Industrial Automation Data Scheduling for Bandwidth-Limited Control Loops
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Solution Overview
Problem
Industrial automation systems face bandwidth constraints when transmitting data to the cloud, as it can divert resources from primary functions and stress components, particularly in upper processing levels where control loops require timely adjustments.
Innovation Solution
Implementing a method to categorize operations in industrial automation systems and schedule data transmission based on operation types (constant speed, cyclic, batch, variable speed) to minimize interference, using edge devices for local bandwidth management and optimizing data transmission during periods of spare bandwidth, and adjusting frequency based on component lifespan and anomaly detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If data is transmitted directly to cloud computing device by collecting component, then data transmission is simplified, but bandwidth of industrial automation component is consumed and primary function performance is interfered with
Solution Approach 1:
An edge computing device is introduced as an intermediary between the collecting component and the cloud computing device. The edge computing device receives data from the collecting component, processes it locally, and then transmits it to the cloud. This intermediary approach allows the collecting component to maintain its primary function without bandwidth consumption for data transmission, while still enabling data to reach the cloud for analysis and model updating.
2Measurement precision
If data transmission frequency is increased to improve model accuracy, then measurement precision is improved, but network overload and component stress increase
Solution Approach 1:
The system implements periodic data transmission based on the operational characteristics of the industrial automation component. Instead of continuous transmission, data is transmitted at specific intervals or under specific conditions (e.g., when the component is in a stable state or during scheduled maintenance windows). This periodic approach maintains sufficient model accuracy while preventing network overload and reducing stress on system components.
Solution Approach 2:
The system transmits only the necessary portion of data required for model accuracy rather than all available data. The edge computing device selectively transmits data that is most relevant for model training and updating, filtering out redundant information. This partial action approach achieves the required measurement precision with reduced data transmission volume, thereby maintaining system stability.
3Loss of information
If data is transmitted during operation to maintain real-time monitoring, then information availability is improved, but bandwidth constraints and control loop timing are violated
Solution Approach 1:
The edge computing device performs preliminary data processing and buffering before transmission to the cloud. Data is collected and pre-processed during operation, but actual transmission to the cloud is scheduled for times when it will not interfere with control loop timing. This preliminary action ensures that information is prepared and ready for transmission without causing timing violations in the control loops.
Solution Approach 2:
The data transmission process is segmented into different priorities and timeframes. Critical data for real-time monitoring is handled separately from data intended for cloud-based model updating. The segmentation allows the system to maintain real-time information availability for control purposes while scheduling non-critical data transmissions during periods when bandwidth is available and control loop timing is not constrained.
Data Source
AI summary
Techniques for data transmission within an industrial automation system include modeling or simulating, in accordance with a model, a plurality of devices performing one or more operations in an industrial automation system, determining, for a first operation of the one or more operations and from a plurality of categories, a category for the first operation, sending a request to the industrial automation system for data associated with the first operation at a time, wherein the data and time are determined based on the category of the first operation, receiving, from the industrial automation system, the requested data, and modifying the model based on the received data.