Digital Twin Product Network for Predictive Data Prioritization
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Solution Overview
Problem
The proliferation of data from numerous sensors in value chain networks overwhelms the ability to transmit and process data effectively, leading to challenges in converting data into actionable insights for timely and efficient operations.
Innovation Solution
A method for transmitting predictive models and prioritizing data streams, allowing for the prediction of future data values and taking proactive actions, such as anticipating supply shortages or equipment maintenance needs, by using parameterized models and adaptive intelligence systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is collected from numerous sensors in value chain networks, then the amount of available data increases, but the ability to transmit and process data effectively is overwhelmed
Solution Approach 1:
The patent extracts only the most critical and relevant data from the vast sensor data streams using filtering mechanisms and prioritization algorithms. This selective extraction approach allows the system to manage data volume without overwhelming transmission and processing capabilities, focusing only on data that provides actionable insights for supply chain optimization.
Solution Approach 2:
The patent segments data processing into distributed edge computing nodes throughout the value chain network. Each node processes and filters data locally before transmission to central systems, dividing the overwhelming data processing task into manageable segments that can be handled by individual components without overloading the entire system.
2Loss of information
If all sensor data is transmitted for processing, then complete information is available, but transmission bandwidth and processing resources are overwhelmed
Solution Approach 1:
The patent applies preliminary filtering, aggregation, and prioritization actions at the data source before transmission. Edge computing nodes perform initial data processing, validation, and filtering to eliminate redundant information, ensuring that only essential data is transmitted. This preliminary action maintains information completeness for critical parameters while significantly reducing overall data transmission volume and improving bandwidth efficiency.
3Measurement precision
If centralized data processing is used, then comprehensive analysis is possible, but response time increases and real-time decision-making is delayed
Solution Approach 1:
The patent segments the centralized processing architecture into a hierarchical distributed system with edge computing nodes at multiple levels. Critical time-sensitive data is processed locally at edge nodes for immediate response, while less time-critical data is aggregated and processed centrally for comprehensive analysis. This segmentation enables parallel processing that maintains analytical comprehensiveness while dramatically reducing response times for urgent decisions.
Solution Approach 2:
The patent adds a spatial dimension to data processing by distributing computational resources across the physical value chain network rather than concentrating them in a single central location. This dimensional transformation allows data processing to occur at multiple geographic and organizational levels simultaneously, enabling both local real-time responses and centralized comprehensive analysis to occur in parallel without time conflicts.
Data Source
AI summary
A digital product network system includes a set of digital products each having a product memory, a product network interface, and a product processor programmed with product instructions. The digital product network system includes a product network control tower having a control tower memory, a control tower network interface, and a control tower processor programmed with control tower instructions. The digital product network system includes a digital twin system defined at least in part by at least one of the product instructions or the control tower instructions to encode a set of digital twins representing the set of digital products