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Plasma Etching Endpoint Detection

Stop at the Right Moment. Control Every Nanometer.

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SEE THE GLOW. KNOW THE ENDPOINT. PREVENT OVER-ETCHING.

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In plasma etching, precision is everything. Etching for too long or stopping too early can compromise critical dimensions, reduce layer selectivity, and ruin yield. Traditional endpoint detection methods, like time-based controls or optical emission spectroscopy (OES), are often reactive, not predictive. AI-powered Plasma Etching Endpoint Detection leverages real-time camera feeds to visually monitor plasma characteristics. By analyzing glow patterns, intensity shifts, and arc behavior using machine learning, it predicts when to stop the etch, improving accuracy and protecting underlying layers.

OUR HOLISTIC VIEW TO CHALLENGES & FEATURES

Challenges

Inaccurate Time-Based Etch Control

Inaccurate Time-Based Etch Control

Static timers don’t account for batch variation, chamber condition, or etch rate drift.

Delayed Reaction with Traditional Sensors

Delayed Reaction with Traditional Sensors

Emission-based or pressure-based systems often detect endpoint after it’s already passed.

Undetected Micro-Etch Failures

Undetected Micro-Etch Failures

Subtle anomalies in plasma arcs or intensity gradients can signal defects, if you can see them.

No Visual Feedback for Engineers

No Visual Feedback for Engineers

Operators lack real-time visual understanding of chamber dynamics during critical steps.

Features

Real-Time Plasma Glow Monitoring

Real-Time Plasma Glow Monitoring

Tracks changes in plasma color, intensity, and pattern using high-contrast vision feeds.

AI-Based Glow Pattern Recognition

AI-Based Glow Pattern Recognition

Learns typical endpoint behavior across recipes and alerts for deviation or completion.

Multi-Recipe Adaptability

Multi-Recipe Adaptability

Adapts to different gases, pressures, and materials (e.g., Si, GaN, III-V) with retrainable models.

Visual Alert System with Chamber Sync

Visual Alert System with Chamber Sync

Triggers system alerts and interacts with tool PLC to suggest or automate etch stop action.

WHO BENEFITS FROM PLASMA ETCHING ENDPOINT DETECTION?

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  • Etch Process Engineers – Gain precise, real-time control over endpoint decisions for every material and layer.
  • Tool Maintenance Teams – Monitor plasma chamber health visually and detect anomalies before tool failure.
  • Yield Management Specialists – Reduce variability caused by inconsistent etching depth across wafers and lots.
  • Cleanroom Operators – Get real-time alerts without having to manually monitor screen trends.

BUILDING AND DEPLOYING PROCESS

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Chamber-Specific Vision Planning

Chamber-Specific Vision Planning

We collaborate with your tool vendor or internal automation team to identify optimal camera mount points within or outside the plasma chamber viewport, ensuring thermal safety and visibility.

Visual Calibration & Etch Recipe Mapping

Visual Calibration & Etch Recipe Mapping

Each etch recipe is captured and analyzed to build a baseline library of endpoint glow patterns, pressure shifts, and color transitions under different gases and process parameters.

AI Model Training for Material-Specific Patterns

AI Model Training for Material-Specific Patterns

The model is trained on known endpoint glow profiles across Si, SiN, SiO₂, and other layers, helping detect subtle shifts that indicate true endpoint vs. noise.

Feedback Loop to Tool Controller

Feedback Loop to Tool Controller

Once the AI model predicts an endpoint, it sends real-time flags to the tool controller, triggering a suggestive or automatic stop action. All endpoint data is logged for traceability and process audits.

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