ATE Error Detection in Compressed Data Sequences
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Solution Overview
Problem
Current automatic test equipment (ATE) systems struggle to identify the source of errors in compressed data sequences from integrated circuits, as compressed data does not provide detailed error or failure information, leading to inefficiencies in test time and requiring additional manipulations to obtain uncompressed fail information.
Innovation Solution
The ATE generates a second stimulus signal based on detected errors to the device under test (DUT), which responds with uncompressed data sequences at error positions, allowing for seamless execution of production and diagnostic test modes without stopping the test run, enabling efficient error identification and collection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data compression is used to reduce test time, then productivity is improved, but measurement precision deteriorates because compressed data does not provide detailed error information
Solution Approach 1:
The test process is segmented into two distinct phases: a production test phase using compressed data for high-speed error detection, and a diagnostic test phase using uncompressed data for detailed error analysis. This segmentation allows each phase to optimize for its specific purpose without compromise.
Solution Approach 2:
The system performs preliminary error detection using compressed data in the production test phase, identifies error positions, and then uses this information to guide the subsequent diagnostic test phase. This preliminary action enables targeted retrieval of detailed error information only where needed.
2Measurement precision
If uncompressed data is used to identify error sources, then measurement precision is improved, but productivity deteriorates due to increased test time
Solution Approach 1:
The system extracts only the necessary uncompressed data segments corresponding to detected error positions, rather than retrieving or processing all uncompressed data. This extraction approach minimizes the time penalty while ensuring complete error source identification.
Solution Approach 2:
The system uses feedback from the production test phase (error positions detected in compressed data) to control the diagnostic test phase, directing it to focus specifically on identified error locations. This feedback mechanism prevents redundant processing of error-free data segments.
3Measurement precision
If individual error-specific tests are performed to obtain uncompressed fail information, then measurement precision is improved, but productivity deteriorates due to additional test time and manipulations
Solution Approach 1:
The system merges the production test and diagnostic test into a coordinated two-phase process, where the diagnostic test is triggered and controlled by results from the production test. This merging eliminates the need for separate, time-consuming individual error tests while maintaining complete error analysis capability.
Data Source
AI summary
A device under test—DUT—, comprising the steps of receiving a first data sequence from the DUT in response to a first stimulus signal, wherein the data of a plurality of internal data sequences of the DUT is compressed into the first data sequence, comparing the first data sequence with expected data and for detecting errors in the first data sequence, and providing a second stimulus signal to the DUT in order to instruct the DUT to generate a second data sequence that comprises uncompressed data of the plurality of the internal data sequences at the positions where the errors have been detected.