Lithographic Process Yield Optimization via Uncertainty Metrics

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Solution Overview

Problem

Current lithographic processes face challenges in optimizing yield due to limitations in measuring and controlling performance parameters across substrates, particularly in determining optimal metrology target positions and process windows, which affects the accuracy and efficiency of pattern transfer and device manufacturing.

Innovation Solution

A method is introduced to determine parameter fingerprints, process window fingerprints, and probability metrics to improve yield by optimizing the placement and measurement of metrology targets based on uncertainty and process window analysis, allowing for targeted adjustments in the lithographic process to ensure performance parameters remain within specified ranges.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If conventional process optimization techniques are used to adjust imaging parameters, then the root mean square error of performance parameters is optimized, but the yield improvement is not optimal due to not considering uncertainty and process window

Engineering Contradiction:

Improveperformance parameter controlVSAvoidyield

Core Design Contradiction:

Manufacturing precisionVSProductivity

Solution Approach 1:

The invention transforms the optimization approach by changing from minimizing RMS error to minimizing a probability metric that incorporates uncertainty fingerprints and process window fingerprints. This parameter transformation allows the system to account for both measurement uncertainty and process variability, leading to better yield optimization.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The invention introduces intermediate computational steps including determining uncertainty fingerprints, process window fingerprints, and probability metrics. These intermediaries bridge the gap between raw measurement data and optimal process adjustments, enabling more informed decision-making for yield improvement.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Manufacturing precision

If measurements are taken across the substrate to optimize performance parameters, then manufacturing precision improves, but the complexity of determining optimal metrology target positions increases

Engineering Contradiction:

Improveperformance parameter measurementVSAvoidmetrology target positioning

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The invention applies local quality by determining uncertainty fingerprints and process window fingerprints at specific locations across the substrate. This allows the system to identify high-risk areas and focus measurements and optimizations where they are most needed, rather than treating the entire substrate uniformly.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The invention performs preliminary actions by determining uncertainty fingerprints and process window fingerprints before final optimization. This advance preparation allows the system to identify problematic areas and plan measurement strategies accordingly, reducing the complexity of subsequent optimization steps.

Inventive Principle:

Principle #10Preliminary action

3Stability of the object's composition

If traditional RMS error optimization is applied, then performance parameter uniformity improves, but the probability of parameters exceeding allowable ranges is not minimized

Engineering Contradiction:

Improveperformance parameter uniformityVSAvoidcompliance with allowable ranges

Core Design Contradiction:

Stability of the object's compositionVSReliability

Solution Approach 1:

The invention applies beforehand cushioning by incorporating process window fingerprints that define allowable ranges. The optimization targets a probability metric that ensures parameters stay within these ranges with high confidence, providing a safety margin against variations and uncertainties.

Inventive Principle:

Principle #11Beforehand cushioning (Prior cushioning)

Solution Approach 2:

The invention uses feedback by continuously determining uncertainty fingerprints from measurements and using this information to update the probability metric. This closed-loop approach ensures that optimization decisions are based on actual measured uncertainty, improving both uniformity and compliance.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS11480884B2Method for optimization of a lithographic process

Publication Date: 2022.10.25 ASML NETHERLANDS BV

AI summary

A method for improving the yield of a lithographic process, the method including: determining a parameter fingerprint of a performance parameter across a substrate, the parameter fingerprint including information relating to uncertainty in the performance parameter; determining a process window fingerprint of the performance parameter across the substrate, the process window being associated with an allowable range of the performance parameter; and determining a probability metric associated with the probability of the performance parameter being outside an allowable range. Optionally a correction to the lithographic process is determined based on the probability metric.