Curated list of Industry 4.0 research, popular events, open-source software projects and learning resources that are worth looking into!
Python codes “Jupyter notebooks” for the paper entitled "A Hybrid Method for Condition Monitoring and Fault Diagnosis of Rolling Bearings With Low System Delay, IEEE Trans. on Instrumentation and Measurement, Aug. 2022. Techniques used: Wavelet Packet Transform (WPT) & Fast Fourier Transform (FFT). Application: vibration-based fault diagnosis.
ProtoForge: 零硬件模拟 Modbus/S7/OPC-UA/BACnet 设备，测试上位机与网关通信。Python，开箱即用。
IndustryFusion is the open source IIoT connectivity solution for smart products and smart factories - it empowers small and medium-sized businesses to participate in tomorrow's connected industry. IndustryFusion instantly creates transparency and added value and enables new business models such as production sharing, pay-per-use machine usage, a…
Repository linked to "Anomaly detection in Smart-manufacturing era: A review"
Open Source Digital Twin Platform
5GTANGO Smart Manufacturing Pilot
Python code “Jupyter notebooks” for the paper entitled " Similarity-Based Predictive Maintenance Framework for Rotating Machinery" has been presented in the Fifth International Conference on Communications, Signal Processing, and their Applications (ICCSPA’22), Cairo, Egypt, 27-29 December 2022. Techniques used: statistical analysis, FFT, and STFT.
m2m is a node.js library for developing machine-to-machine and edge applications using the node-m2m framework.
DAU Firmware and upload tool for the Arduino Opta.
a graduation project on reinforcement learning in smart manufacturing scenarios
This repository contains the official workshop proposal document for the Embodied Autonomous Intelligence Workshop (EAI-WS), developed as part of the transition to the RoboCup Smart Manufacturing League (SML) starting in 2026.
A quick start-up guide on how to develop applications using the node.js m2m library.
Application for the SSM Repak, Year 2, Period 3.
Development of an in-situ digital inspection of tool wear for turning inserts. The model and training is based on EfficientNet and TensorFlow Lite. Input images are obtained from a digital microscope.
CHEMON - 化工过程多智能体整体编排系统 | A multi-agent collaborative system for chemical process control
Data-driven modeling to predict the load vs. displacement curves of targeted composite materials for industry 4.0 and smart manufacturing
Computer vision system that analyzes fabric patterns, detects defects in real-time manufacturing, and generates new textile designs using generative adversarial networks.
Real-time machine status update using MTConnect and MQTT protocols
Forklift Detection with YOLOv8 🚚
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