Event-Driven Digital Twin Control for Responsive Process Management
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Solution Overview
Problem
Existing digital twin technologies are not effectively utilized for efficient and accurate process control in domains like manufacturing and healthcare, lacking comprehensive integration of data interaction and control mechanisms.
Innovation Solution
Implementing a controller service system with event-driven process control using digital twins, enabling bidirectional data exchange and behavioral models to manage process entities, allowing for real-time, asynchronous, and parallel operation of control logic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If digital twins are used to gather extensive real-time data, then data availability and access are improved, but the effectiveness and accuracy of process control remain insufficient
Solution Approach 1:
The patent introduces a controller service system as an intermediary layer between the digital twin data and the process control execution. This system includes controller service modules that contain behavioral models, which act as mediators to translate raw digital twin data into effective control actions. The behavioral models serve as the intermediary mechanism that bridges the gap between data gathering and effective process control, enabling the digital twin to actually influence and control the physical process entities.
2Device complexity
If traditional process control methods are used, then system simplicity is maintained, but responsiveness and flexibility to real-time changes are reduced
Solution Approach 1:
The patent implements dynamic behavioral models within the controller service modules that can adapt and respond to real-time changes in the process entities. These behavioral models are not static control rules but dynamic representations that can adjust their behavior based on current conditions observed from the digital twins. This dynamic approach enables the control system to respond flexibly and rapidly to real-time changes while maintaining a relatively simple overall architecture through the modular service-based design.
3Measurement precision
If comprehensive control logic is integrated into digital twins, then process control accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the comprehensive control logic into multiple independent controller service modules, each containing specific behavioral models for different aspects of process control. Rather than having one complex monolithic control system, the control logic is divided into modular units that can be independently developed, deployed, and managed. Each module handles specific control functions with appropriate accuracy, while the overall system complexity is managed through this modular segmentation approach.
Solution Approach 2:
The controller service modules are designed with universal interfaces and standardized behavioral model structures that can handle multiple control functions. The modular architecture allows the same framework to be applied across different process entities and control scenarios, reducing overall system complexity through reusability. The behavioral models use common data structures and communication protocols, enabling multi-functionality while maintaining consistency and reducing the need for custom complex implementations for each control task.
Data Source
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AI summary
The present invention aims at providing an approach to digital twin-based process control for efficient and accurate achievement of process objectives. Heretofore, a controller service module (18) runs an event-driven control process in a digital twin domain for control of process entities operated in a process domain. The behavior of process entities is modeled through execution of state machine models. Event data is communicated asynchronously to the controller service module (18) for storage in a process cycle buffer (26). A model-based process controller (24) reads input information in processing cycles and controls process entities by operating state machine models to reflect the input of event data. It is checked whether the operation of state machine models triggers the generation of external control commands which are then output by an outbound interface (32) to process entities for control processing.