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Semiconductor
Semiconductor Yield Improvement
Implementation: 10 months
Industry: Semiconductor
Yield Rate Crisis
A semiconductor fab was experiencing low yield rates on advanced node production, with complex process interactions making root cause analysis extremely difficult.
Key Pain Points
- Yield rates 15% below industry benchmarks
- Complex 500+ step process with interdependencies
- Weeks required for root cause analysis
- High cost per wafer making yield critical
- Difficulty correlating defects to process variations
AI-Powered Yield Management
Tesan AI deployed a comprehensive yield management system using AI to identify yield limiters and predict defects before they occur.
Key Features Deployed
- Multi-variate process correlation analysis
- Real-time defect prediction
- Automated root cause analysis
- Process fingerprinting for each wafer
- Equipment matching optimization
- Predictive maintenance for process tools
Yield Excellence
Measurable outcomes from the implementation
12%
Yield Improvement
Absolute yield increase
45%
Faster Root Cause
Days instead of weeks
$50M
Annual Value
From improved yield and reduced cycle time
80%
Defect Prediction
Accuracy for critical defect types
Implementation Journey
A structured approach to transformation
Phase 1
Data Integration
Connection to all process and metrology tools
Phase 2
Baseline Analysis
Understanding current yield limiters
Phase 3
Model Development
AI models for yield prediction and optimization
Phase 4
Process Integration
Closed-loop control implementation
Phase 5
Continuous Learning
Ongoing model refinement
Use Cases Implemented
Specific applications within this implementation
Lithography process optimizationEtch uniformity controlCMP process monitoringMetrology correlationEquipment matching
Ready to Achieve Similar Results?
Let's discuss how Tesan AI can transform your semiconductor operations.