Dynamic Threshold Abnormality Prediction for Device Usage
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Solution Overview
Problem
Existing systems for predicting abnormalities in devices, such as image forming apparatuses, face challenges in accurately predicting abnormalities due to varying usage conditions, as they rely on fixed threshold values that do not account for the timing and frequency of device usage.
Innovation Solution
A system that calculates a first increment value of device usage over a predetermined period and determines abnormalities based on this value, using a similar apparatus search unit to find comparable devices and calculate an increment value, thereby setting a dynamic threshold for abnormality detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed threshold value is used to predict device abnormalities, then the system is simple to operate, but the prediction accuracy deteriorates due to varying usage conditions
Solution Approach 1:
The patent applies dynamics by transitioning from a static fixed threshold to a dynamic threshold that adapts to varying usage conditions. The system calculates a usage-based threshold value that changes according to the device's actual usage pattern, allowing accurate abnormality detection across different usage scenarios without requiring complex manual configuration
Solution Approach 2:
The system implements self-service by automatically learning and adapting to each device's usage patterns without external intervention. The threshold calculation unit autonomously computes appropriate thresholds based on accumulated usage data, eliminating the need for manual threshold setting or complex user configuration while maintaining high prediction accuracy
2Adaptability or versatility
If a fixed threshold value is used for abnormality prediction, then the system is easy to implement, but it cannot appropriately predict abnormalities when usage frequency varies
Solution Approach 1:
The patent applies parameter changes by modifying the threshold parameter from a fixed value to a dynamically calculated value based on usage frequency. The threshold calculation unit adjusts the threshold parameter according to actual usage data, enabling the system to adapt to varying usage patterns while maintaining accurate abnormality detection across different operational conditions
3Loss of time
If the number of uses is compared with a fixed threshold value, then the prediction method is simple, but the timing of abnormality occurrence cannot be accurately predicted
Solution Approach 1:
The system applies preliminary action by accumulating and analyzing usage data over time before making abnormality predictions. The threshold calculation unit prepares adaptive thresholds in advance based on historical usage patterns, enabling accurate timing prediction of abnormalities before they occur without requiring complex real-time analysis
Data Source
AI summary
A system predicts an abnormality of a first device. The system includes processing circuitry. The processing circuitry calculates a first increment value of a number of uses of the first device included in a first apparatus, based on a first total number of uses of the first device within a first predetermined period. The processing circuitry determines an abnormality of the first device based on the first increment value.