CRAFT Semiconductor Overview

Overview of the CRAFT semiconductor fab analytics platform for AI-assisted data analysis, workflow orchestration, and manufacturing insights.

Semiconductor Analytics

The Semiconductor solution provides AI-assisted data analytics for semiconductor fabrication (fab) environments. It enables fab engineers to query manufacturing data using natural language, run automated analysis workflows, and gain insights into production processes, the AI agent generates and executes Python code on behalf of the engineer.

Who Is It For

Fab Engineers

Analyze manufacturing data, identify yield issues, and investigate process deviations using conversational AI instead of manual SQL queries.

Process Engineers

Monitor process parameters, detect drift, and correlate process variables with quality outcomes using AI-assisted analytics.

Quality Engineers

Track defect rates, analyze wafer maps, and identify root causes of quality issues with automated data exploration.

Operations Leaders

Access high-level dashboards and generate reports on fab performance, throughput, and equipment utilization.

Key Capabilities

Conversational Analytics

Fab engineers interact with manufacturing data through a natural-language chat interface:

• “What is the yield trend for product X over the past 30 days?”
• “Which tools have the highest defect rates this week?”
• “Compare process parameters between high-yield and low-yield lots”
• “Show me wafer map defect patterns for the last 100 wafers”

The system generates Python analysis code, executes it in the sandboxed Code Execution service using the platform’s data-access layer, and returns results with interactive visualizations.

Automated Workflows

Prefect-orchestrated workflows automate analysis and data management:

• Yield excursion detection: Automated excursion detection with E1–E7 and parameter detectors, root cause analysis, and report generation (PDF, PPT, DOCX)
• Cross-product analysis: Compare yield and excursion patterns across products
• Data ingestion: Automated data extraction from fab systems (Optimal+)
• Feedback learning: Daily policy refinement from user feedback

Data Integration

The solution connects to standard semiconductor data sources:

• Manufacturing Execution Systems (MES)
• Equipment Data Collection (EDC) databases
• Wafer test and sort databases
• Inline metrology measurement databases
• Defect inspection and review systems

Architecture

The Semiconductor solution follows the same architectural patterns as the other CRAFT solutions:

Component	Role
Conversational interface	Natural-language queries against fab data
AI agents	Pydantic AI agent with MCP tools for fab analytics
Code execution	Sandboxed Python execution for data analysis and visualization
Workflow engine	Prefect workflows for automated analysis pipelines
Platform integration	Authentication, authorization, and data connections

Platform Integration

The Semiconductor solution integrates with the shared CRAFT:

• Authentication: Keycloak OIDC with organization-specific user management
• Authorization: JWT-based access control with organization-scoped data queries
• Data connections: Database connections managed via the data source connection system
• Multi-tenancy: All data isolated per organization

The Semiconductor solution operates as an independent platform with its own microservices (Backend API, AI Agent, MCP Server, Client Dashboard), shared library, and infrastructure. See the detailed architecture documentation for the full system design.

Semiconductor-Specific Analytics

Analysis Type	Description
Yield analysis	Lot-level and wafer-level yield calculation and trending
Excursion detection	Automated detection of yield anomalies using E1–E7, WAT, WSP, and multivariate detectors
Process correlation	Statistical correlation between process parameters and quality outcomes
Bin analysis	Test bin distribution analysis and Pareto charts
Report generation	Automated RCA and insight reports exportable as PDF, DOCX, and PPT
SPC monitoring	Control chart generation with out-of-control detection

Data Model

The solution understands standard semiconductor manufacturing data structures:

Entity	Description
Products	Semiconductor device families, characterized by technology node, foundry, and business unit
Lots	Manufacturing batches with user-friendly IDs (e.g., L2401-001) for natural reference in chat and reports
Wafers	Individual wafers within lots with WAT, WSD, and FTD measurements
Excursion Events	Detected yield anomalies with detector type, severity, and affected lots/wafers
Reports	Generated analysis reports (RCA, Insight) with sections, charts, and export support
Workflow Runs	Execution records for Prefect workflows with inputs, status, and outputs
Policies	Learned excursion detection rules with versioning from user feedback
Alerts	Notifications triggered by excursion detection or workflow events
Data Source Connections	Configured connections to external fab data systems