Semiconductor Memory Test Case Optimization via Iterative Generation
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Solution Overview
Problem
Current methods for testing semiconductor memory devices during the wafer stage often fail to identify the optimum operating conditions due to the limited number of tests performed, leading to suboptimal choices that can decrease yield and reliability.
Innovation Solution
A method and device that perform tests on semiconductor memory devices using a plurality of cases, generate modeled test results, determine optimum cases, and iteratively generate new cases based on these results, employing a case generator, optimizer, and test operator to refine operating conditions through mutation and recombination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the number of tests is restricted to a limited number, then the testing process is simple and quick, but the accuracy of identifying optimum operating conditions deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-generating multiple test cases with different operating conditions before actual testing begins. The case generator creates a comprehensive set of test cases covering various operating parameters, so that when testing starts, all necessary test scenarios are already prepared and can be executed efficiently without time loss
Solution Approach 2:
The patent uses copying by creating multiple generations of test cases based on optimal cases from previous generations. Instead of testing all possible operating conditions, the system copies and refines promising test cases through iterative generations, focusing testing resources on the most promising scenarios while maintaining comprehensive coverage
2Ease of manufacture
If tests are performed depending on engineer's know how, then the testing process is simple, but the reliability of selected operating conditions deteriorates
Solution Approach 1:
The patent implements feedback through an automated evaluation system that objectively assesses test results and determines optimal cases based on measured performance data. The optimizer analyzes test outcomes and feeds back to the case generator to refine subsequent test cases, replacing subjective engineer judgment with objective, data-driven decision making while maintaining process simplicity
Solution Approach 2:
The system applies self-service by enabling the testing process to automatically generate, evaluate, and refine test cases without continuous human intervention. The case generator, optimizer, and evaluation system work together autonomously to identify optimal operating conditions, reducing reliance on engineer expertise while maintaining or improving reliability
3Measurement precision
If multiple generations of test cases are generated and evaluated, then the accuracy of identifying optimum operating conditions is improved, but the device complexity and processing time increase
Solution Approach 1:
The patent applies segmentation by dividing the testing system into distinct functional modules: a case generator that creates test cases, a test operator that executes tests, an optimizer that analyzes results, and an evaluator that determines optimal cases. This modular segmentation manages system complexity by allowing each component to be developed and maintained independently while working together to achieve high accuracy in identifying optimal operating conditions
Data Source
AI summary
A method of testing a semiconductor memory device is provided. The method includes performing a test according to a plurality of cases corresponding to a first generation and generating modeled test results for the plurality of cases, determining optimum cases from among the plurality of cases based on the modeled test results, and generating a plurality of cases corresponding to a second generation based on the optimum cases.


