Intelligent PLC On-Device Data Analytics and Contextualization
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Solution Overview
Problem
Conventional programmable logic controllers (PLCs) in industrial automation systems are inadequate in handling and analyzing data, leading to inefficiencies, loss of important data points, and increased costs due to hardware and software limitations, which result in sub-optimal automation system performance and complex data analytics at higher layers.
Innovation Solution
An Intelligent PLC is configured to perform on-device data analysis and storage, incorporating a data historian and analytics functions, enabling contextualized data generation, compression, and adjustment of data generation parameters, allowing for efficient storage and real-time analytics directly on the control layer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data is collected and transmitted through automation layers at conventional PLCs, then data can be accessed by higher automation layers, but data loss occurs and network bandwidth and storage capacity demands increase
Solution Approach 1:
The patent segments data handling functions between edge devices (PLCs) and cloud platforms. PLCs perform local data processing, filtering, and preliminary analytics, transmitting only essential processed data to the cloud. This segmentation reduces unnecessary data transmission while maintaining data availability at higher layers.
Solution Approach 2:
The patent introduces a new dimensional approach by enabling PLCs to perform advanced analytics and data processing functions traditionally reserved for higher automation layers. This shifts the data handling paradigm from vertical data flow to a multi-dimensional architecture where processing occurs at multiple levels simultaneously.
2Quantity of substance
If data is compressed at higher automation layers, then storage capacity demands are reduced, but important data points are lost
Solution Approach 1:
The patent applies preliminary data processing and filtering at the PLC level before data leaves the control layer. Essential data points are identified and preserved through intelligent filtering algorithms, ensuring that only relevant data is transmitted and stored, thereby preventing data loss while reducing storage demands.
Solution Approach 2:
PLCs perform self-service data processing by autonomously filtering, aggregating, and prioritizing data locally. This self-service capability enables the system to maintain data quality without requiring external intervention from higher automation layers for data selection and filtering.
3Productivity
If PLCs perform data processing, then data analytics capability is improved, but development and customization costs of higher layer systems increase
Solution Approach 1:
The patent implements a universal data processing framework where PLCs can perform multiple functions including data collection, filtering, preliminary analytics, and contextualization. This multi-functionality reduces the need for specialized hardware and software at higher layers, thereby reducing overall system development and customization costs.
Solution Approach 2:
The patent enables dynamic adjustment of data processing parameters at PLCs based on system needs. Processing intensity, data sampling rates, and analytics depth can be modified without hardware changes, providing flexibility that reduces customization costs while maintaining high analytics capability.
4Measurement precision
If resolution and sampling rate of data acquisition are increased, then machine events detection accuracy is improved, but data volume and processing demands increase
Solution Approach 1:
The patent implements dynamic data acquisition where sampling rates and resolution are adjusted in real-time based on process conditions. During critical events, sampling rate increases to capture detailed information; during stable operation, sampling rate decreases to reduce data volume. This dynamic approach maintains detection accuracy while managing data volume.
Solution Approach 2:
The patent applies partial data acquisition by collecting high-resolution data only when necessary for detecting specific machine events. For routine monitoring, reduced sampling rates are used. This selective approach ensures accurate event detection while avoiding the data volume burden of continuous high-resolution sampling.
Data Source
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AI summary
A method of operating an intelligent programmable logic controller over a plurality of scan cycles includes creating, by the intelligent programmable logic controller, a process image area in a volatile computer-readable storage medium operably coupled to the intelligent programmable logic controller. The intelligent programmable logic controller then updates the process image area during each scan cycle with contents comprising data associated with a production unit. The contents of the process image area are stored by the intelligent programmable logic controller during each scan cycle on a non-volatile computer-readable storage medium operably coupled to the intelligent programmable logic controller. The intelligent programmable logic controller annotates the contents of the process image area with automation system context information to generate contextualized data.