Implementation Plan
Overview
This implementation plan breaks down the semiconductor AI ecosystem into discrete, manageable coding tasks that build incrementally toward a complete solution. Each task focuses on specific code implementation that can be executed by a development team.
Tasks
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[ ] 1. Set up project structure and core infrastructure
- Create directory structure for microservices architecture
- Set up Docker containerization for each service
- Configure Kubernetes deployment manifests
- Implement basic logging and monitoring infrastructure
- Requirements: 7.2, 7.6, 9.5
[ ] 2. Implement data ingestion pipeline foundation
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[ ] 2.1 Create ETL pipeline service skeleton
- Implement Apache Airflow DAG structure for batch processing
- Create database connection utilities for Oracle, SQL Server, PostgreSQL
- Write data validation and cleansing functions
- Implement error handling and retry mechanisms
- Requirements: 2.1, 2.9, 2.10
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[ ] 2.2 Implement SEMI SECS/GEM protocol adapters
- Write SECS/GEM message parsing and handling code
- Create MES system integration interfaces
- Implement real-time data extraction from manufacturing systems
- Write unit tests for protocol handling
- Requirements: 2.1, 1.2
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[ ] 2.3 Create stream processing service for real-time data
- Implement Apache Kafka producers and consumers
- Write Apache Flink stream processing jobs
- Create real-time anomaly detection algorithms
- Implement data aggregation and event correlation logic
- Requirements: 2.2, 2.3, 9.4
[ ] 3. Implement data storage layer
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[ ] 3.1 Set up data warehouse schema and connections
- Design and implement star schema for analytical queries
- Create fact tables for process measurements and test results
- Implement dimension tables for equipment, recipes, lots, wafers
- Write database migration scripts and version control
- Requirements: 3.4, 3.5, 9.10
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[ ] 3.2 Implement data lake storage with Apache Iceberg
- Set up Iceberg table structures for raw, curated, and analytics zones
- Implement data partitioning and retention policies
- Create data lineage tracking functionality
- Write data quality monitoring and validation code
- Requirements: 3.4, 3.5, 9.1
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[ ] 3.3 Create vector database integration for RAG system
- Implement vector database connections (Pinecone/Weaviate/Chroma)
- Write embedding generation and storage functions
- Create similarity search and retrieval algorithms
- Implement document indexing and metadata management
- Requirements: 1.3, 3.6, 3.7, 3.8
[ ] 4. Implement LLM integration and RAG system
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[ ] 4.1 Create LLM model serving infrastructure
- Implement model loading and inference using TensorRT/vLLM
- Create GPU resource management and auto-scaling logic
- Write model versioning and deployment automation
- Implement LoRA adapter loading for domain-specific fine-tuning
- Requirements: 1.1, 1.5, 7.2, 7.5
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[ ] 4.2 Implement RAG engine with semantic search
- Create query understanding and intent classification modules
- Implement semantic search across vector database
- Write context ranking and selection algorithms
- Create response generation with source attribution
- Requirements: 1.3, 3.6, 3.7, 3.8
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[ ] 4.3 Integrate semiconductor domain knowledge
- Implement SEMI and JEDEC standards knowledge base
- Create process terminology and equipment specification embeddings
- Write domain-specific query expansion and processing
- Implement semiconductor-specific response validation
- Requirements: 1.2, 1.4, 3.1, 3.2
[ ] 5. Implement ML model services for manufacturing analytics
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[ ] 5.1 Create yield prediction models
- Implement machine learning models for wafer-level yield prediction
- Write feature engineering for process parameters and metrology data
- Create model training pipelines with cross-validation
- Implement model evaluation and performance monitoring
- Requirements: 8.1, 6.6, 6.7
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[ ] 5.2 Implement anomaly detection for process excursions
- Write multivariate statistical analysis algorithms
- Create machine learning anomaly detection models
- Implement real-time scoring and alert generation
- Write model retraining and drift detection logic
- Requirements: 8.2, 6.8, 6.9
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[ ] 5.3 Create equipment predictive maintenance models
- Implement time-series forecasting for equipment health
- Write sensor data preprocessing and feature extraction
- Create failure prediction models using historical patterns
- Implement maintenance scheduling optimization algorithms
- Requirements: 8.4, 2.8, 6.6
[ ] 6. Implement computer vision for wafer map analysis
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[ ] 6.1 Create defect classification models
- Implement CNN models for defect type classification
- Write image preprocessing and augmentation pipelines
- Create training data management and labeling tools
- Implement model evaluation and confusion matrix analysis
- Requirements: 8.5, 8.8, 2.6
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[ ] 6.2 Implement spatial pattern recognition
- Write algorithms for systematic vs. random defect detection
- Create wafer map visualization and analysis tools
- Implement equipment fingerprint detection algorithms
- Write spatial correlation and clustering analysis
- Requirements: 8.8, 6.3, 6.4
[ ] 7. Create API gateway and service mesh
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[ ] 7.1 Implement API gateway with authentication
- Set up Kong or similar API gateway infrastructure
- Implement JWT-based authentication and authorization
- Create rate limiting and throttling mechanisms
- Write API documentation and versioning support
- Requirements: 4.1, 7.7, 9.7
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[ ] 7.2 Create service mesh for microservices communication
- Implement Istio or similar service mesh
- Create service discovery and load balancing
- Implement circuit breaker patterns and retry logic
- Write distributed tracing and monitoring
- Requirements: 7.6, 9.5, 9.7
[ ] 8. Implement user interfaces and dashboards
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[ ] 8.1 Create conversational AI chat interface
- Implement React/Vue.js frontend with WebSocket connections
- Create natural language query processing interface
- Write multi-turn conversation management
- Implement file upload functionality for wafer maps and reports
- Requirements: 4.3, 6.1, 6.2
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[ ] 8.2 Build analytics dashboard for manufacturing insights
- Create real-time equipment health monitoring dashboards
- Implement yield trend analysis and forecasting visualizations
- Write process parameter correlation heatmaps
- Create defect pattern visualization tools
- Requirements: 6.1, 6.2, 6.3, 6.4
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[ ] 8.3 Implement alert and notification system
- Create Apache Kafka-based event streaming for alerts
- Write alert classification and severity scoring
- Implement multi-channel notification delivery (email, SMS, Slack)
- Create alert escalation and acknowledgment workflows
- Requirements: 6.9, 8.2, 8.4
[ ] 9. Implement MLOps and model governance
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[ ] 9.1 Create model registry and versioning system
- Implement MLflow model registry integration
- Write model versioning and metadata management
- Create model deployment automation pipelines
- Implement A/B testing framework for model comparison
- Requirements: 7.6, 7.9
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[ ] 9.2 Implement automated model training pipelines
- Create scheduled retraining workflows using Apache Airflow
- Write data drift detection and model performance monitoring
- Implement automated feature engineering pipelines
- Create model validation and testing automation
- Requirements: 1.6, 7.6, 7.9
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[ ] 9.3 Create model monitoring and observability
- Implement model performance metrics collection
- Write prediction accuracy and bias monitoring
- Create model explainability and interpretability tools
- Implement automated model rollback mechanisms
- Requirements: 7.6, 7.9, 9.7
[ ] 10. Implement security and compliance features
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[ ] 10.1 Create data encryption and access control
- Implement encryption at rest and in transit
- Write role-based access control (RBAC) system
- Create audit logging and compliance reporting
- Implement data masking and anonymization tools
- Requirements: 1.7, 1.8, 4.1
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[ ] 10.2 Implement ITAR/EAR compliance features
- Create data classification and handling procedures
- Write export control validation and reporting
- Implement secure data transfer protocols
- Create compliance audit trails and documentation
- Requirements: 1.8, 4.1
[ ] 11. Create testing and validation framework
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[ ] 11.1 Implement comprehensive test suites
- Write unit tests for all service components
- Create integration tests for data pipelines
- Implement end-to-end testing for user workflows
- Write performance and load testing scripts
- Requirements: 5.2, 5.3, 5.4
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[ ] 11.2 Create data quality and validation testing
- Implement data pipeline testing and validation
- Write model accuracy and bias testing frameworks
- Create synthetic data generation for testing
- Implement automated regression testing
- Requirements: 2.10, 5.1, 5.4
[ ] 12. Implement deployment and infrastructure automation
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[ ] 12.1 Create CI/CD pipelines
- Implement GitLab CI or GitHub Actions workflows
- Write automated testing and deployment scripts
- Create infrastructure as code using Terraform
- Implement blue-green deployment strategies
- Requirements: 5.1, 5.5, 7.6
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[ ] 12.2 Set up monitoring and observability
- Implement Prometheus and Grafana monitoring stack
- Create application performance monitoring (APM)
- Write log aggregation and analysis tools
- Implement distributed tracing for microservices
- Requirements: 9.7, 9.5
[ ] 13. Create knowledge base integration and management
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[ ] 13.1 Implement document processing pipeline
- Write OCR and NLP processing for PDF documents
- Create automated document ingestion and indexing
- Implement version control and change detection
- Write multilingual document processing support
- Requirements: 3.6, 3.7, 3.8, 3.10
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[ ] 13.2 Create knowledge graph implementation
- Implement Neo4j or Amazon Neptune graph database
- Write relationship extraction and entity linking
- Create graph-based query and reasoning algorithms
- Implement knowledge graph visualization tools
- Requirements: 3.7, 3.8
[ ] 14. Implement advanced analytics and optimization
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[ ] 14.1 Create process optimization algorithms
- Implement Bayesian optimization for recipe parameters
- Write design of experiments (DOE) automation
- Create multi-objective optimization algorithms
- Implement chamber matching optimization
- Requirements: 8.3, 8.7, 6.7
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[ ] 14.2 Implement virtual metrology system
- Create machine learning models for metrology prediction
- Write sensor fusion and data correlation algorithms
- Implement real-time prediction and validation
- Create measurement uncertainty quantification
- Requirements: 8.10, 6.6, 6.7
[ ] 15. Create final system integration and testing
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[ ] 15.1 Implement end-to-end system integration
- Connect all microservices and validate data flow
- Create comprehensive system health checks
- Implement disaster recovery and backup procedures
- Write system performance optimization
- Requirements: 5.5, 9.5, 9.9
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[ ] 15.2 Conduct user acceptance testing preparation
- Create user training materials and documentation
- Implement user feedback collection mechanisms
- Write system administration and maintenance guides
- Create deployment and rollback procedures
- Requirements: 5.3, 5.4, 4.4
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