Achieve Zero Defect Escapes.
Every Single Time.
WatchDog™ Catches What Traditional Inspection Cannot
Your fab produces millions of wafers annually. One undetected defect batch costs millions in scrap and lost yield. WatchDog™ is the only AI inspection system that detects both known AND unknown defects—delivering absolute zero escapees through dual-layer cascading architecture. No blind spots. No surprises. No excuses.
The Critical Gap
Unknown defects from unexpected sources lead to defect escapes, compromising wafer yield and increasing downstream costs.
Equipment Changes
Tool modifications and component replacements introduce novel defect patterns that traditional supervised learning systems cannot detect.
Process Drift
Gradual parameter shifts over time create new defect modes that historical AI models have never encountered, leading to blind spots.
Electrical Variations
Power fluctuations and grounding issues can trigger defects that emerge unpredictably and vary from standard patterns.
Environmental Factors
Temperature, humidity, and vibration changes in fab environments introduce defect modes that require continuous monitoring.
Averroes WatchDog Solution
AI-powered solution that continuously monitors semiconductor fab processes to detect anomalies without requiring pre-labeled defect libraries
Minimal Data Requirements
Starts with few data points and learns from your fab environment. No extensive historical data needed.
Real-time Monitoring
Continuously analyzes wafer data to detect anomalies as they occur, preventing defect escapes.
Rapid Deployment
Deploy advanced AI inspection applications in hours, not months, with minimal data requirements.
Unsupervised to Supervised Learning Pipeline
WatchDog runs alongside your existing supervised models to catch unknown defects that would otherwise escape detection. This creates a continuous learning loop that enhances both systems over time.
Production Data (Real-time wafer/sensor data)
Supervised Engine
Fast, precise classification and detection of known defect types
- Low computational overhead
- Detailed defect categorization
- Production-ready speed
Unsupervised Engine
Anomaly detection flags unknown patterns and anomalies
- Discovers unknown defects
- No historical data required
- Continuous monitoring
Human Validation
Expert review by semiconductor quality engineers
Label Generation
Data enrichment creates labeled dataset for new defect types
Enhanced Detection
Discover how WatchDog™ transforms defect detection with dual-layer architecture
Customer Case Study
Real-world results from leading semiconductor manufacturers
Subtle Process Variation Defects
The Challenge:
A leading photomask manufacturer began encountering unknown defect patterns sporadically across masks used in advanced node production. Traditional inspection systems failed to capture these anomalies, as they represented entirely new patterns absent from historical defect libraries.
Averroes WatchDog Solution:
We implemented a two-layer modeling approach combining supervised learning and our WatchDog anomaly detection system. The supervised model was trained on known defect classes, while WatchDog continuously monitored for any patterns outside of this known defect space, flagging anomalies that traditional inspection systems could not capture.
Key Benefits
Reduces Inspection Overhead
Automated anomaly detection reduces manual review time while maintaining high accuracy standards.
Minimizes Quality Complaints
Catch defects before they reach customers, protecting your reputation and reducing costly returns.
Improves OEE
Increases Overall Equipment Effectiveness by detecting issues early and preventing production losses.
Fast Deployment
Production-ready in hours with minimal data requirements. No lengthy training or data collection needed.
Unknown Defect Detection
Discovers defects that traditional systems miss, adapting automatically to new patterns and variations.
Continuous Learning
System improves over time through feedback loop, constantly enhancing detection capabilities.
Deployment & Integration
Flexible deployment options designed for semiconductor manufacturing environments
Real-time Processing
Immediate detection and alerting of anomalies as they occur in production.
API Integration
Seamless connection to existing MES/SCADA systems via standard APIs.
On-premise Deployment
Complete control over data and processing in your secure fab environment.
Edge Deployment
Real-time processing at fab production line for immediate defect detection.
Containerized Solutions
On-premise deployment for sensitive fab environments using Docker/Kubernetes. Maintain complete data security while leveraging advanced AI capabilities.
WatchDog™ Across Your Fab
From lithography to BEOL—comprehensive defect detection at every critical process step
Post-Lithography
- Stochastic printing failures
- Resist residue patterns
- Micro-bridging detection
- Reticle contamination
Post-Etch
- Grass/fencing textures
- Polymer redeposition
- Chamber drift prediction
- Profile anomalies
Post-CMP
- Novel scratch patterns
- Dishing/erosion trends
- Slurry contamination
- Pad wear monitoring
Post-Deposition
- Film stress defects
- Particle generation
- Thickness non-uniformity
- Delamination detection
BEOL Interconnect
- Void detection
- Via misalignment
- Copper protrusions
- Barrier breakthrough
WatchDog™ vs Traditional Solutions
| Capability | Traditional AOI | WatchDog™ |
|---|---|---|
| Detects unknown defect types | ||
| Real-time production speed | ||
| Requires 100+ defect examples | ||
| Adapts to process changes automatically | ||
| Model retraining time | Weeks | Hours |
| Zero defect escapees guarantee |