Closed Loop Simulation via Digital Twin Data Packages

Resolve Bottlenecks,
Find Innovative Solutions
Generate Solutions

Solution Overview

Problem

Existing technologies face challenges in gathering and processing data from widely distributed assets in IoT environments due to connectivity and data storage complexities, making it difficult to perform closed loop simulations for asset design and validation.

Innovation Solution

An IoT environment with a cloud computing system that configures digital twins based on real-time IoT data, generates data packages, and enables simulations on user devices for asset and process behavior analysis, allowing for closed loop simulations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If data is gathered from widely distributed assets in IoT environment, then asset performance validation and design optimization are enabled, but connectivity and data storage complexities increase

Engineering Contradiction:
Improveasset performance validationVSAvoidconnectivity and data storage complexities
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent introduces a cloud computing system as an intermediary between distributed assets and user devices. The cloud system receives IoT data from multiple assets, manages data storage centrally, and provides processed data to user devices for simulation. This mediator architecture eliminates the need for direct peer-to-peer connectivity between assets and user devices, thereby reducing connectivity and data storage complexities at the edge while enabling comprehensive asset performance validation.

Inventive Principle:
Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent creates digital twins (virtual copies) of physical assets that store and represent asset data in the cloud. Instead of directly accessing and processing data from numerous physical assets, the system works with simplified digital representations. This copying approach reduces the complexity of data gathering and storage by operating on manageable digital models rather than raw data from distributed sensors and devices.

Inventive Principle:
Principle #26Copying

2Measurement precision

If multiple physical prototypes are used for asset testing, then design validation accuracy is improved, but time-to-market and overall costs increase

Engineering Contradiction:
Improvedesign validation accuracyVSAvoidtime-to-market
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The patent uses digital twins as virtual copies of physical assets to perform simulations and design validations. Instead of manufacturing and testing multiple physical prototypes, engineers can run numerous simulation scenarios on digital models in the cloud. This approach maintains high measurement precision for design validation while eliminating the time-consuming iterative process of building and testing physical prototypes, thereby significantly reducing time-to-market.

Inventive Principle:
Principle #26Copying

Solution Approach 2:

The system performs preliminary simulations and validations on digital twins before committing to physical manufacturing. By conducting virtual testing and optimization in advance, the system identifies and resolves design issues before physical prototypes are needed, reducing the number of iterative physical testing cycles required and accelerating the overall development timeline.

Inventive Principle:
Principle #10Preliminary action

3Productivity

If real-time IoT data is processed in cloud computing system, then closed loop simulations are enabled, but data processing and transmission requirements increase

Engineering Contradiction:
Improveclosed loop simulation capabilityVSAvoiddata processing and transmission requirements
Core Design Contradiction:
ProductivityVSUse of energy by moving object

Solution Approach 1:

The patent extracts only the essential and relevant data from IoT data streams that are needed for simulation purposes, rather than transmitting and processing all raw data. The cloud computing system selectively processes specific parameters and metrics required for closed-loop simulations, reducing the overall data processing and transmission requirements while maintaining the capability to perform comprehensive simulations.

Inventive Principle:
Principle #2Taking out (Extraction)

Data Source

PatentEP4338017B1System and method for performing closed loop simulation in an IoT environment
Publication Date: 2026.04.01 SIEMENS AG
  • EP4338017B1 patent drawingFigure 1
  • EP4338017B1 patent drawingFigure 2
  • EP4338017B1 patent drawingFigure 3

AI summary

An IoT environment (100) comprising at least one source configured to provide IoT data associated with at least one asset of at least one industrial plant (106A-M), at least one user device (114); and a cloud computing system (102) communicatively coupled to the at least one source and the at least one user device (114). The cloud computing system (102) configures a digital twin corresponding to at least one of the asset and a production process associated with the industrial plant (106A-M) based on the IoT data received from the source. Further, at least one data package is generated based on the configured digital twin upon receiving a request for accessing the digital twin from the user device (114). The at least one data package is transmitted to the user device (114), for enabling the user device (114) to perform one or more simulations based on the data package.