serves as an IoT platform enabling the creation of digital replicas of physical entities, spaces, processes, and people. This innovative platform yields critical insights that can significantly improve product development, optimize operational efficiency, lower costs, and enhance customer satisfaction. It provides an intuitive framework for crafting digital representations of interconnected settings using a flexible modeling language. Users can model a wide variety of entities, including buildings, manufacturing plants, agricultural fields, energy systems, transportation networks, sports facilities, and even entire cities. These digital twins come alive in a dynamic execution environment that monitors changes over time. By utilizing powerful query APIs, users can glean actionable insights into the behaviors of their modeled environments and easily integrate with Azure's data analytics services. The open modeling language allows for the creation of customized domain models tailored to any connected setting through the Digital Twins Definition Language, ensuring adaptability across various applications. Thus, Azure Digital Twins not only supports business innovation but also enables organizations to adjust effectively in an ever-evolving digital landscape, making it an invaluable tool for modern enterprises.
Integrations Supported
APERIO DataWise
Azure Marketplace
ICONICS' Intelligent Building Software (IBSS)
Microsoft Azure
Integrations Supported
APERIO DataWise
Azure Marketplace
ICONICS' Intelligent Building Software (IBSS)
Microsoft Azure
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
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
Microsoft
Date Founded
1975
Company Location
United States
Company Website
azure.microsoft.com/en-us/services/digital-twins
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
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization