Outcome-Driven Digital Twin Orchestration for Scalable Automation
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Solution Overview
Problem
Existing digital twins in industrial automation environments are limited in customizability and require significant processing power and sensor data, making it difficult to accurately model performance characteristics and interface with complex systems, thus unable to effectively represent large-scale industrial processes.
Innovation Solution
An orchestration engine is introduced to configure and simulate digital twin models, allowing for customizable inputs/outputs and scalable representation of industrial systems by identifying targeted outcomes and configuring digital twin environments with multiple digital twins that represent real entities, enabling real-time data analysis and process simulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing digital twins are used to model industrial automation systems, then real-time data on component performance can be provided, but the systems require significant processing power and sensor data, limiting their scalability to complex industrial environments
Solution Approach 1:
The patent segments the digital twin system into hierarchical levels (device-level, assembly-level, system-level digital twins), allowing each level to model only the necessary performance characteristics for its scope. This segmentation enables scalable deployment in complex industrial environments without requiring all digital twins to process all sensor data, thus maintaining modeling accuracy while improving scalability.
2Adaptability or versatility
If existing digital twins are configured to accurately represent real entities, then performance characteristics can be modeled, but the customizability is limited and significant processing power is required
Solution Approach 1:
The patent implements dynamic configuration of digital twins where the level of detail and processing intensity adapts based on the specific application needs. Users can dynamically adjust the fidelity and customization of each digital twin according to the required outcome, allowing high customizability for critical components while using simplified models for less critical ones, thus reducing overall processing power requirements.
Solution Approach 2:
The system allows changing parameters such as model fidelity, update frequency, and data granularity based on the targeted outcome. By adjusting these parameters, users can balance between customizability and processing power consumption, enabling flexible adaptation to different industrial scenarios without requiring maximum processing power for all applications.
3Productivity
If digital twins are used to interface with various industrial systems, then real-time monitoring is achieved, but the interfacing capability is siloed making it difficult to implement in complex environments
Solution Approach 1:
The patent creates a universal digital twin platform that can interface with multiple types of industrial systems and devices through standardized protocols and adapters. The system maintains real-time monitoring capabilities while providing process-wide interfacing by enabling digital twins at different hierarchical levels to communicate and share data, thus achieving both real-time monitoring and broad adaptability to complex industrial environments.
Data Source
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AI summary
Various embodiments of the present technology relate to digital twins of devices and assemblies. More specifically, some embodiments relate to the orchestration of digital twin models for simulating industrial systems based on characteristics of digital twins. In an embodiment, a method of operating an orchestration engine in an industrial automation environment comprises identifying a targeted outcome for modeling the industrial automation environment, configuring a digital twin environment corresponding to the industrial automation environment based at least on the targeted outcome, and executing a process associated with the industrial automation environment using the digital twin environment.