Popular GitHub Repositories for Predictive Maintenance

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.

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.

Predictive Maintenance System for Digital Factory Automation

Deep Learning applied to predictive maintenance use cases

Evolutionary Neural Architecture Search for Remaining Useful Life Prediction

Curated list of predictive maintenance research and repositories.

This is a Machine Learning Practice Case of Predictive Maintenance by Python with NASA's Turbofan Engine Degradation Simulation Data Set.

In this project, high dimensional noisy data collected from thousands of trucks during the course of 4 years was compressed using Artificial Neural Networks (ANN). This compressed meaningful information was used for performing predictive maintenance on turbochargers. Our novel deep learning ANN architecture, compressed vehicle data by over 87% while still improving fault forecasting prediction by 23% and even with extreme data size reduction of 99.7% we still see a significant performance improvement of 6.31%.

Drift Detection in Gas Sensor Array at Different Concentration Levels ☢️

Showcase how machine learning can help plant operator monitor equipment condition through correctly analyzing measurement data collected from many sensors.

Anomaly Detection deployed on machine data dataset for Predictive Maintenance

Official PyTorch code for UAI 2024 paper "ContextFlow++: Generalist-Specialist Flow-based Generative Models with Mixed-variable Context Encoding"

Showcase how machine learning can help operators monitor equipment conditions through correctly analyzing measurement data collected from many sensors.

[IEEEHTC2023] Repo to analyse and predict cutting tool wear using acoustic signals.

Distributed MPI based Heterogenous GPU Solver for Markov Decision Processes (MDP)

Predictive Maintenance for Healthcare Equipment utilizes machine learning to analyze operational metrics and predict equipment failures. This project leverages a dataset of usage hours, temperature, and maintenance history to enhance equipment reliability and reduce downtime.

Partially Hidden Markov Chain Multivariate Linear AutoRegressive model