XR Flow Interface Simulation Using Digital Twin Metadata
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Solution Overview
Problem
Current methods for developing extended reality (XR) Human Machine Interfaces (HMIs) for flow systems are complex, prone to human error, and require high expertise, especially when components change status during operation, necessitating a simplification that reduces resource usage and error likelihood while maintaining reliability.
Innovation Solution
A computer-implemented method using an XR user interface to simulate an actual flow system by selecting and configuring graphical elements and connections, receiving metadata, and applying operations to actual data for real-time simulation and display, incorporating mathematical, machine learning, or artificial intelligence operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If customized scripts are generated to track and visually represent each segment of the flow system in XR HMI, then the system can provide detailed visual representation and tracking of flow, but the complexity of the scripts increases and requires high level of expertise for development
Solution Approach 1:
The patent uses digital twin technology to create virtual copies of physical flow system components. Instead of writing complex custom scripts for each component, the system automatically generates virtual representations that mirror the physical system's behavior, reducing scripting complexity while maintaining detailed visual representation capabilities
Solution Approach 2:
The XR HMI system automatically tracks and updates the digital twin components based on real-time data from the physical system. The system self-updates the virtual representations without requiring manual script modifications, reducing the expertise needed for development and maintenance while providing continuous visual feedback
2Reliability
If individual scripts are designed to handle every combination of possible conditions in the flow system, then the system can account for all scenarios, but the development resources and time required increase significantly
Solution Approach 1:
The patent implements a universal digital twin framework where a single set of virtual components can represent multiple physical components across different scenarios. This universal approach allows the system to handle various flow conditions without requiring separate custom scripts for each case, reducing development time while maintaining comprehensive scenario coverage
Solution Approach 2:
The digital twin system dynamically adapts to changing flow conditions by automatically updating virtual component states based on real-time sensor data. Instead of pre-programming all possible conditions, the system dynamically responds to actual system states, reducing development effort while ensuring reliable handling of all scenarios
3Reliability
If the XR HMI system is updated to account for modifications in the flow system, then the system remains accurate, but the level of expertise needed and resources required for updates increase
Solution Approach 1:
The patent implements bidirectional communication between the physical flow system and its digital twin representation. When modifications occur in the physical system, sensors detect the changes and automatically feed this information back to update the virtual model. This feedback mechanism maintains accuracy without requiring manual updates by experts, as the system self-adjusts to reflect current system state
4Ease of operation
If conventional HMI methods are used to model flow systems in XR, then detailed control and monitoring is achieved, but human error increases and resources used for development increase
Solution Approach 1:
The patent replaces manual script-writing and configuration processes with automated digital twin generation technology. Instead of operators manually creating and maintaining complex XR HMI scripts, the system automatically generates virtual representations from physical system data, reducing human error while maintaining detailed control and monitoring capabilities
Data Source
AI summary
A method for applying extended reality to simulate an actual flow system, including receiving selection of simulated components of the actual flow system that are graphical elements, receiving component metadata for each simulated component that represents simulated component factors that affect the simulated flow from, through, or to the simulated component, receiving simulation connection metadata for each simulated connection between the simulated components that represents simulated connection factors that affect the simulated flow through the simulated connection, receiving actual data over time, simulating the flow over time through the simulated connections based on the actual data by applying a model using a set of operations to the actual data, the simulation component metadata, and the simulation connection metadata. The method further includes displaying via the extended reality user interface the three or more simulated components as connected by the simulated connections and the simulated flow.