Color Map Process Anomaly Diagnosis for Noisy Manufacturing Data
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Solution Overview
Problem
In manufacturing processes like iron steel, existing statistical models struggle to accurately predict anomalies due to high variance and noise, making it difficult to distinguish true anomalies from prediction results.
Innovation Solution
A process anomalous state diagnostic device that uses deviation indexes to create a color map displaying temporal changes in a hierarchical structure, allowing operators to visually recognize anomalies and differentiate between true anomalies and noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If comprehensive determination with a large number of statistical models is performed, then the coverage of complex manufacturing process phenomena is improved, but the prediction accuracy deteriorates due to variance and noise among models
Solution Approach 1:
The patent segments the complex manufacturing process into multiple sub-processes, each monitored by dedicated statistical models. Instead of using one comprehensive model that suffers from high variance, the system divides the monitoring task into smaller, more focused models that each handle specific process aspects, thereby improving overall prediction accuracy while maintaining comprehensive coverage.
Solution Approach 2:
The patent introduces a color map visualization as an intermediary between the statistical models and the operator. This intermediary transforms complex prediction results from multiple models into an intuitive visual format that highlights anomalies, allowing operators to interpret results accurately without being overwhelmed by the variance and noise inherent in comprehensive multi-model analysis.
2Adaptability or versatility
If multiple statistical models are used to cover complex phenomena, then the comprehensiveness of diagnosis is improved, but the ease of operation deteriorates due to difficulty in understanding prediction results
Solution Approach 1:
The patent employs color changes in the color map visualization to represent different levels of anomaly detection. By assigning specific colors to different prediction deviation levels, the system transforms complex multi-model results into an easily interpretable visual format, greatly improving ease of operation while maintaining comprehensive diagnostic coverage.
Solution Approach 2:
The patent transitions from numerical prediction results to a two-dimensional color map visualization, adding spatial and visual dimensions to the data presentation. This dimensional transformation allows operators to quickly comprehend complex diagnostic information through visual patterns rather than numerical analysis.
3Reliability
If deviation indexes from multiple models are analyzed, then the detection capability for true anomalies is improved, but the device complexity increases due to noise from variance among models
Solution Approach 1:
The patent merges the results from multiple statistical models into a unified color map visualization. By combining individual model predictions into a single integrated visual representation, the system maintains high detection capability while reducing the perceived complexity for operators, as they interact with one unified interface rather than multiple separate model outputs.
Data Source
AI summary
A process anomalous state diagnostic device configured to diagnose an anomalous state of a process based on deviation indexes for the magnitude of deviation from a reference that is a normal state of the process includes: a color mapping unit configured to configure a two-dimensional matrix that has a first axis as an axis of a temporal factor including time and that has a second axis as an axis of an item of each deviation index, associate each cell of the matrix with data for an item of the deviation index and the temporal factor, and allocate a color in accordance with the magnitude of the deviation index to each cell of the matrix; and a color map display unit configured to display a color map produced by the color mapping unit.