Real-Time Outlier Detection and Product Re-Binning
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Solution Overview
Problem
Existing manufacturing processes struggle with inconsistent device characteristics across different manufacturing locations due to limited access to external test results data, leading to inconsistent binning and potential quality issues.
Innovation Solution
A system and method for real-time outlier detection and product re-binning, which involves establishing binning limits based on external test results data, applying these limits in real-time to test results data, and identifying outliers for separate binning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional binning methods are used with limited local test data, then manufacturing process simplicity is maintained, but binning consistency and quality across different manufacturing locations deteriorate
Solution Approach 1:
The patent combines test data from multiple manufacturing locations into a centralized database, merging local binning decisions with global quality standards. This allows binning limits to be established based on comprehensive external test results data while maintaining real-time local application, resolving the contradiction between binning consistency and system complexity.
Solution Approach 2:
The system creates universal binning limits that can be applied across different manufacturing locations and device types. The binning system serves multiple functions: quality control, outlier detection, and standardized decision-making across diverse manufacturing contexts, improving consistency without proportionally increasing complexity.
2Manufacturing precision
If real-time outlier detection is implemented, then quality consistency is improved, but processing time and computational resources increase
Solution Approach 1:
The system pre-establishes binning limits and outlier detection criteria before actual testing begins. By preparing decision rules and thresholds in advance based on historical data, the system eliminates the need for complex real-time calculations during device testing, maintaining quality consistency while minimizing processing time.
Solution Approach 2:
The patent replaces complex real-time statistical analysis with pre-computed binning limits and standardized comparison operations. Instead of performing heavy computational analysis during testing, the system uses straightforward comparisons against established limits, reducing processing time while maintaining detection accuracy.
3Measurement precision
If comprehensive external test data is collected and analyzed, then binning accuracy is improved, but data processing complexity and resource requirements increase
Solution Approach 1:
The system extracts only the essential parameters and trends from comprehensive external test data to establish binning limits, rather than processing the entire raw dataset. This extraction approach maintains binning accuracy by focusing on critical quality indicators while reducing data processing complexity and resource requirements.
Solution Approach 2:
The patent transforms raw test data into standardized parameters and binning limits that simplify subsequent analysis. By changing the form of data from raw measurements to processed binning criteria, the system improves binning accuracy through comprehensive data analysis while reducing the complexity of real-time data processing.
Data Source
AI summary
A method for analyzing device test data includes accessing a core analytics rule that is based on manufacturing data of a plurality of devices. Each of the plurality of devices are produced in one of a plurality of manufacturing facilities and are of a same type as a first device being tested on a tester. The method also includes receiving initial test results of a plurality of other devices of a same type tested at a testing facility, generating, based on the initial test results, an edge analytics rule, modifying the core analytics rule based on the edge analytics rule, wherein the modified core analytics rule including modified binning limits, applying the modified core analytics rule to testing data obtained by testing the first device, and determining, based on applying the modified core analytics rule, that the first device is an outlier with respect to the modified binning limits.