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| # CNC Agentic Programming | |
| ## Overview | |
| Agentic CNC programming uses autonomous AI agents to plan, generate, validate, and optimize CNC machining workflows. Rather than fully autonomous operation, the winning approach is **agent-assisted**: AI proposes machining strategies, human reviews and approves. | |
| ## Industry State of the Art | |
| ### Commercial Systems | |
| **CloudNC CAM Assist 2.0** | |
| - Used by 1,000+ machine shops globally | |
| - Generates trillions of machining strategies, simulates to find optimal | |
| - Physics-based Cutting Parameters Engine for feeds/speeds | |
| - Integrates with Mastercam, Fusion 360, Siemens NX, SolidCAM | |
| - Supports 3-axis and 3+2-axis | |
| - Completes ~80% of CAM programming in minutes | |
| **Toolpath.com** | |
| - AI CAM using game-based simulation (chess-engine approach) | |
| - Learns through virtual machining scenarios, not user data | |
| - Analyzes geometry, fixturing, tool access for minimum setups | |
| - Exports to Autodesk Fusion with geometry, tools, and setups | |
| **Mastercam 2026.R2 Copilot** | |
| - ~200 toolpath types via voice or text commands | |
| - GPU-accelerated simulation (90min CPU tasks in 22min) | |
| - Adjusts feed rates and spindle speeds across operations | |
| **Siemens NX CAM Copilot** (beta) | |
| - Generates 3 machining strategies per feature | |
| - 80% programming time reduction claim | |
| - Context-aware guidance, learns from past patterns | |
| ### Research Systems | |
| **ChatCNC** (Journal of Manufacturing Systems, 2025) | |
| - Multi-agent + RAG for conversational CNC monitoring | |
| - 93.3% accuracy on production-tracking queries | |
| - Merges LLM agents with real-time CNC machine data | |
| **CADSmith** (arxiv 2603.26512) | |
| - Multi-agent text-to-CAD with Planner/Coder/Executor/Validator/Refiner | |
| - 100% execution rate, median F1 0.98, IoU 0.96 | |
| - Two nested correction loops (code errors + geometry validation) | |
| - See [Multi-Agent CAD Research](multi-agent-cad-research.md) for details | |
| ## Key Insight | |
| AI-generated G-code still requires ~50% rework for complex parts. Current AI tools are force multipliers for experienced machinists -- the expert handles the final 20%. Fully autonomous end-to-end CNC programming without human review remains aspirational. | |
| ## NeuralCAD Approach | |
| NeuralCAD implements agentic CNC programming through its multi-agent pipeline: | |
| 1. **Design Agent** -- clarifies intent, proposes form factors | |
| 2. **Engineering Agent** -- specifies dimensions, materials, tolerances | |
| 3. **CNC Agent** -- advises on manufacturability, tool access, axis requirements | |
| 4. **CAD Coder Agent** -- generates CadQuery Python code | |
| 5. **CAM Agent** -- selects operations, tools, generates toolpath via ocp-freecad-cam | |
| The orchestrator (Gemini-powered) routes user messages to relevant agents, chains their outputs, and triggers the CAM pipeline after successful CAD generation. | |
| ## Open-Source CNC Projects | |
| | Project | URL | Description | | |
| |---------|-----|-------------| | |
| | Generic CAM | genericcam.sourceforge.net | Multi-axis toolpath generator, reads STL/GTS | | |
| | PathCAM | github.com/xenovacivus/PathCAM | 2.5D toolpath for CNC routers | | |
| | Toolpath_Gcode_generation | github.com/zhangty019 | 5-axis toolpath and G-code examples | | |
| | NEPath | github.com/WangY18/NEPath | Toolpath planning for additive/CNC | | |