Apr 24
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If you want a portfolio project that proves you can bridge industrial automation, controls, and software engineering, this is the kind of build to study. This Industrial Maintenance Intelligence Platform connects PLC fault events to a technician-facing web app, AI-assisted troubleshooting, automated 5 Whys generation, document retrieval, and demo work order creation. It was built as a practical IT/OT project using a React frontend, FastAPI backend, PostgreSQL, Celery, Redis, Docker, NGINX, GCP, and a Python PLC poller using Snap7. The frontend workflow was accelerated with Claude, especially around user flow and interface scaffolding. Codex helped drive backend implementation, API repair, deployment fixes, live debugging, and system integration. That split mirrors real delivery work: fast UI iteration on one side, infrastructure and backend execution on the other. If you're in industrial automation, controls, DevOps, or full-stack engineering, this project shows portfolio evidence that you can work across the plant floor and the cloud stack. STACK • React 18 + Vite + Tailwind CSS • FastAPI + SQLAlchemy + Alembic • PostgreSQL + Celery + Redis • Docker Compose + NGINX + GCP VM • Gemini API for AI workflows • python-snap7 PLC poller for Siemens-style fault ingestion This is the kind of project that looks strong on a portfolio because it demonstrates: • IT/OT integration • industrial context • full-stack delivery • API and infrastructure debugging • AI workflow implementation Comment GITHUB and I'll release the full stack on my GitHub. #IndustrialAutomation #DevOps #PortfolioProject #IndustrialAutomation #DevOps #PortfolioProject #ControlsEngineering #FullStackDeveloper #PLC #FastAPI #ReactJS #Docker #OTCybersecurity #MaintenanceEngineering #AIProjects #ITOT #TechPortfolio #BuildInPublic