PLC Soft-Sensor Contextualization for Early Quality Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional programmable logic controllers (PLCs) face limitations in handling and analyzing large amounts of data, leading to inefficient data processing, loss of important data points, and increased computational demands, which results in delayed quality problem detection and increased development costs for business analytics.
Innovation Solution
An intelligent PLC system that selects and updates soft-sensor values during each scan cycle, annotates them with automation system context information, and applies data analytics to adjust data generation parameters, enabling efficient data storage and contextualization, and performing analytics directly on the control layer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional PLCs process and transmit all automation system data to higher layers, then data completeness is improved, but network bandwidth consumption and storage capacity demands increase significantly
Solution Approach 1:
The patent segments data into two categories: process data (sensor readings, control outputs) and context data (control program variables, parameter values). This segmentation allows selective transmission where only essential process data is sent to higher layers, while context data remains at the control layer, reducing network bandwidth consumption while maintaining data completeness for control operations.
Solution Approach 2:
The patent extracts and retains context data locally at the PLC level, separating it from process data that needs to be transmitted upward. This extraction allows the system to maintain complete data availability for control decisions while minimizing the volume of data transmitted through the network to higher automation layers.
2Measurement precision
If conventional PLCs transmit all control program variables to higher automation layers, then data fidelity is improved, but computational demands and development costs increase
Solution Approach 1:
The patent implements local quality by maintaining high data fidelity locally at the PLC where control decisions are made, while providing summarized or selective data to higher layers. The full-fidelity context data remains available locally for precise control operations, while higher layers receive sufficient data for monitoring and analysis without the complexity of processing all control variables.
Solution Approach 2:
The patent introduces a data contextualization layer at the PLC that acts as an intermediary between internal control variables and external higher-layer systems. This intermediary selectively translates and transmits only the most relevant data upward, maintaining data fidelity for control purposes while reducing the complexity burden on higher automation layers and decreasing development costs.
3Device complexity
If conventional PLCs monitor only standard sensor data, then system complexity is reduced, but quality problem detection is delayed
Solution Approach 1:
The patent applies preliminary action by continuously monitoring control program variables and context data at the PLC level, where real-time control decisions are made. This allows quality problems to be detected immediately when they affect control parameters, before they propagate to higher layers or manifest as finished product defects, thereby reducing quality detection time without significantly increasing system complexity.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A method of operating an intelligent programmable logic controller over a plurality of scan cycles includes the intelligent programmable logic controller selecting one or more softsensors available in a control program corresponding to a production unit, each soft-sensor comprising a local parameter or variable used by the control program. The intelligent programmable logic controller determines updated soft-sensor values corresponding to the one or more soft-sensors during each scan cycle and stores those values during each scan cycle on a non-volatile computer-readable storage medium operably coupled to the intelligent programmable logic controller. Additionally, the intelligent programmable logic controller annotates the updated soft-sensor values with automation system context information to generate contextualized data.