Industrial Machine Setting Change Tracking for Event Diagnosis
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Solution Overview
Problem
Identifying the specific setting data responsible for a predetermined event, such as an alarm or performance degradation, in industrial machines is laborious due to the large number of setting data parameters involved.
Innovation Solution
An industrial machine management system that collects and analyzes changeable setting data, determines changes over time, identifies change information related to predetermined events, and outputs this information to assist in event analysis, utilizing a network-connected management server, controller, and user terminal to register, collect, and display relevant data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all setting data parameters are collected and analyzed to identify the cause of predetermined events, then the completeness of diagnostic information is improved, but the time and effort required for analysis increases
Solution Approach 1:
The system performs preliminary actions by continuously monitoring and recording all setting data changes in a database before predetermined events occur. When an event happens, the analysis only needs to query pre-collected data rather than gathering information in real-time, significantly reducing diagnostic time while maintaining complete information availability.
Solution Approach 2:
The system creates copies of setting data at different time points and stores them in a database. Instead of analyzing the original complex set of all parameters, the system copies only the relevant changed parameters identified through change detection algorithms, reducing the information processing burden while maintaining diagnostic completeness.
2Measurement precision
If change detection is performed on all setting data at every time point, then the accuracy of identifying event-causing changes is improved, but the computational complexity and data processing load increases
Solution Approach 1:
The system extracts only the changed parameters from the complete setting data set by comparing current data with historical data stored in the database. This extraction approach maintains high accuracy in identifying relevant changes while significantly reducing computational complexity by processing only the differential data rather than the entire parameter set at each time point.
Solution Approach 2:
The monitoring system segments the analysis by dividing setting data into categories (changed vs. unchanged parameters) and processing them differently. By segmenting the data processing task, the system achieves accurate change detection for relevant parameters while avoiding unnecessary processing of unchanged parameters, thereby reducing overall computational complexity.
3Reliability
If detailed change information for all parameters is stored and analyzed, then the thoroughness of event analysis is improved, but the storage requirements and data management burden increases
Solution Approach 1:
The system extracts and stores only the changed parameters in the database rather than maintaining complete copies of all setting data at all time points. This extraction strategy ensures that all relevant information for thorough event analysis is preserved while significantly reducing the total data storage volume and simplifying data management operations.
Data Source
AI summary
An industrial machine management system includes circuitry that collects changeable setting data of an industrial machine, determines, based on the setting data at each time point of multiple time points, whether a change has been made to the setting data, obtains change information regarding the change when the change is determined as having been made to the setting data, determines whether a predetermined event has occurred in the industrial machine, identifies, when the predetermined event is determined as having occurred, the change information such that the change information is related to the predetermined event, and outputs the change information that is identified.