journalA. S. Behr, L. Neuendorf, P. Sakthithasan, M. Karan, Q. Fang, K. E. R. Boettcher, C. Terkowsky, N. Kockmann

Uniting knowledge and application in a hybrid laboratory experiment in virtual reality – a cross-reality laboratory with applications of artificial intelligence for industry 4.0

REV 2023 Lecture Notes in Networks and Systems, 2023, vol. 763, https://doi.org/10.1007/978-3-031-42467-0_26

journalL. Neuendorf, S. Höving, L. Bennemann, N. Kockmann

Detecting Crystals in Suspensions: Convolutional Neural Networks vs. Gravity-Based Approach for Size Distribution Detection

Chem. Eng. Technol., 2023, http://doi.org/10.1002/cite.202200235

journal S. Höving, L. Neuendorf, T. Betting, N. Kockmann

Determination of Particle Size Distributions of Bulk Samples Using Micro-Computed Tomography and Artificial Intelligence

Materials, 2023, vol. 16(3), p. 1002, https://doi.org/10.3390/ma16031002

posterL. Neuendorf, P. Müller, C. Bergeest, A. Meijer, C. Schlander, N. Kockmann

Künstliche Intelligenz (KI)-basierte optische Sensorik für flüssig-flüssig Systeme

16. Dresdner Sensor-Symposium, 05. - 07122022, Dresden, Germany

talkV. Khaydarov (TU Dresden), L. Neuendorf (TU Dortmund), C. Schlander (Merck), T. Kock (TU Dresden), J. Fischer (Merck), N. Kockmann (TU Dortmund), L. Urbas (TU Dresden)

Visual Sensors for Modular Plants

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

talkL. Neuendorf, M. Schwing, N. Kockmann

Control of an Extraction Column Using Reinforcement Learning

(Bio)Process Engineering, 12. - 15092022, Aachen, Germany

talkA. Behr, L. Neuendorf, P. Sakthithasan, K. Boettcher, N. Kockmann

Process control using AI on a digital twin of an extraction column in VR

IEEE German Education Conference 2022, 11.-12.08.2022, Berlin, Germany

talkL. Neuendorf, N. Kockmann

Extraction column automation using three types of Machine Learning (ML) algorithms

ACHEMA, 22. - 26082022, Frankfurt am Main, Germany

posterL. Neuendorf, P. Kolloch, M. J.Alam, L. Marsollek, P. Müller, C. Bergeest, N. Kockmann

Artificial Intelligence (AI)-based optical sensors

Workshop digitale Sensorik, 13.06.2022, Frankfurt, Germany

talkL. Neuendorf, P. Kolloch, F. Baygi, M. Schwing, N. Kockmann

Online Process Monitoring and Control of an Extraction column using Machine Learning (ML)

Jahrestreffen der ProcessNet-Fachgruppen Extraktion, Phytoextrakte und Membrantechnik, 23. - 24.05.2022, Frankfurt am Main, Germany

posterL. Neuendorf, Md Jahangir Alam, N. Kockmann

AI-based sensors for extraction column control

ProcessNet JT Fluidverfahrenstechnik, 02.-03.05.2022, Frankfurt am Main

proceedingL. Neuendorf, P. Müller, C. Bergeest, A. Meijer, C. Schlander, N. Kockmann

Künstliche Intelligenz (KI)-basierte optische Sensorik für flüssig-flüssig Systeme

16. Dresdner Sensor-Symposium 2022, 2022, vol. 16, p. 230 - 234, 10.5162/16dss2022/P50

proceedingL. Neuendorf, C. Bergeest, C. Schlander, A. Meijer, N. Kockmann

Liquid-Liquid Interphase Tracking during Coalescence for Process Scale up

μFIP 2022,, 2022, vol. 22, p. 78, 978-1-7334190-3-1

proceedingA. S. Behr; L. Neuendorf; P. Sakthithasan; K. E.R. Boettcher; N. Kockmann

Process control using AI on a digital twin of an extraction column in VR

2022 IEEE German Education Conference (GeCon), 2022, 10.1109/GeCon55699.2022.9942788

proceedingV. Khaydarov, L. Neuendorf, T. Kock, N. Kockmann, L. Urbas

MTPPy: Open-Source AI-friendly Modular Automation

2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA), 2022, 10.1109/ETFA52439.2022.9921713

journalO. S. Bayomie, R. F. L. de Cerqueira, L. Neuendorf, I. Kornijez, S. Kieling, T. H. Sandermann, K. Lammers, N. Kockmann

Detecting flooding state in extraction columns: Convolutional neural networks vs. a white‐box approach for image‐based soft sensor development

Computers & Chemical Engineering, 2022, vol. 164, https://doi.org/10.1016/j.compchemeng.2022.107904

journalL. Neuendorf, Fatemeh Baygi, Pia Kolloch, N. Kockmann

Implementation of a Control Strategy for Hydrodynamics of a Stirred Liquid–Liquid Extraction Column Based on Convolutional Neural Networks

ACS Engineering Au, 2022, https://doi.org/10.1021/acsengineeringau.2c00014

talkL. Neuendorf, Pia Kolloch, Fatemeh Baygi, N. Kockmann

Development of a smart sensor for extraction column control

ProcessNet JT PAAT, 22.-23.11.2021

talkL. Neuendorf, J. Oeing, W. Krieger, L. Bittorf, N. Kockmann

Artificial Intelligence in laboratories: Machine and Deep Learning based monitoring of flooding behavior in distillation and extraction columns

European Congress of Chemical Engineering, 20.-23.09.2021, Berlin, Germany

talkJulia Schuler, Nina Gumbiowski, Michael Kensy, Laura Maria Neuendorf, Norbert Kockmann

3D Investigation of Droplet Generation in a Co-flow Device Using Micro-Computed Tomography

ProcessNet Fachgruppensitzung CFD & MPH, 09.-10.03.2021, Paderborn, Germany

Uniting knowledge and application in a hybrid laboratory experiment in virtual reality – a cross-reality laboratory with applications of artificial intelligence for industry 4.0

Detecting Crystals in Suspensions: Convolutional Neural Networks vs. Gravity-Based Approach for Size Distribution Detection

Determination of Particle Size Distributions of Bulk Samples Using Micro-Computed Tomography and Artificial Intelligence

Künstliche Intelligenz (KI)-basierte optische Sensorik für flüssig-flüssig Systeme

Visual Sensors for Modular Plants

Control of an Extraction Column Using Reinforcement Learning

Process control using AI on a digital twin of an extraction column in VR

Extraction column automation using three types of Machine Learning (ML) algorithms

Artificial Intelligence (AI)-based optical sensors

Online Process Monitoring and Control of an Extraction column using Machine Learning (ML)

AI-based sensors for extraction column control

Künstliche Intelligenz (KI)-basierte optische Sensorik für flüssig-flüssig Systeme

Liquid-Liquid Interphase Tracking during Coalescence for Process Scale up

Process control using AI on a digital twin of an extraction column in VR

MTPPy: Open-Source AI-friendly Modular Automation

Detecting flooding state in extraction columns: Convolutional neural networks vs. a white‐box approach for image‐based soft sensor development

Implementation of a Control Strategy for Hydrodynamics of a Stirred Liquid–Liquid Extraction Column Based on Convolutional Neural Networks

Development of a smart sensor for extraction column control

Artificial Intelligence in laboratories: Machine and Deep Learning based monitoring of flooding behavior in distillation and extraction columns

3D Investigation of Droplet Generation in a Co-flow Device Using Micro-Computed Tomography

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