EOS-TDR Waveform Analysis for Chip Soft Defect Detection
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Solution Overview
Problem
Existing methods fail to effectively detect soft defects in devices during manufacturing, particularly in chip production, which can affect long-term sustainability and reliability, especially in critical industries like automotive.
Innovation Solution
Employing electro-optic sampling based time-domain reflectometry (EOS-TDR) to measure and analyze device under test (DUT) waveforms, comparing them with reference waveforms to identify soft defects through cross-correlation and statistical analysis, such as Hotelling's T2-test, enabling early detection of defects that functional testing misses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If functional testing is used to detect defects, then manufacturing process is simple, but soft defects are not detected
Solution Approach 1:
The patent replaces traditional functional testing methods with time-domain reflectometry (TDR) measurement. Instead of applying functional stimuli and observing device behavior, the system uses electrical signal reflection analysis to directly detect physical defects in interconnect structures. This substitution enables detection of soft defects that functional testing misses, while maintaining manufacturing process simplicity.
Solution Approach 2:
The patent introduces TDR measurement as an intermediary detection method between manufacturing and final product testing. By measuring signal reflections during manufacturing, the system creates an intermediate quality checkpoint that identifies soft defects without requiring complex functional test setups or operating the device under test conditions.
2Measurement precision
If TDR measurement is used to detect soft defects, then defect detection sensitivity is improved, but measurement complexity increases
Solution Approach 1:
The patent creates reference waveforms from known good devices and compares them against waveforms from devices under test. This copying approach allows the system to detect subtle deviations indicating soft defects without requiring complex analysis algorithms. The reference copy serves as a baseline for comparison, simplifying the measurement evaluation process while maintaining high detection sensitivity.
Solution Approach 2:
The patent transforms the complex problem of soft defect detection into a simpler parameter comparison task. By converting defect detection into a waveform parameter comparison (amplitude, timing, shape characteristics) against reference values, the system achieves high measurement precision using relatively simple measurement equipment and analysis methods.
3Reliability
If traditional manufacturing testing is used, then manufacturing speed is maintained, but defect detection coverage is insufficient
Solution Approach 1:
The patent performs TDR measurements during the manufacturing process itself, before devices are fully assembled or require functional testing. This preliminary detection approach identifies soft defects early in production, allowing for immediate sorting or rework without delaying subsequent manufacturing steps or requiring additional testing stages, thus maintaining productivity while improving quality assurance.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
EOS-TDR provides superior sensitivity and resolution for detecting soft defects, allowing for early identification of defects under normal conditions, improving manufacturing quality and reliability of chips.
Implementation Method 1
measuring the device under test using at least one time-domain reflectometry measurement of the device under test to generate a device under test waveform
Data Source
AI summary
A method, apparatus, and/or system for soft defects modeling of measurements using time-domain reflectometry. Electro-Optic Sampling based Time-Domain Reflectometry (EOS-TDR) may quickly detect soft defects in a chip under test. For example, EOS-TDR may detect soft defects in each pin from a trace-structure point at a relatively high resolution. To interpret the results in a time sensitive manner, a reference model for chips may be established from chips that are known to have met the expected quality standards. Through automated analysis of the features of the device under test waveform, soft defects of a chip may be detected that would be otherwise undetectable under time constraints, temperature variations, applied current variations, applied voltage variations, vibration variations, moisture variations, or any other kind of possible variation.