AI-Powered Predictive Maintenance & Fault Diagnosis through Model Context Protocol. An open-source framework for integrating Large Language Models with predictive maintenance and fault diagnosis workflows.

An Introduction to HART Protocol. The aim of this repository is to understand the HART message format & create ways to interface the device data with upstream IoT network

A PHP library that talks OPC UA binary protocol over TCP. It handles the full stack — transport, encoding, secure channels, sessions, crypto — so you can connect to any OPC UA server straight from PHP, without shelling out to C/C++ libraries.

MCP_HACK//26 — Industrial Zero-Trust AI: T-IA Connect + AgentGateway for Siemens TIA Portal

This project simulates a conveyor system with multiple workpiece carriers. Using Unity for 2D layout planning, it aims to answer questions about the required number of carriers. Salabim is employed for discrete event simulation to model and analyze the system's dynamic behavior. Developed as part of a university project.

OPC UA industrial library for executing commands, reads and writes on OPC UA servers

An advanced Industrial IoT (IIoT) simulator for Smart Factory 4.0 environments using Python, MQTT, and Docker. Emulates configurable production lines with realistic sensor data (vibration, temperature, quality) and predictive alerts.

A streaming Digital Twin of a steel hot rolling mill demonstrating Online Machine Learning (OML) with Apache Kafka, Apache Flink and MOA to handle real-time concept drift.

Open-source industrial OPC UA platform for realtime monitoring and visualization.

AI control fabric for physical systems. Visual pipeline orchestration from LLM reasoning to real hardware — PLCs, ESP32, Pico, Arduino, Raspberry Pi — runs fully local.

An AAS MCP adapter that exposes configured Asset Administration Shell APIs as Model Context Protocol tools, enabling LLM agents to interact with any AAS-compliant backend.

An open-source factory intelligence platform for quality drift detection, synthetic factory simulation, governed AI workflows, and industrial operations intelligence.

🎯 AI-powered CNC production monitoring: Automatically tracks machining cycles, optimizes efficiency, reduces costs 15-25%. Real-time analytics, predictive maintenance alerts, seamless MES integration. Industrial-grade security, 99.8% uptime. ROI in 6-12 months. Ready for Industry 4.0.

Industrial IoT Educational Bridge - ESP32 to React Dashboard via MQTT. Learn Industry 4.0 concepts: Edge Computing, MQTT, InfluxDB, Real-time Visualization. Perfect for technical students!

Smart Packaging Platform — AI-powered quality inspection, sustainable material catalog, and digital transformation assessment for the printing & packaging industry

Real-time CNC machine failure detection using ML on AWS SageMaker | F1 ≥ 0.85 | P95 Latency ≤ 50ms | Live Streamlit Dashboard

End-to-End Industrial AI-driven condition monitoring system for early fault detection in rotating machinery using Unsupervised LSTM Autoencoders. Detects failures 72h in advance. Early fault detection with 100% accuracy on high-frequency sensor data (NASA IMS Dataset).

Ultra-fast (120-180 FPS) bare-metal AI inspection engine for Industry 4.0 edge computing. High-performance defect detection in 3.42 MB RAM.

Features a logic-gate to pause updates and notify stakeholders if maintenance records are incomplete.Simultaneously, machine learning models are used in retool to provide early warnings and suggestions.

Machine Learning and NLP system for detecting social media misinformation and prioritizing high-risk content using risk-based optimization.