Automation Event Analysis Using Modular PLC Data Extraction
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Solution Overview
Problem
The complexity of automation software in technical devices leads to time-consuming and resource-intensive processes in identifying the cause of operation events, which often require deep technical knowledge across multiple fields, making it difficult to analyze operation events effectively.
Innovation Solution
A system that analyzes operation events by extracting and conditioning data from automation software and physical sensors, using analysis software that can be executed on separate computers, cloud systems, or automation devices, with modular analysis modules and tools for generating new modules, ensuring rapid identification and analysis of operation events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If automation software complexity increases to handle more complex automation tasks, then adaptability and functionality improve, but analysis time and resource consumption increase
Solution Approach 1:
The patent segments the analysis system into modular analysis modules, each responsible for specific types of operation events. The automation device is divided into separate analysis components that can independently process different event types, allowing parallel analysis and reducing overall analysis time while maintaining the ability to handle complex automation tasks.
Solution Approach 2:
The patent introduces an intermediary analysis system that sits between the complex automation software and the operators. This intermediary automatically collects, analyzes, and presents information about operation events, reducing the time operators need to spend analyzing events while the automation software maintains its full complexity and adaptability.
2Adaptability or versatility
If automation software complexity increases to handle more complex automation tasks, then adaptability and functionality improve, but resource consumption increases
Solution Approach 1:
The analysis system is segmented into specialized modules that only activate when specific types of operation events occur. This modular approach reduces overall resource consumption by avoiding unnecessary analysis activities while maintaining the ability to handle diverse automation tasks through the appropriate module selection.
Solution Approach 2:
The system applies partial analysis by focusing only on the specific aspects of operation events that are relevant to the current situation. Rather than performing complete comprehensive analysis on all events, the system applies analysis only where needed, reducing resource consumption while maintaining effective monitoring of complex automation operations.
3Measurement precision
If deepening technical knowledge is required in multiple fields for operation event analysis, then analysis accuracy improves, but ease of operation deteriorates
Solution Approach 1:
The analysis system performs self-service by automatically collecting data from the automation device, analyzing operation events using built-in analysis modules, and generating results without requiring external expert intervention. This maintains high analysis accuracy through systematic multi-field analysis while making the system easy to operate for users regardless of their technical knowledge in multiple fields.
Solution Approach 2:
The patent introduces an intermediary analysis system that bridges the gap between complex multi-field technical requirements and simple user operation. This intermediary automatically performs the complex analysis requiring knowledge in information technology, machine technology, and installation technology, then presents results in an easily understandable format to operators.
4Reliability
If comprehensive data collection from automation software and physical sensors is performed, then analysis completeness improves, but device complexity increases
Solution Approach 1:
The system segments data collection into separate modules: one for automation software data and another for physical sensor data. Each module independently collects its designated data type, ensuring comprehensive coverage while keeping the overall system structure manageable through clear separation of data sources and processing paths.
Data Source
AI summary
The system described herein relates to analyzing operation events during operation of a technical device, in particular of a machine or installation, where the technical device includes at least one automation device, such as a programmable logic controller. The automation device is enabled to execute automation technology tasks using automation software that is executable by the automation device. Analysis software extracts data from operation data obtained using sensors in the physical world, from the automation software and/or from data traffic of the automation device and conditions the data, where the conditioning includes storing the extracted data in a database, such as a relational database, and the data stored in the database are evaluated with regard to the operation event by the analysis software.