Embedded Controller Data Marketplace for Distributed Industrial Analytics
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Solution Overview
Problem
Conventional industrial computing environments face bandwidth bottlenecks and limited visibility of data, restricting the effectiveness of data analysis and decision-making due to centralized data management and lack of distributed analytics in industrial automation systems.
Innovation Solution
Implementing a distributed data management system where embedded controllers form a distributed database, allowing for local processing and storage of data, enabling distributed analytics and reducing the need for real-time data transfer to a central location, with each controller having a distributed database instance for storing and processing data locally.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is transferred from control layer devices to higher layers for centralized analysis and storage, then data management follows conventional multi-layer architecture, but network bandwidth becomes a bottleneck limiting data transfer capacity and higher layers consume excessive energy for processing
Solution Approach 1:
The patent segments the centralized data management function into distributed data marketplaces at each control layer device. Instead of one central repository, multiple local data markets are created, allowing data to be stored and processed locally rather than being transferred to higher layers, thus reducing network bandwidth consumption and energy usage at higher layers.
Solution Approach 2:
The patent introduces a new dimensional approach by creating a data marketplace layer at the control level, transforming the traditional vertical data flow into a horizontal distributed architecture. This adds a new dimension of data management at the edge, allowing parallel processing and reducing the burden on higher layers.
2Ease of operation
If data is transferred to higher layers for analysis, then centralized decision making is achieved, but visibility and readiness of data are reduced limiting analytical effectiveness
Solution Approach 1:
The patent enables control layer devices to serve themselves by creating local data marketplaces where they can store, manage, and analyze their own data without requiring constant transfer to higher layers. This self-service capability improves data visibility and readiness while maintaining analytical effectiveness at the source.
Solution Approach 2:
The patent implements feedback mechanisms where data is made immediately available at the control layer for real-time analysis and decision-making. The data marketplace provides continuous feedback loops between data generation and analysis, improving visibility and readiness without losing behavioral insights.
3Productivity
If conventional centralized data management is used, then system architecture is simple, but controller context cannot be utilized for deeper analytic insights and decision making is inefficient
Solution Approach 1:
The patent makes control layer devices multi-functional by enabling them to not only execute control functions but also serve as data marketplaces and analytical nodes. This universality allows these devices to utilize their local context for deeper analytics while improving decision-making efficiency without requiring a complete architectural overhaul.
4Quantity of substance
If all control layer devices transfer data to higher layers, then centralized data collection is achieved, but network bandwidth limitations prevent handling of massive data volumes
Solution Approach 1:
The patent segments the massive data volume handling task across multiple distributed data marketplaces at control layer devices. Instead of concentrating all data at higher layers, the segmentation approach allows each device to manage its own data locally, collectively handling large volumes without overwhelming the network infrastructure.
Data Source
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AI summary
A system for managing data in an industrial production environment includes a distributed database system stored on a plurality of embedded controller devices. Each respective embedded controller device comprises: a distributed database instance and a database management application. The distributed database instance is configured to store data collected from the industrial production environment by the respective embedded controller device. The database management application is configured to facilitate distributed queries and transactions on the plurality of embedded controller devices.