Defect Knowledge Linking and Summarization for Process Insight
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Solution Overview
Problem
Existing systems fail to effectively organize and utilize defect knowledge from inspection results to prevent future defects and improve manufacturing processes, as they do not provide insights into the processes causing defects.
Innovation Solution
A method and system using AI models to link defect records with work information, generating summaries using summarization keywords to circulate defect knowledge intelligently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If workers manually organize and inspect defect notes, then defect knowledge can be captured, but the burden on workers increases significantly
Solution Approach 1:
The system enables defect knowledge to organize and circulate itself automatically without human intervention. AI models process defect records, extract insights, and generate summaries autonomously, allowing the knowledge management system to serve itself rather than requiring workers to manually organize notes
Solution Approach 2:
The patent replaces the manual mechanical process of organizing defect notes with automated AI-based processing. Machine learning models substitute for human workers in analyzing defect records, extracting patterns, and generating knowledge summaries, thereby eliminating the burdensome manual work while preserving defect knowledge
2Productivity
If defect notes are recorded without linking to work information, then inspection results are captured, but insights into process causes are lost
Solution Approach 1:
The system merges defect records with corresponding work information by linking them through AI processing. This combination integrates inspection results with process context, enabling the system to not only detect defects quickly but also analyze their root causes by examining associated work instructions and process data together
Solution Approach 2:
The patent implements feedback loops where defect information is continuously linked with work information to improve future manufacturing processes. The system uses extracted insights to provide feedback on process improvements, creating a closed-loop system that prevents recurrence of defects while maintaining high detection speed
3Extent of automation
If existing MES systems are used to record inspection results, then automation is achieved, but advanced defect knowledge organization capabilities are lacking
Solution Approach 1:
The patent transforms the basic MES recording function into a multi-functional defect knowledge management system. The same automated recording infrastructure is extended to perform multiple functions including AI-based defect analysis, pattern recognition, knowledge extraction, and predictive insights, making the system adaptable to various defect management needs while maintaining automation
Solution Approach 2:
The system changes the parameters of defect data processing from simple recording to advanced AI-based analysis. By transforming how defect information is processed, stored, and utilized, the system maintains the automation benefits of MES while gaining sophisticated defect knowledge organization capabilities through modified data processing parameters and AI model integration
Data Source
AI summary
A method for performing defect summarization, the method comprising: receiving, by a processor, defect records associated with an operation; receiving, by the processor, work information associated with the operation linking, by the processor, the defect records and the work information using a first Artificial Intelligence (AI) model to generate linked information; and performing, by the processor, summary generation using a second AI model to generate work summary using summarization keywords, the defect records, and the work information, as input to the second AI model.