Controller Health Monitoring via Signal Segmentation
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Solution Overview
Problem
Existing maintenance practices for manufacturing equipment, particularly in the electronics/optoelectronics industry, fail to accurately monitor controller health, leading to false alarms and undetected problems, which can result in reduced yield and production downtime.
Innovation Solution
A method and system that collect control and sensing signals over time, segment them to identify control steps, calculate a health index based on these signals and user manual information, and generate a warning signal when the health index exceeds a predetermined threshold, enabling timely maintenance and preventing equipment failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing maintenance practices are used for controller monitoring, then equipment maintenance can be performed, but false alarms are transmitted and problems fail to be detected accurately
Solution Approach 1:
The monitoring method segments controller operation into discrete control steps, analyzing signal characteristics within each step to determine health status. This segmentation enables precise detection of abnormalities at specific operational phases, improving both measurement precision and alarm reliability by focusing analysis on relevant operational segments rather than continuous signals.
Solution Approach 2:
The system implements feedback by comparing actual control and sensing signals against expected characteristics to generate health assessments. This feedback mechanism continuously monitors controller performance and provides accurate alerts only when genuine deviations from normal operation are detected, eliminating false alarms while maintaining high detection accuracy.
2Reliability
If equipment monitoring is enhanced to detect problems accurately, then equipment breakdown can be prevented, but monitoring complexity increases
Solution Approach 1:
The monitoring system performs self-service by automatically collecting control and sensing signals, segmenting them into control steps, and calculating health status without requiring external intervention. This self-contained approach enhances equipment reliability through continuous monitoring while managing complexity through automated processing rather than manual analysis systems.
Solution Approach 2:
The system calculates controller health status in advance by analyzing control and sensing signals before equipment failure occurs. This preliminary assessment allows maintenance to be scheduled proactively, improving reliability while using straightforward signal analysis methods that avoid the need for complex real-time intervention systems.
3Measurement precision
If continuous monitoring of control signals is performed, then controller health can be assessed accurately, but data processing time and computational resources increase
Solution Approach 1:
By segmenting continuous control and sensing signals into discrete control steps, the system processes data in manageable segments rather than analyzing entire continuous signal streams. This segmentation maintains health assessment accuracy by analyzing relevant operational phases while significantly reducing computational burden and processing time compared to continuous signal analysis.
Solution Approach 2:
The system applies partial action by focusing analysis only on the essential characteristics of control steps rather than processing every detail of continuous signals. This selective approach achieves sufficient health assessment accuracy without the excessive computational resources required for complete signal analysis, optimizing the balance between precision and processing efficiency.
Data Source
AI summary
A method for monitoring a manufacturing apparatus includes collecting a control signal, of a controller and a corresponding sensing signal, of the manufacturing apparatus over a predetermined period of time; segmenting the control signal and the corresponding sensing signal to obtain at least one control step; calculating a character of the controller based on at least one of the control signal, the sensing signal, the at least one control step, or information from a user manual; generating, based on the character, a health index indicating health of the controller; and generating a warning signal when the health index exceeds a predetermined threshold.