README.md

metadata

license: cc-by-4.0
task_categories:
  - time-series-forecasting
  - tabular-classification
tags:
  - bioprocess
  - manufacturing
  - anomaly-detection
  - fault-detection
  - batch-monitoring
  - pharma
pretty_name: Golden Batch Sentinel Data
size_categories:
  - 1M<n<10M

Golden Batch Sentinel Data

Benchmark datasets for process monitoring and fault detection in batch manufacturing.

Datasets

IndPenSim (Industrial Penicillin Simulation)

A 100,000L fermentation simulation with 100 batches and rich multivariate signals.

• Source: Mendeley Data
• Paper: Modern day monitoring and control challenges...
• Batches: 100 (90 normal, 10 faulty)
• Variables: 37 process variables (Raman spectra excluded for efficiency)
• Time resolution: 0.2 hours

Files:

• indpensim/batches.parquet - Main batch data
• indpensim/statistics.parquet - Batch statistics and fault labels

Tennessee Eastman Process (TEP)

The most common benchmark for fault detection in multivariate industrial processes.

• Source: Harvard Dataverse
• Fault types: 20 different fault scenarios
• Variables: 52 (41 measured + 11 manipulated)

Files:

• tep/fault_free_train.parquet - Normal operation (training)
• tep/fault_free_test.parquet - Normal operation (testing)
• tep/faulty_train.parquet - Faulty operation (training, all 20 faults)
• tep/faulty_test.parquet - Faulty operation (testing, all 20 faults)

Usage

from datasets import load_dataset

# Load IndPenSim
indpensim = load_dataset("foundation-models/golden-batch-sentinel-data", data_dir="indpensim")

# Load TEP
tep = load_dataset("foundation-models/golden-batch-sentinel-data", data_dir="tep")

# Or load specific files
import pandas as pd
from huggingface_hub import hf_hub_download

path = hf_hub_download(
    repo_id="foundation-models/golden-batch-sentinel-data",
    filename="indpensim/batches.parquet",
    repo_type="dataset"
)
df = pd.read_parquet(path)

License

The original datasets are provided under their respective licenses:

• IndPenSim: CC BY 4.0
• TEP: Public domain

This compilation is provided under CC BY 4.0.

Citation

If you use this data, please cite the original papers:

@article{goldrick2019modern,
  title={Modern day monitoring and control challenges outlined on an industrial-scale benchmark fermentation process},
  author={Goldrick, Stephen and others},
  journal={Computers \& Chemical Engineering},
  year={2019}
}

@article{downs1993plant,
  title={A plant-wide industrial process control problem},
  author={Downs, James J and Vogel, Ernest F},
  journal={Computers \& Chemical Engineering},
  year={1993}
}