{"url":"/dataset/tennessee-eastman-process","name":"Tennessee Eastman Process","full_name":null,"description_markdown":"This dataset contains simulations of a complex, large-scale chemical plant proposed by Downs and Vogel (1993). As described by Reinartz, Kulahci and Ravn (2021):\r\n\r\nThe process involves the production of two liquid product components G and H from four gaseous reactants A, C, D and E with an additional inert B and a byproduct F. The reaction system consists of four exothermic and irreversible reactions which are described by,\r\n\r\n\\begin{equation}\r\n\\begin{cases}\r\nA(g) + C(g) + D(g) \\rightarrow G(liq)&\\text{(Product 1)}\\\\\r\nA(g) + C(g) + E(g) \\rightarrow H(liq)&\\text{(Product 2)}\\\\\r\nA(g) + E(g) \\rightarrow F(liq)&\\text{(Byproduct)}\\\\\r\n3D(g) \\rightarrow F(liq)&\\text{(Byproduct)}\r\n\\end{cases}\r\n\\end{equation}\r\n\r\nThe analysis and simulations were done by Reinartz, Kulahci and Ravn (2021), who published the complete dataset online. In this context. Different simulations correspond to different types of faults, and operation conditions, Montesuma et al (2023) used these simulations to compose a Cross-Domain Fault Diagnosis problem.\r\n\r\n# References\r\n\r\nDowns, J.J., Vogel, E.F., 1993. A plant-wide industrial process control problem. Comput. Chem. Eng. 17 (3), 245–255. doi:10.1016/0098-1354(93)80018-I.\r\n\r\nChristopher Reinartz, Murat Kulahci, and Ole Ravn. An extended tennessee eastman simulation dataset for faultdetection and decision support systems. Computers & Chemical Engineering, 149:107281, 2021\r\n\r\nMontesuma, E. F., Mulas, M., Mboula, F. N., Corona, F., & Souloumiac, A. (2023). Multi-Source Domain Adaptation for Cross-Domain Fault Diagnosis of Chemical Processes. arXiv preprint arXiv:2308.11247.","description_withheld":null,"homepage":"https://data.dtu.dk/articles/dataset/Tennessee_Eastman_Reference_Data_for_Fault-Detection_and_Decision_Support_Systems/13385936/1","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":{"name":"CC0","url":"https://creativecommons.org/publicdomain/zero/1.0/"},"modalities":[{"name":"Time series","url":"/datasets/modality/time-series"}],"tasks":[{"name":"Multi-Source Unsupervised Domain Adaptation","url":"/task/multi-source-unsupervised-domain-adaptation","datasets_with_task":"/datasets/task/multi-source-unsupervised-domain-adaptation"}],"languages":[],"variants":["Tennessee Eastman Process"],"data_loaders":[],"num_papers_in_archive":7,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}