predictive-maintenance

Synapsa Commons: free, hands-on AI courses that run anywhere (Colab, Kaggle, Binder, Codespaces, Jupyter). EU AI Act conformity evidence, model validation, predictive maintenance, document extraction, retrieval and RAG, AI agents and MCP, a simulated humanoid. Every lesson autograded. From the team building Synapsa.

AssetOpsBench - Industry 4.0: A unified benchmark and framework for building, orchestrating, and evaluating domain-specific AI agents for Industry 4.0 asset operations and maintenance, with 460+ scenarios, 5 specialist agents (IoT, FMSR, TSFM, Work Order,...), and multi-agent orchestration blueprints (MetaAgent, AgentHive) over MCP.

Power Tools for AI Engineers With Deadlines

Example of Multiple Multivariate Time Series Prediction with LSTM Recurrent Neural Networks in Python with Keras.

Transformer implementation with PyTorch for remaining useful life prediction on turbofan engine with NASA CMAPSS data set. Inspired by Mo, Y., Wu, Q., Li, X., & Huang, B. (2021). Remaining useful life estimation via transformer encoder enhanced by a gated convolutional unit. Journal of Intelligent Manufacturing, 1-10.

Papers and datasets for Vibration Analysis

DataGene - Identify How Similar TS Datasets Are to One Another (by @firmai)

Datasets for Predictive Maintenance

In this project I aim to apply Various Predictive Maintenance Techniques to accurately predict the impending failure of an aircraft turbofan engine.

collection of predictive maintenance solutions for NASAs turbofan (CMAPSS) dataset

This research project will illustrate the use of machine learning and deep learning for predictive analysis in industry 4.0.

Predictive_Maintenance_using_Machine-Learning_Microsoft_Casestudy

N-CMAPSS data preparation for Machine Learning and Deep Learning models. (Python source code for new CMAPSS dataset)

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.

An open-source MCP server that turns LLMs into condition monitoring assistants for reliability engineers. It gives your AI assistant evidence-based vibration diagnostics: machine fault detection, severity assessment and diagnostic reports, for faster predictive maintenance decisions. Also available as a Claude Code plugin.

Nvidia DLI workshop on AI-based predictive maintenance techniques to identify anomalies and failures in time-series data, estimate the remaining useful life of the corresponding parts, and map anomalies to failure conditions.

Industrial time series forecasting with Static Transformer (R²>0.9, <5ms inference）

Predictive Maintenance for Vehicle Fleets

This project is about predictive maintenance with machine learning. It's a final project of my Computer Science AP degree.

A powerful app for processing DJI infrared (IR) images, featuring advanced thermal analysis, conversion, and visualization capabilities. Supports DJI Matrice 4 (M4T), Matrice 30 (M30T), Mavic 3 (M3T), and Mavic 2 Enterprise Advanced drones