Industrial Data Feed Tagging for Autonomous Automation Control
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Solution Overview
Problem
Industrial automation systems lack effective methods to efficiently manage and optimize operations across various components and hierarchical levels, leading to inefficiencies in energy usage and production processes due to a lack of awareness and communication between devices.
Innovation Solution
An industrial control system that connects and communicates with various components within an industrial automation network, allowing for data analysis and contextualization across different scopes, enabling devices to recognize each other, share data, and adjust operations autonomously to optimize performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If devices in industrial automation systems operate independently without communication, then device simplicity is maintained, but operational efficiency and energy optimization deteriorate due to lack of system-wide awareness
Solution Approach 1:
The system segments data communication into structured data feeds with specific types (e.g., process data, alarm data, event data) and uses data tags to categorize information. This segmentation allows devices to selectively receive and process only relevant data, improving operational efficiency while maintaining manageable system complexity through organized information flow.
Solution Approach 2:
The system implements continuous feedback loops where devices broadcast their state information through data feeds and other devices respond by adjusting their operations. This feedback mechanism enables real-time optimization of energy usage and production processes, with devices autonomously adapting based on system-wide conditions without requiring complex centralized control.
2Loss of information
If real-time data broadcasting is implemented across all devices, then operational awareness and optimization improve, but data transmission overhead and processing load increase
Solution Approach 1:
The system applies local quality by allowing different devices to subscribe to and receive only the specific data feeds and tags relevant to their function and location in the system. This selective data reception reduces unnecessary data transmission and processing overhead while maintaining complete system awareness where each device has knowledge of information pertinent to its operations.
Solution Approach 2:
The data feed mechanism serves multiple functions simultaneously: it broadcasts system-wide information, enables selective subscription based on device needs, provides real-time monitoring capabilities, and supports autonomous decision-making. This multi-functionality reduces the need for separate communication protocols and mechanisms, lowering overall data transmission energy requirements.
3Productivity
If autonomous control capabilities are added to devices, then production optimization improves, but device complexity and control system requirements worsen
Solution Approach 1:
Devices are equipped with autonomous control capabilities that allow them to independently analyze received data feeds, make decisions about their operations, and adjust their behavior without external intervention. This self-service approach enables production optimization at the device level, reducing the need for complex centralized control systems while maintaining relatively simple individual device architecture.
Data Source
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AI summary
An industrial control system may receive data associated with at least one component within an industrial automation system. The industrial control system may then determine whether the data is associated with at least one of a plurality of data tags, such that the at least one of the plurality of data tags describes at least one characteristic of the data. The industrial control system may then broadcast the data and the at least one of the plurality of data tags in a data feed channel when the data is associated with the at least one of the plurality of data tags.