Design Support Device for Automated Defect Knowledge Utilization
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Solution Overview
Problem
Existing fault tree analysis (FTA) and failure mode and effects analysis (FMEA) methods struggle to effectively utilize accumulated defect knowledge in design work, especially when FTA or FMEA is not implemented frequently, leading to time-consuming causal factor examinations with user-dependent variations.
Innovation Solution
A design support device that evaluates defects in design models using a causal model database, attribute information extraction, and relevance/importance degree evaluation to identify high-relevance and high-importance defect factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If FTA or FMEA is implemented in design work to utilize defect knowledge, then reliability improvement is achieved, but the time required for precise examination of causal factors increases and results vary depending on individual users
Solution Approach 1:
The patent introduces an automated analysis device as an intermediary between the design model and the defect knowledge base. This device automatically extracts attribute information from design models, queries the defect knowledge base, and presents relevant defect factors to designers, eliminating the need for manual FTA/FMEA execution while maintaining reliability improvements
Solution Approach 2:
The patent replaces the manual mechanical process of FTA/FMEA with an automated information processing system. The system automatically performs attribute extraction, database querying, and result presentation, substituting human analysts with computational processes that eliminate time consumption and subjectivity while preserving reliability benefits
2Reliability
If a large number of defect factors are presented to users, then comprehensive defect coverage is achieved, but it takes time to precisely examine the causal factors and results vary depending on individual users
Solution Approach 1:
The patent extracts only the essential attribute information from design models that is relevant to defect analysis. By selectively extracting only necessary attributes rather than all possible information, the system presents a focused set of relevant defect factors to designers, improving both coverage and ease of examination
Solution Approach 2:
The patent changes the parameter of information presentation by automatically filtering and ranking defect factors based on their relevance to the specific design model. This transformation converts a static, comprehensive but overwhelming list into a dynamic, prioritized set of critical factors that are easier to examine while maintaining comprehensive defect coverage
3Productivity
If FTA or FMEA is not implemented frequently in design work, then design productivity is maintained, but accumulated defect knowledge from the past cannot be effectively utilized
Solution Approach 1:
The patent enables the design process to automatically access and utilize accumulated defect knowledge without requiring dedicated FTA/FMEA implementation. The system self-services by automatically querying the defect knowledge base using extracted attributes from design models, ensuring continuous utilization of historical defect information while maintaining design productivity
Solution Approach 2:
The patent performs preliminary actions by pre-building a defect knowledge base from historical data before design work begins. This preliminary preparation enables automatic utilization of accumulated defect knowledge during subsequent design activities without requiring additional time investment, resolving the contradiction between productivity and knowledge utilization
Data Source
AI summary
Provided is a design support device capable of effectively utilizing defect knowledge in design work and reducing man-hours required for precise examination of a presented analysis result and variation depending on an individual user. A design support device that evaluates a defect that can occur in a design model generated by a design tool and a factor of the defect is configured to include a causal model database that stores a causal model expressing a defect that can occur in a design target by using a causal relationship in which, due to a certain phenomenon, another phenomenon occurs, an attribute information extraction unit that extracts attribute information regarding a design target from the design model, and a relevance degree evaluation unit that extracts, for the causal model, a causal relationship including a content matching with the extracted attribute information as a causal relationship having a high relevance degree to the design model.