Factory Anomaly Diagnosis with Two-Stage Detection and Analysis
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Solution Overview
Problem
Existing anomaly diagnosis technologies face a conflicting relationship between computational load and diagnostic accuracy, necessitating a solution that suppresses computational load while ensuring diagnostic accuracy in manufacturing industries.
Innovation Solution
An anomaly diagnosis device and system that divides anomaly diagnosis into two stages: anomaly detection, which requires fewer data and lower computational load, and anomaly analysis, using models like MAHARANOBIS-TAGUCHI for detection and VAE for analysis, with data acquisition and processing optimized for real-time detection and post-anomaly analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If diagnostic accuracy is increased, then anomaly detection precision is improved, but computational load increases
Solution Approach 1:
The patent segments the anomaly diagnosis process into two distinct stages: anomaly detection (real-time, low computational load) and anomaly analysis (post-processing, higher diagnostic accuracy). This segmentation allows the system to maintain low computational load during real-time operation while achieving high diagnostic accuracy during offline analysis, effectively resolving the contradiction between speed and accuracy.
2Speed
If real-time detection is implemented, then response speed is improved, but diagnostic accuracy may be reduced
Solution Approach 1:
The patent implements real-time anomaly detection using a simplified model that prioritizes speed, then performs comprehensive anomaly analysis using a more accurate model in a post-processing stage. This two-stage segmentation enables the system to achieve both real-time response speed and high diagnostic accuracy by performing different functions at different time stages.
Solution Approach 2:
The system performs preliminary anomaly detection in real-time to identify potential issues quickly, then conducts thorough anomaly analysis afterward to determine precise causes. This preliminary action approach ensures that real-time response requirements are met while still achieving high diagnostic accuracy through subsequent detailed analysis.
Data Source
AI summary
This abnormality diagnostic device for diagnosing an abnormality that occurs in a factory acquires data to be used for detecting an abnormality that occurs in a factory, detects an abnormality of a subject of diagnosis by using the data to be used for detecting an abnormality, reports the detected abnormality, acquires data to be used for analyzing an abnormality, and analyzes a candidate abnormality cause by using the data to be used for analyzing an abnormality in a period including a time point at which the abnormality has occurred, or by using the data to be used for analyzing an abnormality and the data to be used for detecting an abnormality in a period including a time point at which the abnormality has been detected.