This tool is still in beta-phase and not finished yet. We're currently working on improving it.
About
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Imprint
Digital Twin Maturity
Digital Twin Maturity
Public
Maturity
Model Maintenance
How is the model quality observed and controlled?
Descriptions of models are not formalized and maintained manually
Models are maintained manually in dedicated modeling tools
Individual models can detect lacking model quality itself
Individual models can detect lacking model quality itself and can reload latest data and code itself
Individual models can detect lacking model quality itself and can load additional model plugin or adjust the model parameter itselfs
Individual models are can detect lacking model quality itself and can full maintain themselves by e.g. organizing new sensors and computing capabilities
DT Data
Your decisions will be encoded in this string. You can distribute this string to show your DT.
Load previous session:
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Reset
Reset the session.
This resets all your decisions regarding your DT.
Categories
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Context
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Reference Object
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Tangible Product Life Cycle Phases
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Benefits
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Application domain
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Model
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DT Creation Approach
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Modelled characteristics
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Digital Model Types
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Model Authenticity
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Model Maintenance
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Modularity
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Computing Capabilities
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Trigger Types
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Model Look-Ahead Perspective
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Computing Capabilities
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Update Frequency - Input
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Update Frequency - Output
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Data
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Data Storage
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Data Scope
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Data Quality
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Data Sources
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Data Interpretation
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Control
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Level of Cognition
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Levels of Autonomy
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Learning capabilities
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Integration
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Digital Twin Interaction
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Hierarchy
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Connection Mode
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User Focus
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Interorganizational Integration / Collaboration
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Human-Machine-Interaction (HMI)
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Types of Interaction Devices
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Human Interaction Capabilities