Extended FMEA Analysis for Faster Failure Mode Identification
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Solution Overview
Problem
Existing automatic analysis systems face challenges in rapidly identifying failure modes, particularly when multiple sensors detect anomalies, leading to inefficiencies in maintenance operations and prolonged identification times for inexperienced users.
Innovation Solution
An information processing device with an extended FMEA database that includes information on check items, their association with failure effects, and previous events, allowing for rapid identification of failure modes by calculating score values and prioritizing potential causes based on these associations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensors are used to detect failure effects, then failure detection capability is improved, but failure mode identification speed deteriorates
Solution Approach 1:
The system pre-establishes a database containing check items, failure effects, and their associations before actual failure occurs. When failure is detected, the system quickly queries this pre-prepared database to identify failure modes, avoiding time-consuming analysis during critical moments
Solution Approach 2:
The patent introduces check items as intermediary elements between sensors and failure modes. Sensors detect failure effects, which are then matched with check items in the database, and these check items lead to failure mode identification. This intermediary layer structures the information flow and accelerates diagnosis
2Measurement precision
If multiple check items are inspected to identify failure, then detection accuracy is improved, but identification time increases
Solution Approach 1:
The system changes the parameter of information organization by creating a database with structured associations between check items, failure effects, and failure modes. This structured parameter transformation enables efficient querying and rapid identification without sacrificing accuracy
Solution Approach 2:
The database is pre-populated with all possible check item-failure effect-failure mode relationships before operation. During failure analysis, the system only needs to query this pre-organized information rather than analyzing all possibilities from scratch, significantly reducing identification time
3Measurement precision
If comprehensive failure knowledge is stored, then diagnostic accuracy is improved, but system complexity increases
Solution Approach 1:
The comprehensive failure knowledge is segmented into discrete, structured database records with specific fields for check items, failure effects, and failure modes. This segmentation organizes complex information into manageable, queryable units that improve diagnostic accuracy without overwhelming system complexity
Solution Approach 2:
The system transforms unstructured failure knowledge into structured database parameters with defined relationships. This parameterization enables efficient storage and retrieval of comprehensive diagnostic information while maintaining system manageability through standardized data structures
Data Source
AI summary
In order to enable rapid identification of a failure mode, the present disclosure proposes an information processing device comprising: an extended FMEA database containing, on a per-failure effect basis, information on check items, information on the degree of association between the check items and the failure effect, and information on previous events of the check items; and a processor that obtains information on a check item confirmed as an event and that identifies a failure mode corresponding to a failure effect on the basis of the obtained check item, wherein the processor executes a first process for extracting information on the failure effect related to the check item from the extended FMEA database, a second process for calculating a score value for the failure effect extracted in the first process by referring to information on the degree of association between the check item and the failure effect, and a third process for presenting, on the basis of the score value, the failure mode corresponding to the failure effect extracted in the first process (see FIG. 2).