I-BiDaaS CRF SCADA Dataset — Automotive Welding-Line Sensors [3.9 GB]
Catalog Summary
"SCADA sensor dataset from automotive welding sub-assembly lines with 147 sensors. 3.9 GB 7z archive for anomaly thresholds and predictive maintenance analysis."
Catalog Notes
Overview
The I-BiDaaS CRF SCADA Dataset contains sensor data from welding processes in vehicle sub-assembly production lines.
It includes multiple sensor types installed on a production line, including acceleration, velocity, pressure, and temperature.
The metadata explicitly connects vibration monitoring to predictive maintenance and states that the dataset includes 147 sensors.
Column Schema
| Column | Description |
|---|---|
| timestamp | Time of the SCADA sensor observation. |
| sensor_id | Identifier for one of the 147 production-line sensors. |
| acceleration | Acceleration measurement from industrial sensors. |
| velocity | Velocity measurement from production-line sensors. |
| pressure | Pressure measurement associated with the welding process. |
| temperature | Temperature measurement from the line or equipment environment. |
| machine_area | Production-line or sub-assembly area represented in anonymized SCADA data. |
Key Statistics
- Total Records: SCADA sensor archive; exact row count not stated on Zenodo
- Features: 147 sensors including acceleration, velocity, pressure, and temperature
- File Format: 7z archive plus metadata PDF
- File Size: 3.9 GB
- Industrial Domain: Automotive welding sub-assembly line
Use Cases
- Automotive production-line predictive maintenance
- SCADA anomaly detection
- Threshold learning for industrial sensor measurements
Source & Attribution
Created by Julien Mascolo, Gianmarco Genchi, and Giuseppe Danilo Spennacchio at CRF. Published on Zenodo with DOI 10.5281/zenodo.4265324.
View Data Structure
To explore column names, data types, and sample rows, visit the official dataset page on Zenodo.
Preview on ZenodoCite This Dataset
Mascolo, J., Genchi, G., & Spennacchio, G. D. (2020). I-BiDaaS - CRF - SCADA Dataset. [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.4265324
Source metadata: Zenodo (2020) · DOI: 10.5281/zenodo.4265324
Indexed by IoTDataset.com on Jun 06, 2026
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