✈️ Remaining Useful Life (RUL) Prediction of Jet Engines

A Machine Learning application that predicts the Remaining Useful Life (RUL) of aircraft jet engines using the NASA CMAPSS dataset, enabling predictive maintenance through data-driven insights and an interactive web interface.

---

📖 Overview

Predictive maintenance plays a crucial role in the aerospace industry by identifying potential engine failures before they occur. This project leverages Machine Learning techniques to estimate the Remaining Useful Life (RUL) of turbofan engines based on historical sensor readings.

The project covers the complete workflow—from data preprocessing and feature engineering to model training and deployment through an interactive web application.

---

✨ Features

➼ Predicts the Remaining Useful Life (RUL) of jet engines.

➼ Trained on the NASA CMAPSS turbofan engine dataset.

➼ Performs data preprocessing and feature scaling.

➼ Uses a pre-trained machine learning model for inference.

➼ Interactive web interface for real-time predictions.

➼ Demonstrates an end-to-end predictive maintenance workflow.

---

📊 Dataset

This project uses the NASA CMAPSS (Commercial Modular Aero-Propulsion System Simulation) dataset, which contains multivariate time-series sensor data collected from simulated turbofan engines operating under different conditions.

Included Files

File	Description
train_FD001.txt	Training dataset
test_FD001.txt	Testing dataset
RUL_FD001.txt	Ground truth Remaining Useful Life values

---

📂 Project Structure

Folder	Description
UI/	Streamlit application, trained model, scaler, and dependencies
data/	NASA CMAPSS datasets
files/	Jupyter notebooks for data analysis and model development

---

🛠️ Tech Stack

Category	Technologies
Language	Python
Machine Learning	Scikit-learn
Data Processing	Pandas, NumPy
Web Framework	Streamlit
Model Storage	Pickle
Development	Jupyter Notebook

---

⚙️ Model Pipeline

Dataset
   │
   ▼
Data Preprocessing
   │
   ▼
Feature Engineering
   │
   ▼
Feature Scaling
   │
   ▼
Model Training
   │
   ▼
Model Evaluation
   │
   ▼
Model Serialization (.pkl)
   │
   ▼
Streamlit Web Application

---

🎯 Applications

➼ Predictive Maintenance

➼ Aircraft Engine Health Monitoring

➼ Failure Prediction

➼ Industrial Equipment Monitoring

➼ Machine Learning Research

---

👨‍💻 Author

Harshil Kothiya

AI/ML Engineer

• GitHub: https://github.com/Harshilkothiya
• LinkedIn: https://linkedin.com/in/harshil-kothiya

---

⭐ If you found this project helpful, consider giving it a Star! ⭐