Failure Diagnostic Apparatus Path Segmentation for Investigation Efficiency
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Solution Overview
Problem
Conventional failure diagnosis software only outputs high-accuracy failure location candidates, making it inefficient for analysts to investigate potential failures outside these locations, as they cannot efficiently explore regions with lower accuracy scores.
Innovation Solution
A failure diagnostic apparatus that calculates and outputs multiple path types, including first and second failure candidate paths and a normal path, allowing analysts to visually investigate and prioritize potential failure locations based on accuracy scores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional failure diagnosis software only outputs high-accuracy failure location candidates, then the output precision is improved, but the analyst cannot efficiently investigate potential failures in lower-scoring regions
Solution Approach 1:
The patent segments failure candidate paths into multiple categories (first failure candidate paths with high agreement rates, second failure candidate paths with lower agreement rates, and normal paths) based on their agreement rates with simulation conditions. This segmentation allows analysts to systematically investigate different regions of interest with appropriate detail levels, maintaining high accuracy for primary candidates while enabling efficient exploration of secondary regions.
Solution Approach 2:
The patent applies local quality by providing different levels of diagnostic information for different path types. High-accuracy first failure candidate paths receive detailed analysis with multiple input patterns, while lower-accuracy second failure candidate paths and normal paths receive progressively less detailed information. This localized information quality optimization improves overall investigation efficiency without sacrificing the accuracy of primary failure candidates.
2Ease of operation
If multiple path types are calculated and output, then the ease of operation for investigation is improved, but the device complexity increases
Solution Approach 1:
The patent implements partial action by calculating and outputting different quantities of path information based on agreement rates. For first failure candidate paths with high agreement rates, multiple input patterns and detailed path information are calculated. For second failure candidate paths and normal paths with lower agreement rates, fewer input patterns and less detailed information are provided. This partial calculation approach reduces overall computational complexity while maintaining investigative efficiency for the most critical failure candidates.
3Loss of information
If detailed path information is provided for all candidates, then the information completeness is improved, but the loss of time for processing increases
Solution Approach 1:
The patent changes the parameter of information detail level based on the agreement rate parameter. For paths with high agreement rates (first failure candidate paths), detailed information including multiple input patterns and comprehensive path analysis is provided. For paths with lower agreement rates (second failure candidate paths and normal paths), less detailed information is provided. This parameter-based information scaling maintains diagnostic completeness for critical cases while significantly reducing processing time for lower-priority cases.
Data Source
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AI summary
A failure diagnostic apparatus includes a path calculation unit which calculates, for each input pattern to a diagnosis target cell, a path affecting an output value of the diagnosis target cell when a failure is assumed as an activation path, a path classification unit which classifies the activation path associated with the input pattern for which the diagnosis target cell has passed a test and the activation path associated with the input pattern for which the diagnosis target cell has failed the test, a path narrowing unit which calculates a first failure candidate path, a second failure candidate path and a normal path of the diagnosis target cell based on classified activation paths, and a result output unit which outputs information on the first failure candidate path, the second failure candidate path and the normal path.