Fuse Configuration Detection for Precise Circuit Trimming
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for detecting optimal electrical fuse configurations in semiconductor devices are time-consuming and costly, failing to effectively improve circuit characteristics due to inefficiencies in evaluating and generating fuse configurations.
Innovation Solution
A method and system that evaluate characteristics of multiple fuse configurations, calculate contribution information, and generate new fuse configurations using an evaluation module, selection module, contribution module, and variation module to optimize circuit trimming, incorporating machine learning for improved efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional methods are used to detect optimal fuse configurations, then fuse trimming can be performed, but the process is time-consuming and costly
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing contribution information that quantifies the influence of each fuse configuration on circuit characteristics before actual trimming. This pre-computed data enables faster optimization during the actual trimming process, reducing the time required to detect optimal fuse configurations while maintaining manufacturing precision.
Solution Approach 2:
The patent replaces conventional trial-and-error mechanical testing methods with a computational approach using contribution information calculations. By substituting physical iterative testing with algorithmic optimization based on pre-calculated contribution data, the system achieves faster fuse configuration detection without sacrificing trimming precision.
2Manufacturing precision
If conventional methods are used to detect optimal fuse configurations, then fuse trimming can be performed, but the cost is high
Solution Approach 1:
The patent reduces manufacturing cost by performing preliminary calculations of contribution information that quantifies fuse configuration influences. This pre-computed data eliminates the need for expensive iterative physical testing, thereby reducing overall manufacturing costs while maintaining the precision required for circuit characteristic trimming.
Solution Approach 2:
The patent substitutes expensive physical testing and trial-and-error methods with a computational optimization approach using contribution information. This replacement of mechanical testing with algorithmic processing significantly reduces manufacturing costs while preserving the ability to achieve precise circuit trimming.
3Manufacturing precision
If multiple fuse configurations are evaluated to improve circuit characteristics, then better performance can be achieved, but the complexity of the process increases
Solution Approach 1:
The patent replaces complex physical evaluation of multiple fuse configurations with a computational system that uses contribution information to guide optimization. This substitution simplifies the overall process by replacing intricate physical testing and manual analysis with automated calculations that systematically evaluate configuration impacts.
Solution Approach 2:
The patent introduces contribution information as an intermediary that mediates between fuse configurations and circuit characteristics. This intermediary quantifies the relationship, allowing the system to evaluate multiple configurations more systematically and with less complexity by relying on pre-calculated influence data rather than direct physical testing of each configuration.
Data Source
AI summary
A method of generating a fuse configuration for trimming a circuit includes evaluating characteristics, corresponding to each of a plurality of fuse configurations, of the circuit trimmed based on the plurality of fuse configurations respectively, selecting at least one fuse configuration from among the plurality of fuse configurations, based on a result of the evaluating the characteristics of the circuit, calculating a contribution information by calculating a degree of influence of fuse data of each of the plurality of fuse configurations to the characteristics of the circuit, based on the plurality of fuse configurations and the characteristics, and generating at least one new fuse configuration, based on the selected at least one fuse configuration and the contribution information.


