Electrical Characterization Data Quantile Visualization
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Solution Overview
Problem
The volume of data generated during quality control in volume manufacturing of electrical components is unwieldy and unhelpful for making business and manufacturing decisions, making it difficult to synthesize insights for improving product quality.
Innovation Solution
The method involves obtaining electrical characterization data, processing it to determine quantile statistics, generating a graphical user interface for visualization, and displaying this interface to facilitate quality control actions such as maintenance, process selection, or supplier feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If electrical characterization data is collected during quality control, then measurement precision is improved, but device complexity increases due to the unwieldy volume of data generated
Solution Approach 1:
The patent extracts only the essential statistical information (quantile statistics) from the large volume of electrical characterization data, separating the useful quality metrics from the unwieldy raw data. This allows maintaining measurement precision while reducing data complexity for decision-making.
Solution Approach 2:
Instead of trying to manage and analyze the raw electrical characterization data directly, the patent inverts the approach by computing quantile statistics first and then visualizing these aggregated statistics. This inversion transforms the problem from managing large data volumes to presenting concise statistical summaries.
2Loss of information
If quantile statistics are calculated and visualized, then loss of information is reduced, but device complexity increases due to processing requirements
Solution Approach 1:
The patent replaces complex manual data analysis with automated computational processing of quantile statistics. The system automatically calculates and visualizes statistical metrics, substituting mechanical human analysis with efficient computational methods that reduce information loss while managing complexity.
Solution Approach 2:
The patent introduces graphical user interfaces and visualizations as intermediaries between the raw electrical characterization data and human decision-makers. These visual intermediaries preserve manufacturing trend information in an easily interpretable format without requiring complex direct data analysis.
3Ease of operation
If traditional quality control methods are used, then ease of operation is maintained, but productivity decreases due to difficulty in synthesizing insights
Solution Approach 1:
The patent enables the quality control system to automatically compute quantile statistics and generate visualizations without requiring manual data synthesis. The system serves itself by automatically transforming raw electrical characterization data into actionable quality insights, maintaining operational simplicity while improving productivity.
Solution Approach 2:
The patent performs preliminary computation of quantile statistics and generation of visualizations before quality control decisions are needed. This preliminary processing of data into meaningful statistics allows operators to make decisions quickly without having to synthesize insights from raw data at the moment of decision-making.
Data Source
AI summary
Techniques for performing quality control in the manufacture of electrical components are provided. The techniques include obtaining electrical characterization data from the electrical components by using test equipment to measure electrical responses of the electrical components and processing, using at least one processor, the electrical characterization data to determine quantile statistics for the electrical characterization data. The techniques additionally include generating, using the at least one processor, a graphical user interface containing a visualization of the determined quantile statistics and displaying, using a display device, the generated graphical user interface.