Position innerhalb des Seitenbaumes

Julian Ziegler

Herr M.Sc.

Wissenschaftlicher Angestellter
IPVS
Anwendersoftware

Kontakt

+49 711 685 88277
E-Mail

Universiätsstraße 38
D-70569 Stuttgart
Deutschland
Raum: 2.328

Sprechstunde

Nach Vereinbarung

Fachgebiet

Projektbereich: IKT-Plattform für die Produktion

Anwendungen im Bereich des Computer-Aided-Engineering (CAE) unterstützen den digitalen Wandel in der Fertigungsindustrie. Sie ermöglichen die virtuelle Produktentwicklung und Produktprüfung durch Computersimulationen. CAE-Anwendungen generieren riesige Mengen an heterogenen Daten. Domänenexperten haben Schwierigkeiten, auf diese zuzugreifen und sie zu analysieren, da solche Daten aus dem Ingenieursbereich nicht ausreichend mit Metadaten beschrieben sind. Darüber hinaus sind Daten in Unternehmen oft in „Silos“ separiert und schlecht auffindbar.
In diesem Projekt identifizierte Julian Ziegler ungelöste Herausforderungen für ein für die CAE-Domäne maßgeschneidertes Daten- und Metadatenmanagement. Daran schloss sich die Entwicklung eines Metadatenmodells an, das diese Herausforderungen adressiert und in einer vernetzten Struktur eine zusammenhängende Sicht auf alle CAE-Daten, Metadaten und Arbeitsaktivitäten virtueller Produktentwicklungsprojekte bietet. Eine prototypische Implementierung dieses Metadatenmodells wird bereits auf einen realen Anwendungsfall beim Industriepartner angewendet. Dies zeigt, wie es die Aufgabe von Domänenexperten erleichtert, für ihre Anwendungen relevante Daten zu finden. Darüber hinaus ermöglicht das Metadatenmodell eine Vielzahl neuer Anwendungsfälle für Datenanalysen. Durch die Kopplung verschiedener Datensilos werden beispielweise in einem Feedback-Loop Computersimulationen automatisiert mithilfe von Daten eines Prüfstands optimiert. Weiterführend können Datenanalysen direkt die Metadatenstruktur nutzen, um einen Mehrwert zu bieten, ohne auf die großen CAE-Daten selbst zugreifen zu müssen. Dadurch können mit wenig Aufwand Prozessstrukturen in Entwicklungsprojekten analysiert werden, um gute oder schlechte Abläufe in Entwicklungsprojekten zu identifizieren.

Publikationen

Ziegler, J., Reimann, P., Schulz, C., Keller, F., Mitschang, B.: A Graph Structure to Discover Patterns in Unstructured Processes of Product Development. In: 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science (IRI). pp. 222–227 (2022). https://doi.org/10.1109/IRI54793.2022.00057.
Zusammenfassung
A well-known information reuse approach is to exploit event logs for process discovery and optimization. However, process discovery is rarely used for product development projects. This is because information systems in product development, e. g., Product-Lifecycle-Management (PLM) systems, do not provide the event logs required by process discovery algorithms. Additionally, existing algorithms struggle with development projects, as these are unstructured and rich in variety. In this paper, we propose a novel approach to process discovery in order to make it applicable and tailored to product development projects. Instead of using flat event logs, we provide a graph-based data structure that is able to represent both activities and data of product development projects with the dataflow between activities. Based on this structure, we can leverage provenance available in PLM systems. Furthermore, we may use frequent subgraph mining to discover process patterns. Such patterns are well suited to describe different variants and common sub-processes of unstructured processes. Using a prototype, we evaluate this approach and successfully discover prevailing patterns. These patterns may be used by engineers to support their decision-making or help improve the execution of development projects.
BibTeX
@inproceedings{9874054, abstract = {A well-known information reuse approach is to exploit event logs for process discovery and optimization. However, process discovery is rarely used for product development projects. This is because information systems in product development, e. g., Product-Lifecycle-Management (PLM) systems, do not provide the event logs required by process discovery algorithms. Additionally, existing algorithms struggle with development projects, as these are unstructured and rich in variety. In this paper, we propose a novel approach to process discovery in order to make it applicable and tailored to product development projects. Instead of using flat event logs, we provide a graph-based data structure that is able to represent both activities and data of product development projects with the dataflow between activities. Based on this structure, we can leverage provenance available in PLM systems. Furthermore, we may use frequent subgraph mining to discover process patterns. Such patterns are well suited to describe different variants and common sub-processes of unstructured processes. Using a prototype, we evaluate this approach and successfully discover prevailing patterns. These patterns may be used by engineers to support their decision-making or help improve the execution of development projects.}, author = {Ziegler, Julian and Reimann, Peter and Schulz, Christoph and Keller, Florian and Mitschang, Bernhard}, booktitle = {2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science (IRI)}, doi = {10.1109/IRI54793.2022.00057}, pages = {222-227}, title = {A Graph Structure to Discover Patterns in Unstructured Processes of Product Development}, year = 2022 }
DOI
10.1109/IRI54793.2022.00057
Ziegler, J., Reimann, P., Keller, F., Mitschang, B.: A Metadata Model to Connect Isolated Data Silos and Activities of the CAE Domain. In: La Rosa, M., Sadiq, S., and Teniente, E. (eds.) Advanced Information Systems Engineering (CAiSE). pp. 213--228. Springer International Publishing, Cham (2021). https://doi.org/10.1007/978-3-030-79382-1_13.
Zusammenfassung
Computer-aided engineering (CAE) applications support the digital transformation of the manufacturing industry. They facilitate virtual product development and product testing via computer simulations. CAE applications generate vast quantities of heterogeneous data. Domain experts struggle to access and analyze them, because such engineering data are not sufficiently described with metadata. In this paper, we characterize the CAE domain and identify unsolved challenges for a tailored data and metadata management. For instance, work activities in product development projects and their relationships to data are not represented explicitly in current metadata models. We propose a metadata model that addresses all challenges and provides a connected view on all CAE data, metadata, and work activities of development projects. We validate the feasibility of our metadata model through a prototypical implementation and its application to a real-world use case. This verifies that our metadata model addresses the CAE-specific challenges and this way eases the task of domain experts to exploit relevant data.
BibTeX
@inproceedings{10.1007/978-3-030-79382-1_13, abstract = {Computer-aided engineering (CAE) applications support the digital transformation of the manufacturing industry. They facilitate virtual product development and product testing via computer simulations. CAE applications generate vast quantities of heterogeneous data. Domain experts struggle to access and analyze them, because such engineering data are not sufficiently described with metadata. In this paper, we characterize the CAE domain and identify unsolved challenges for a tailored data and metadata management. For instance, work activities in product development projects and their relationships to data are not represented explicitly in current metadata models. We propose a metadata model that addresses all challenges and provides a connected view on all CAE data, metadata, and work activities of development projects. We validate the feasibility of our metadata model through a prototypical implementation and its application to a real-world use case. This verifies that our metadata model addresses the CAE-specific challenges and this way eases the task of domain experts to exploit relevant data.}, address = {Cham}, author = {Ziegler, Julian and Reimann, Peter and Keller, Florian and Mitschang, Bernhard}, booktitle = {Advanced Information Systems Engineering (CAiSE)}, doi = {10.1007/978-3-030-79382-1_13}, editor = {La Rosa, Marcello and Sadiq, Shazia and Teniente, Ernest}, isbn = {978-3-030-79382-1}, pages = {213--228}, publisher = {Springer International Publishing}, title = {A Metadata Model to Connect Isolated Data Silos and Activities of the CAE Domain}, year = 2021 }
DOI
10.1007/978-3-030-79382-1_13
Ziegler, J., Reimann, P., Keller, F., Mitschang, B.: A Graph-based Approach to Manage CAE Data in a Data Lake. In: Procedia CIRP: Proceedings of the 53rd CIRP Conference on Manufacturing Systems (CIRP CMS 2020). pp. 496–501. Elsevier (2020). https://doi.org/10.1016/j.procir.2020.04.155.
Zusammenfassung
Computer-aided engineering (CAE) applications generate vast quantities of heterogeneous data. Domain experts often fail to explore and analyze these data, because they are not integrated across different applications. Existing data management solutions are rather tailored to scientific applications. In our approach, we tackle this issue by combining a data lake solution with graph-based metadata management. This provides a holistic view of all CAE data and of the data-generating applications in one interconnected structure. Based on a prototypical implementation, we discuss how this eases the task of domain experts to explore and extract data for further analyses.
BibTeX
@inproceedings{INPROC-2020-18, abstract = {Computer-aided engineering (CAE) applications generate vast quantities of heterogeneous data. Domain experts often fail to explore and analyze these data, because they are not integrated across different applications. Existing data management solutions are rather tailored to scientific applications. In our approach, we tackle this issue by combining a data lake solution with graph-based metadata management. This provides a holistic view of all CAE data and of the data-generating applications in one interconnected structure. Based on a prototypical implementation, we discuss how this eases the task of domain experts to explore and extract data for further analyses.}, author = {Ziegler, Julian and Reimann, Peter and Keller, Florian and Mitschang, Bernhard}, booktitle = {Procedia CIRP: Proceedings of the 53rd CIRP Conference on Manufacturing Systems (CIRP CMS 2020)}, cr-category = {H.2.8 Database Applications}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems}, doi = {10.1016/j.procir.2020.04.155}, institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany}, issn = {2212-8271}, language = {English}, month = {09}, pages = {496 - 501}, publisher = {Elsevier}, title = {A Graph-based Approach to Manage CAE Data in a Data Lake}, type = {Conference Paper}, url = {http://www.sciencedirect.com/science/article/pii/S2212827120310349}, volume = 93, year = 2020 }
Link
http://www.sciencedirect.com/science/article/pii/S2212827120310349
DOI
10.1016/j.procir.2020.04.155

Lehre

Laufende Arbeiten

Evaluation von Deep-Learning-Verfahren zur datengetriebenen Erstellung von Surrogatmodellen für CAE-Simulationen
Masterarbeit, Universität Stuttgart, 2020
Konzeption und Realisierung eines Werkzeugs zur Extraktion von Metadaten aus einem heterogenen Datenbestand des Computer-Aided Engineering
Bachelorarbeit, Universität Stuttgart, 2020
Konzeption und Realisierung eines Werkzeugs zur Visualisierung von Metadaten des Computer-Aided Engineering
Bachelorarbeit, Universität Stuttgart, 2020

Abgeschlossene Arbeiten

Visualisierung und Exploration eines Datenbestandes mit graphbasierter Metadatenverwaltung
Bachelor Forschungsprojekt Informatik, Universität Stuttgart, 2020
Approximation aufwendiger Simulationen durch datengetriebene Surrogatmodelle
Bachelorarbeit, Universität Stuttgart, 2020
Konzeption einer Ontologie zur Beschreibung von Daten der CAE-Domäne
Bachelorarbeit, Universität Stuttgart, 2020
Softwarearchitektur für ein graph-basiertes Metadatenmanagement von CAE Daten
Masterarbeit, Universität Stuttgart, 2020

Teamseite

Julian Ziegler

Kontakt

Sprechstunde

Fachgebiet

Publikationen

Zusammenfassung

BibTeX

DOI

Zusammenfassung

BibTeX

DOI

Zusammenfassung

BibTeX

Link

DOI

Lehre

Zielgruppe

Formalia

Services

Organisation

Julian Ziegler

Kontakt

Sprechstunde

Fachgebiet

Publikationen

Zusammenfassung

BibTeX

DOI

Zusammenfassung

BibTeX

DOI

Zusammenfassung

BibTeX

Link

DOI

Lehre

So erreichen Sie uns

Zielgruppe

Formalia

Services

Organisation