NASA Turbofan Jet Engine Data Set dataset, kaggle link. Currenltly has only FD002 subset

This dataset is designed for research on real-time edge computing architectures in Industrial Internet of Things (IIoT) applications. It simulates sensor data, network latency, and predictive maintenance in a smart manufacturing environment. The dataset integrates Fuzzy PID controllers for adaptive industrial process control and includes a target column (Predicted_Failure) for autonomous decision-making.

Key Features Time-Series IIoT Sensor Data (Temperature, Pressure, Vibration)

Edge Computing Metrics (Network Latency, Processing Time)

Fuzzy PID Controller Output (Optimized for real-time control)

Maintenance Status (Normal, Warning, Failure)

Predictive Failure Labels (1 = Failure, 0 = No Failure)

Overview: The NASA CMAPSS dataset consists of simulated jet engine sensor readings generated using the Commercial Modular Aero-Propulsion System Simulation (CMAPSS). It’s widely used for research in prognostics, health management, and remaining useful life (RUL) estimation.

Contents:

Training Data: Contains engine cycle information and sensor measurements. Test Data: Engine cycle data without RUL labels, to be predicted. RUL Values: Ground truth remaining useful life for the test engines. Applications: Ideal for time-series analysis, anomaly detection, and developing machine learning models focused on predictive maintenance.