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M.Sc. Jonas Oeing

M.Sc. Jonas Oeing Photo of M.Sc. Jonas Oeing

Telephone
(+49)231 755-7392

Fax
(+49)231 755-8084

Address

Fakultät Bio- und Chemieingenieurwesen
Arbeitsgruppe ApparateDesign
Geschossbau 3

Room 4.31

Information

Curriculum Vitae

Jonas Oeing has studied Chemical Engineering at the TU Dortmund University since 2013. He completed his Bachelor thesis with the topic ‘Entwicklung eines Simulationsprogrammes zur Berechnung der Ein- und Ausatmungsvorgänge atmosphärischer Tanks‘ in collaboration with INEOS Phenol GmbH. He completed his Master at the Laboratory of Equipment Design with his thesis ‘Service oriented architecture for an automated laboratory distillation column’. Since 2020 he works as a research associate at the laboratory of Equipment Design, participation in the KEEN project. Within the scope of this project he researches AI-supported process development and HAZOP-analyses.

Research

The aim is the development of AI-supported methods in process planning. Parallel to this, the development of new processes with the help of an AI-based HAZOP-assistance will be used for a comprehensive and reliable safety assessment.

Thesis vacancy

Currently no open theses are available.

Publications

Journal Articles

journalJ. Oeing, W. Welscher, N. Krink, L. Jansen, F. Henke, N. Kockmann

Using artificial intelligence to support the drawing of piping and instrumentation diagrams using DEXPI standard

Digital Chemical Engineering, 2022, vol. 4, https://doi.org/10.1016/j.dche.2022.100038

journalM. Wiedau, G. Tolksdorf, J. Oeing, N. Kockmann

Towards a Systematic Data Harmonization to Enable AI Application in the Process Industry

Chem. Ing. Tech., 2021, https://doi.org/10.1002/cite.202100203

journalJ. Oeing, L. Neuendorf, L. Bittorf, W. Krieger, N.Kockmann

Flooding Prevention in Distillation and Extraction Columns with Aid of Machine Learning Approaches

Chem. Ing. Tech., 2021, doi: 10.1002/cite.202100051


Talks

talkJ. Oeing, W. Welscher, K. Brandt, N. Kockmann

Using artificial intelligence to support the engineering of piping and instrumentation diagrams: modeling & prototyping

ProcessNet Jahrestreffen Prozess-, Apparate- und Anlagentechnik 2022, 21-22112022, Frankfurt am Main, Germany

talkJ. Oeing, T. Holtermann, W. Welscher, N. Kockmann

preHAZOP: Using DEXPI P&IDs and open-source process simulation to automatically predict safety-critical plant areas

ProcessNet Jahrestreffen Prozess-, Apparate- und Anlagentechnik 2022, 21-22112022, Frankfurt am Main, Germany

talkJ. Oeing, W. Welscher, L. Jansen, N. Kockmann

Smart, artificial intelligence-based synthesis of piping and instrumentation diagrams (P&IDs)

ProcessNet JT PAAT, 22.-23.112021


Posters

posterJ. Oeing, W. Welscher, N. Kockmann

Artificial Intelligence supported P&ID-development

KEEN Research Project2021, http://keen-plattform.de/Aktuelles/Downloads.html

posterJ. Oeing, F. Henke, N. Kockmann

AI-supported prediction of separation processes

KEEN Research Project2021, http://keen-plattform.de/Aktuelles/Downloads.html

posterL. Bittorf, J. Oeing, T. Holm, S. Loepker, M. Hoernicke, K. Stark, N. Kockmann

Service oriented architecture for an automated laboratory distillation process module

JTR Prozess-, Apparate- und Anlagentechnik, 04.-05.11.2019, Dortmund


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Scientific Theses

MasterKevin Brandt (Supervisor: Jonas Oeing)

Entwicklung eines KI-Tools zur Konsistenzprüfung von standardisierten R&I-Fließbildern im DEXPI-Format

TU Dortmund, Fakultät BCI, Arbeitsgruppe Apparatedesign, 22.09.2022

MasterTim Holtermann (Supervisor: Jonas Oeing)

Entwicklung eines Expertentools zur automatisierten Si-cherheitsbetrachtung von standardisierten R&I-Fließbildern im DEXPI Format

TU Dortmund, Fakultät BCI, Arbeitsgruppe Apparatedesign, 08.04.2022

BachelorTom Olusanya (Supervisor: Jonas Oeing)

Detektion von funktionalen Baugruppen in Rohrleitungs- und Instrumentierungs-fließbildern (R&Is) mit Methoden der künstlichen Intelligenz

TU Dortmund, Fakultät BCI, Arbeitsgruppe Apparatedesign, 07.03.2022

BachelorLars Jansen (Supervisor: Jonas Oeing)

Modellierung von R&I-Fließbildern mit künstlichen neuronalen Netzen

TU Dortmund, Fakultät BCI, Arbeitsgruppe Apparatedesign, 27.09.2021

BachelorDiana Chernenko (Supervisor: Jonas Oeing)

Normierung und Modellierung von tabellarischen Sicherheitsbetrachtungen mit Methoden künstlicher Intelligenz

TU Dortmund, Fakultät BCI, Arbeitsgruppe Apparatedesign, 31.05.2021

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