Defect Relationship Analysis for Manufacturing Root Cause Detection
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Solution Overview
Problem
Conventional defect management systems are inadequate in efficiently managing large numbers of manufacturing defects, often leading to improper identification and handling of defects, as well as a failure to identify root causes due to the lack of sufficient rules-based systems for analyzing relationships between defects.
Innovation Solution
A computer-based system that applies a rules-based approach to classify and analyze relationships between manufacturing defects, using a method to determine relatedness levels and suggest potential correlations, with an ongoing learning process to improve defect issue identification based on user inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional defect management systems store large numbers of defects in databases, then defect information can be accessed by quality engineers, but the systems cannot efficiently identify relationships between defects or root causes due to lack of rules-based analysis
Solution Approach 1:
The patent replaces manual analysis of defect relationships with an automated rules-based system that uses computer processors to execute algorithms for comparing defect data objects, determining relatedness levels, and identifying issues. This substitution enables efficient analysis of large volumes of defect data without manual intervention.
Solution Approach 2:
The patent introduces defect data objects as intermediary structures that contain standardized defect information and enable systematic comparison. These objects serve as mediators between raw defect data and relationship analysis, allowing the rules-based system to efficiently process and compare defects through structured attributes.
2Ease of operation
If manual methods are used to analyze defect relationships, then quality engineers can review defect information, but the process is inefficient and root causes are rarely identified
Solution Approach 1:
The patent implements a self-service system where the rules-based engine automatically performs defect relationship analysis without requiring quality engineers to manually examine each defect. The system autonomously compares defect data objects, determines relatedness, identifies issues, and presents results, freeing engineers from tedious manual analysis while maintaining ease of use through intuitive interfaces.
Solution Approach 2:
The patent incorporates feedback mechanisms where the system presents identified issues and relationships to quality engineers for review. Engineers can validate or correct the system's findings, and this feedback is used to refine and improve the rules-based analysis over time, enhancing both efficiency and accuracy.
3Loss of information
If detailed defect information is stored for each defect item, then comprehensive defect data is available, but the complexity of analyzing relationships among many defects increases
Solution Approach 1:
The patent segments defect information into standardized defect data objects with structured attributes and fields. Each defect is divided into manageable components (e.g., defect type, location, severity, associated equipment) that can be independently compared and analyzed. This segmentation reduces analysis complexity while preserving comprehensive defect information.
Solution Approach 2:
The patent transforms detailed defect information into standardized parameters and attributes that can be systematically compared. By converting unstructured or semi-structured defect data into standardized parameters with defined data types and validation rules, the system enables efficient relationship analysis without losing important defect details.
Data Source
AI summary
Systems and methods are provided for identifying relationships between defects. The system may obtain defect items and associated information. Defect items may be compared to one another based on their attributes to determine how related they are. According to the comparisons, defect items may be grouped together into issue items for further analysis by a user. The system may further update a defect comparison model according to user interaction with defect items.