Digital Twin Data Model for Full Life Cycle Object States
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Solution Overview
Problem
Current digital twinning models require separate models for objects with the same structure but different specific parameters, leading to high complexity and resource consumption, and only model real-time events, lacking full life cycle data modeling.
Innovation Solution
A digital twinning method that creates a data model with attribute parameters, capturing current, historical, and planned states to generate real-time, historical, and planned object representations, enabling full life cycle modeling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If separate models are created for objects with the same structure but different specific parameters, then modeling precision is improved, but device complexity increases and resource consumption increases
Solution Approach 1:
The patent applies universality by creating a single standardized data model structure that can represent multiple objects with the same structure but different parameters. Instead of creating separate models for each object instance, the system uses one universal model template that can be instantiated with different parameter values, thereby reducing model complexity while maintaining modeling precision.
Solution Approach 2:
The patent uses parameter changes by distinguishing between structural parameters (which define the model architecture) and instance parameters (which vary across objects). The data model structure remains constant while specific parameter values change to represent different objects, allowing precise modeling without increasing structural complexity.
2Manufacturing precision
If separate models are created for objects with the same structure but different specific parameters, then modeling precision is improved, but resource consumption increases
Solution Approach 1:
The standardized data model structure serves multiple objects simultaneously, reducing the total number of models that need to be created, stored, and processed. This universal model reduces computational resources and storage requirements while maintaining the ability to precisely represent each object's specific parameters.
Solution Approach 2:
The patent merges the common structural elements of multiple objects into a single standardized model framework. By combining shared structural definitions and only storing instance-specific parameter variations, the system reduces overall resource consumption while preserving modeling precision for each individual object.
3Ease of operation
If only real-time events are modeled, then ease of operation is improved, but loss of information increases due to inability to model full life cycle
Solution Approach 1:
The patent applies preliminary action by incorporating planned state modeling that captures future events before they occur. The standardized data model structure is designed to accommodate not only current and historical states but also planned/future states, allowing the system to prepare and track life cycle information in advance rather than reacting only to real-time events.
Solution Approach 2:
The patent adds a temporal dimension to the modeling by explicitly including historical state and planned state alongside current state. This transforms the model from a single-point-in-time representation to a multi-temporal representation, capturing the full life cycle across different time dimensions without complicating the core data structure.
Data Source
AI summary
Provided are a digital twinning method, apparatus and device for a full life cycle of a thing. The method includes: creating a data model of a thing, the structure of the data model being an attribute parameter set of the thing; obtaining the current state, historical state and planned state of a same target thing; and performing digital twinning on the basis of the data model and the current state of the target thing to obtain a real-time thing object, performing digital twinning on the basis of the data model and the historical state of the target thing to obtain a historical thing object, and performing digital twinning on the basis of the data model and the planned state of the target thing to obtain a planned thing object, wherein the thing is a physical entity or an event.