Digital Twin Simulation Orchestration for Modular Plant Edge Deployment
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Solution Overview
Problem
Current technologies lack solutions for distributed analytics and simulation on edge devices in modular plants, particularly in integrating automation and analytics functionalities, which are time-consuming and dependent on specific hardware, software, and operating systems.
Innovation Solution
A computer-implemented method and orchestration system that generates and deploys simulated model components on distributed operational-technology applications using a digital twin model of modular plants, leveraging the Functional Mock-up Interface (FMI) and Remote Procedure Call (RPC) technologies to automate configuration and deployment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If distributed simulation is implemented on edge infrastructure, then simulation capability and analytics functionality are improved, but integration complexity and deployment time increase significantly
Solution Approach 1:
The system segments the digital twin model into multiple simulated model components that can be independently deployed on different edge devices. Each component represents a specific simulation functionality that can be orchestrated separately, reducing the complexity of integrating entire simulation systems on edge infrastructure.
Solution Approach 2:
The patent introduces an orchestration system that acts as an intermediary between the central simulation environment and distributed edge devices. This orchestrator manages the deployment, configuration, and synchronization of simulated model components, abstracting away the complexity of direct integration between simulation software and edge infrastructure.
2Reliability
If manual integration of automation tags is performed, then connection reliability is improved, but integration time and orchestration effort increase
Solution Approach 1:
The system performs preliminary actions by pre-configuring simulated model components with standardized interfaces and automatic tag mapping capabilities. Before deployment to edge devices, the orchestration system prepares connection configurations and validation rules, so that actual integration requires minimal manual effort while maintaining reliability through pre-established connection protocols.
3Ease of operation
If simulation components are deployed manually on edge devices, then deployment control is improved, but scalability and replicability decrease
Solution Approach 1:
The patent creates universal simulated model components that can be deployed across multiple edge devices with consistent behavior. The orchestration system provides multi-functionality by handling both individual device deployment and bulk deployment scenarios, allowing the same component library to serve both controlled single-device deployment and scalable multi-device deployment needs.
Solution Approach 2:
The system enables parameter changes in simulated model components during deployment through the orchestration system. Configuration parameters such as connection settings, data sources, and simulation parameters can be dynamically adjusted based on the target edge device characteristics, allowing automated deployment across diverse hardware platforms while maintaining deployment control through centralized parameter management.
4Adaptability or versatility
If vendor-specific simulation solutions are used, then functionality completeness is improved, but system dependencies and vendor lock-in increase
Solution Approach 1:
The patent creates standardized copies of simulation model components that can be replicated across different vendor platforms. The orchestration system manages these copies, allowing the system to leverage functionality from various vendor solutions while maintaining a unified, vendor-agnostic interface. This reduces dependencies on any single vendor's proprietary system while preserving access to diverse simulation capabilities.
Data Source
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Figure 1B
Figure 1C
AI summary
In order to orchestrate configurations of simulations based on digital twin models (DTM1, DTM2, DTM3) of modular plants (Pm, PM1, PM2, PM3) such that the configurations of the model-based simulations are generated and deployed automatically, it is proposed and based on a logical "System Structure and Parameterization <SSP>"-functionality (SSP-T) including a "Functional Mock-up Interface <FMI>"-functionality (FMI-T) combined with a "Functional Mock-up Unit <FMU>"-functionality (FMU-T) to (i) generate (grt) for distributed operational- technology-applications (OTAd, ED1, ED2, ED3) of the modular plants simulated model components (MCs,1, MCs,2, M Cs,3; including assignment rules (AR1, AR2, AR3) for automation data (AD1, AD2, AD3) captured due to automation of the plants and assigned to the distributed operational-technology-applications, and (ii) deploy (dpl) in the course of orchestrating the simulations configurations the simulated model components on the distributed operational-technology-applications by using the SSP-functionality with "Functional Mock-up Unit <FMU>"- functionalities (FMU-T1, FMU-T2, FMU-T3) as part of the FMI- functionality for the distributed operational-technology™ applications and implementing for the distributed operational-technology-applications and as part of the FMI- functionality in a server-client-manner "Remote Procedure Call <RPC>"-technology based Proxy- FMU-functionalities (PFMU-T1, PFMU-T2, PFMU-T3) with - "Proxy- FMU"-entities (PFMU-E1, PFMU-E2, PFMU-E3) embedded in the SSP-functionality and - corresponding "Remote-Controlled™ FMU"-entities (RCFMU-E1, RCFMU-E2, RCFMU-E3) implemented on the distributed operational-technology-applications.