Integrated Digital Twin Simulation for Cascading Process Impacts
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Solution Overview
Problem
Traditional systems face challenges in ingesting and analyzing data from disparate technical systems, leading to issues with data quality, noise, inconsistencies, and the inability to identify cascading impacts across multifunctional processes, resulting in limited enterprise-level views and a lack of forward-looking optimization capabilities.
Innovation Solution
A process optimization platform leveraging integrated digital twins that connect multiple technical systems for real-time data ingestion, providing visualizations and predictions by simulating scenarios using agent-based models and machine learning, and adjusting parameters to optimize enterprise processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional systems ingest data from disparate technical systems, then data coverage is improved, but data quality deteriorates due to noise and inconsistencies
Solution Approach 1:
The patent introduces an intermediary layer (data lake, data warehouse, or data mesh) between disparate technical systems and analysis tools. This intermediary standardizes data formats, validates data quality, and manages data integration, allowing comprehensive data coverage while maintaining data quality through centralized control and validation mechanisms.
Solution Approach 2:
The patent creates a composite data architecture that combines multiple data sources (transactional data, unstructured data, external data) into a unified data structure. This composite approach integrates diverse data types while applying consistent quality standards, validation rules, and transformation processes across all data sources.
2Loss of information
If traditional systems analyze data from multiple sources, then enterprise-level view is improved, but the ability to identify cascading impacts deteriorates
Solution Approach 1:
The patent segments the enterprise data landscape into distinct data domains (e.g., customer data, product data, operational data) while maintaining defined relationships between them. This segmentation allows comprehensive enterprise-level visibility through organized data domains while simplifying cascading impact analysis by limiting the scope of interconnections that need to be tracked.
Solution Approach 2:
The patent adds a temporal dimension to data analysis by incorporating historical data, trends, and time-based relationships. This enables enterprise-level views across time while improving cascading impact identification by showing how changes propagate through systems over time, making complex relationships more manageable through temporal patterns.
3Ease of operation
If traditional systems provide backward-looking analysis, then decision-making support is improved, but forward-looking optimization capabilities deteriorate
Solution Approach 1:
The patent implements preliminary action by using simulation and prediction capabilities to evaluate potential future scenarios before decisions are made. The system can model different decision outcomes, predict future performance, and optimize processes in advance, enabling forward-looking optimization while maintaining ease of decision-making through pre-analyzed scenarios.
Solution Approach 2:
The patent establishes continuous feedback loops that combine historical performance data with predictive analytics. The system monitors actual outcomes, compares them with predictions, and uses machine learning to continuously improve future predictions and optimizations, bridging backward-looking analysis with forward-looking capabilities through iterative learning.
Data Source
AI summary
Implementations for receiving an integrated digital twin including multiple digital twins, each digital twin including a computer-executable model of a real-world system used to execute a portion of a process, within the integrated digital twin, a first digital twin providing output to generate input to a second digital twin, receiving enterprise data, the enterprise data being provided from a set of real-world systems used to execute the process, executing, by the integrated digital twin module, simulations of the process using the integrated digital twin and one or more agent-based models based on the enterprise data, at least one agent-based model providing input to the first digital twin, determining simulation results from the simulations, the simulation results including a value of at least one objective function, and adjusting one or more parameters of at least one real-world system used to execute the process based on the simulation results.