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    AuthorTitleYearJournal/Proceedings DOI/URL
    Al Mawla, H. & Kroll, A. Multivariate statistical approaches for an early detection of foaming in a refinery SCOT unit 2018 at -- Automatisierungstechnik , Vol. 66 (8) , pp. 665 - 679   DOI URL  
    Abstract: The formation of foam in amine units is an issue that plant operators and field personnel are confronted with on a regular basis. The inability to take proper actions in due time may result in plant downtime and increased emissions. Steep rises in differential pressure indicate foam formation, and are monitored manually in practice. Antifoaming agent is added in order to reduce foaming, but this is usually carried out under time pressure. Hence, plant operating authorities have expressed a strong interest in a data-driven solution capable of providing an early warning against foaming. The classical univariate alarm associated with differential pressure can be ineffective for foaming detection due to high misdetection rates and its lateness of detection. Modern univariate approaches based on pattern recognition techniques may not be suitable either for an early detection, as no universally distinctive features of differential pressure are observed prior to foaming in the present study. In this contribution, the multivariate statistical process monitoring approach based on principal component analysis (PCA) is applied to the early detection of foaming in a continuously operated Shell Claus Off-gas Treating (SCOT) unit of a major refinery in Germany. The results are extended to facilitate fully automated and adaptive modeling based on exponentially weighted recursive principal component analysis (EWRPCA).
    BibTeX:
    	@article{Al_Mawla-AT-2018,
    	   author = {H. Al Mawla and A. Kroll}
    	  , title = {Multivariate statistical approaches for an early detection of foaming in a refinery SCOT unit}
    	  
    	  , journal = {at -- Automatisierungstechnik}
    	  
    	  
    	  
    	  , year = {2018}
    	  , volume = {66}
    	  , number = {8}
    	  , pages = {665 -- 679}
    	  
    	  
    	  
    	  , url = {https://www.degruyter.com/view/j/auto.2018.66.issue-8/auto-2018-0048/auto-2018-0048.xml}
    	  , doi = {https://doi.org/10.1515/auto-2018-0048}
    	  
    	  , issn = {2196-677X}
    	   } 
    	
    Atzmueller, M., Kloepper, B., Al Mawla, H., Jäschke, B., Hollender, M., Graube, M., Arnu, D., Schmidt, A., Heinze, S., Schorer, L., Kroll, A., Stumme, G. & Urbas, L. Big data analytics for proactive industrial decision support: Approaches & first experiences in the FEE Project 2016 atp edition , Vol. 58 (9) , pp. 62-74 , September   URL  
    BibTeX:
    	@article{AtzmuellerATP2016,
    	   author = {Atzmueller, Martin and Kloepper, Benjamin and Al Mawla, Hassan and Jäschke, Benjamin and Hollender, Martin and Graube, Markus and Arnu, David and Schmidt, Andreas and Heinze, Sebastian and Schorer, Lukas and Kroll, Andreas and Stumme, Gerd and Urbas, Leon}
    	  , title = {Big data analytics for proactive industrial decision support: Approaches & first experiences in the FEE Project}
    	  
    	  , journal = {atp edition}
    	  
    	  
    	  
    	  , year = {2016}
    	  , volume = {58}
    	  , number = {9}
    	  , pages = {62-74}
    	  
    	  
    	  
    	  , url = {https://www.di-verlag.de/de/Zeitschriften/atp-edition/2016/09/Big-data-analytics-for-proactive-industrial-decision-support}
    	  
    	  
    	  
    	   } 
    	
    Heinze, S., Graube, M., Schegner, L., Arnu, D., Klinkenberg, R., Schmidt, A., Atzmüller, M., Klöpper, B., Dix, M., Hollender, M., Chioua, M., Al Mawla, H., Rehmer, A., Kroll, A., Stumme, G. & Urbas, L. Big Data in der Prozessindustrie: Frühzeitige Erkennung und Entscheidungsunterstützung 2017 Automation 2017 , VDI , Baden-Baden , 27.-28. Juni , VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik (GMA) , online   URL  
    BibTeX:
    	@inproceedings{HeinzeAutomation2017,
    	   author = {S. Heinze and M. Graube and L. Schegner and D. Arnu and R. Klinkenberg and A. Schmidt and M. Atzmüller and B. Klöpper and M. Dix and M. Hollender and M. Chioua and H. Al Mawla and A. Rehmer and A. Kroll and G. Stumme and L. Urbas}
    	  , title = {Big Data in der Prozessindustrie: Frühzeitige Erkennung und Entscheidungsunterstützung}
    	  , booktitle = {Automation 2017}
    	  
    	  , publisher = {VDI}
    	  
    	  
    	  , year = {2017}
    	  
    	  
    	  
    	  , address = {Baden-Baden}
    	  
    	  
    	  , url = {http://www.automatisierungskongress.de/}
    	  
    	  
    	  
    	   } 
    	
    Kroll, A., Dürrbaum, A., Arengas, D., Al Mawla, H., Kistner, L. & Rehmer, A. µPlant: Eine automatisierungstechnisch-orientierte Modellfabrik für vernetzte heterogene Systeme 2017 atp edition , Vol. 59 (9) , pp. 40-53 , September   URL PDF  
    Abstract: Modellfabriken werden mittlerweile häufig in Forschung und Lehre eingesetzt, aber über ihren Aufbau und ihre Funktionen ist wenig zu lesen. Im Beitrag wird eine Übersicht über in Deuschland vorhandene Modellfabriken gegeben. Zudem werden Details der selbst konzipierten und realisierten Modellfabrik µPlant vorgestellt. Diese besteht aus mehreren mit Transportrobotern verbundenen Produktionsinseln/-zellen, die jeweils lokal über angepasste Automatisierungssysteme verfügen. Alle Module sind stofflich und informationstechnisch integriert und die Modellfabrik kann voll automatisiert betrieben werden. Der Beitrag richtet sich an Personen mit Interesse an Aufbau, Beschaffung oder Nutzung von Modellfabriken
    BibTeX:
    	@article{2017-Kroll_et_al-atp_edition-Modellfabrik_muPlant,
    	   author = {Andreas Kroll AND Axel Dürrbaum AND David Arengas AND Hassan Al Mawla AND Lars Kistner AND Alexander Rehmer}
    	  , title = {µPlant: Eine automatisierungstechnisch-orientierte Modellfabrik für vernetzte heterogene Systeme}
    	  
    	  , journal = {atp edition}
    	  
    	  
    	  
    	  , year = {2017}
    	  , volume = {59}
    	  , number = {9}
    	  , pages = {40-53}
    	  
    	  
    	  
    	  , url = {https://www.di-verlag.de/de/Zeitschriften/atp-edition/2017/09/Plant:-Modellfabrik-fuer-vernetzte-heterogene-Anlagen}
    	  
    	  
    	  
    	   } 
    	
    Kroll, A., Dürrbaum, A., Arengas, D., Jäschke, B., Al Mawla, H. & Geiger, A. µPlant: Model factory for the automatization of networked, heterogeneous and flexibly changeable multi-product plants 2016 Automation 2016 , Vol. VDI-Berichte 2284 , VDI , Baden-Baden , 7.-8. Juni , VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik (GMA) , online   URL  
    BibTeX:
    	@inproceedings{muPlant_AUTOMATION_2016,
    	   author = {A. Kroll and A. Dürrbaum and D. Arengas and B. Jäschke and H. Al Mawla and A. Geiger}
    	  , title = {µPlant: Model factory for the automatization of networked, heterogeneous and flexibly changeable multi-product plants}
    	  , booktitle = {Automation 2016}
    	  
    	  , publisher = {VDI}
    	  
    	  
    	  , year = {2016}
    	  , volume = {VDI-Berichte 2284}
    	  
    	  
    	  , address = {Baden-Baden}
    	  
    	  
    	  , url = {http://www.automatisierungskongress.de/}
    	  
    	  , isbn = {978-3-18-092284-0}
    	  , issn = {0083-5560}
    	   } 
    	

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