Digital Twin Meta-Modeling for Flexible Event-Discrete Control
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Solution Overview
Problem
Current approaches to real-time process control in manufacturing environments, particularly in distributed event-discrete systems, lack flexibility and adaptability due to rigid hierarchical tree models that require complete recoding for changes or additions, leading to increased complexity and inefficiency as systems evolve.
Innovation Solution
A computer-implemented meta-modeling approach that uses meta-objects to model subsystems of distributed event-discrete systems, allowing for state representation with different levels of data abstraction and enabling dynamic modification of the system model in real-time through meta-level, use-level, and twin-level abstraction, reducing complexity and enhancing flexibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If hierarchical tree models are used for process control, then system structure is clearly defined and control is systematic, but flexibility and adaptability deteriorate requiring complete recoding for changes
Solution Approach 1:
The patent segments the hierarchical tree model into multiple independent layers (process layer, control layer, execution layer). Each layer can be modified independently without affecting the entire model, enabling flexible adaptation while maintaining systematic control. This layered segmentation allows changes in one layer without requiring complete recoding of the hierarchical structure.
Solution Approach 2:
The patent introduces a temporal dimension to the hierarchical model by enabling dynamic modification of model parameters and structure over time. The system transitions from a static hierarchical tree to a dynamic multi-layered architecture where models can be updated, added, or removed in real-time without complete recoding, adding the dimension of time flexibility to the rigid hierarchical structure.
2Adaptability or versatility
If hierarchical tree models are used for process control, then systematic control is achieved, but adaptability to changes deteriorates requiring complete recoding
Solution Approach 1:
By dividing the hierarchical model into independent layers (process, control, execution), the patent enables localized modifications. When changes are needed, only the specific layer or module requiring adaptation is modified, eliminating the need for complete recoding and significantly reducing the time loss associated with model updates.
Solution Approach 2:
The patent transforms the static hierarchical tree model into a dynamic multi-layered architecture where model parameters and structures can be modified in real-time. This dynamic capability allows the system to adapt to changes without requiring complete recoding, reducing adaptability time while maintaining systematic control through the layered structure.
3Productivity
If distributed event-discrete systems are modeled traditionally, then system operations are controlled, but information exchange complexity increases
Solution Approach 1:
The patent segments distributed event-discrete systems into independent modular units organized in layers. Each module handles specific functions with well-defined interfaces, reducing information exchange complexity between modules while maintaining overall system control efficiency. The segmentation creates clear boundaries that simplify communication protocols.
Solution Approach 2:
The patent introduces standardized interface layers and communication protocols as intermediaries between different system modules. These intermediary layers abstract complex information exchange details, enabling efficient process control while reducing the apparent complexity of inter-module communication through standardized data formats and interaction patterns.
Data Source
AI summary
Modelling of distributed event-discrete systems using digital twins. In more detail, the present disclosure relates to the field of modeling distributed event-discrete systems using digital twins for subsequent use of the models during real time control of distributed even-discrete systems. Heretofore, there are provided a computer implemented meta model, modeling methods using the computer implemented meta model, and related modeling engine and service engine. In the computer implemented meta model at least one state in the at least one state model is represented by a set of partial states using different levels of data abstraction according to a meta description, a range of values characterizing a target for a considered state, and a range of values representing an actual constellation of a considered state.