Industrial Control Load Balancing for Processing Bottlenecks
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Solution Overview
Problem
Industrial automation systems face challenges in efficiently balancing processing loads and optimizing energy usage across components, leading to inefficiencies and potential bottlenecks in production and energy consumption.
Innovation Solution
An industrial control system that connects components via a network, allowing for data exchange and analysis to distribute processing loads and adjust operations based on real-time data, using load balancing algorithms and autonomous control to optimize performance across hierarchical levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If processing loads are concentrated in fewer control systems, then device complexity is reduced, but productivity decreases due to bottlenecks
Solution Approach 1:
The patent segments the processing load across multiple control systems instead of concentrating it in a single system. Each control system handles a portion of the total processing load, which distributes the workload and prevents bottlenecks while maintaining manageable complexity at each node.
Solution Approach 2:
The patent combines multiple control systems into a coordinated network where each system contributes to the overall processing capacity. By merging the capabilities of multiple systems and enabling them to work together through load balancing, the system achieves higher total productivity than any single system could provide alone.
2Productivity
If real-time data exchange is implemented across all components, then productivity improves through optimization, but use of energy increases due to continuous communication
Solution Approach 1:
The patent implements partial data exchange by having control systems exchange only the specific processing load information necessary for load balancing decisions, rather than continuously exchanging all possible data. This reduces energy consumption while still enabling the optimization needed to maintain productivity.
3Productivity
If processing loads are distributed across multiple control systems, then productivity increases by avoiding bottlenecks, but device complexity increases
Solution Approach 1:
The patent implements a feedback mechanism where control systems periodically exchange processing load information and use this feedback to dynamically adjust the distribution of processing loads. This automated feedback loop enables the system to maintain optimal productivity across multiple distributed systems without requiring complex manual coordination or centralized control.
4Ease of operation
If autonomous control is implemented at hierarchical levels, then ease of operation improves, but device complexity increases
Solution Approach 1:
The patent enables control systems to autonomously monitor their own processing loads and self-adjust by distributing loads to other systems based on current conditions. This self-service capability allows the system to operate autonomously without requiring external intervention, improving ease of operation while the modular autonomous units keep individual complexity manageable.
Data Source
AI summary
An industrial control system may receive processing information from at least two control systems associated with at least two components within an industrial automation system. The processing information may include a processing load value for each of the at least two control systems. The industrial control system may then distribute processing loads associated with the at least two control systems when a total processing load between the at least two control systems is unbalanced.