AI_AR_Install_Optimization

Overview

AI_AR_Install_Optimization is a research and prototype initiative exploring the integration of Artificial Intelligence, Augmented Reality, and Lean manufacturing principles to streamline automotive installation, inspection, and QA processes.
This project builds upon Toyota Production System (TPS) foundations while leveraging real-time AI guidance, HoloLens visualization, and Dockerized deployment for scalability.

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Objectives

• Reduce install and QA cycle time through real-time AI feedback.
• Integrate AR-assisted workflows (Microsoft HoloLens 2).
• Create standardized installation guidance models using visual AI.
• Enable cloud-based version control and deployment via Docker.

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Key Components

Component	Description
AI_AR_Install_Optimization_Project_Proposal.pdf	Full project proposal outlining design, goals, and technical approach.
download.html	Microsoft FastAPI documentation snapshot used for backend reference.
download (1).html	HoloLens documentation for AR deployment context.
download (2).html	Microsoft Learn: HoloLens technical overview and commercial readiness.
download (3).html	Docker documentation reference for containerization setup.

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Technical Stack

• Frontend: Streamlit (for dashboard prototyping)
• Backend: FastAPI / Python
• Containerization: Docker
• Hardware Interface: Microsoft HoloLens 2
• Version Control: Git + GitHub

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Future Development

1. Connect FastAPI backend with AR interface through REST API endpoints.
2. Add telemetry capture for human + AI installation performance metrics.
3. Containerize application with Docker for cross-system deployment.
4. Test AR overlay guidance using HoloLens SDK integration.

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Author

James C. Young
AI Enablement & Workflow Specialist
Portland, Oregon
LinkedIn • GitHub

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License

MIT License © 2025 James C. Young