@inproceedings{47108,
  author       = {{Gräßler, Iris and Özcan, Deniz and Preuß, Daniel}},
  booktitle    = {{Design fox X - Beiträge zum 34. DfX-Symposium}},
  editor       = {{Krause, Dieter and Paetzold-Byhain, Kristin and Wartzack, Sandro}},
  location     = {{Radebeul}},
  pages        = {{163 -- 172}},
  title        = {{{KI-basierte Extrahierung von Anforderungen aus Regularien für die Automobilentwicklung}}},
  doi          = {{10.35199/dfx2023.17}},
  volume       = {{34}},
  year         = {{2023}},
}

@inproceedings{46450,
  author       = {{Gräßler, Iris and Preuß, Daniel and Brandt, Lukas and Mohr, Michael}},
  booktitle    = {{Proceedings of the Design Society}},
  location     = {{Bordeaux}},
  pages        = {{1595--1604}},
  title        = {{{Efficient Formalisation of Technical Requirements for Generative Engineering}}},
  doi          = {{10.1017/pds.2023.160}},
  year         = {{2023}},
}

@inproceedings{45661,
  abstract     = {{Effect chain modelling is a method for creating information
models for impact analyses of changes in system elements. For
the estimation of change propagation, dependencies between
requirements must be detected. The high number of require-
ment dependencies in the engineering of complex technical
systems results in the need for automation. In a study, it was
shown that transformer models (BERT) are suitable for the
automated dependency analysis of requirements. However,
there are currently deficits in the applicability of the models
for different projects without an extensive and heterogeneous
training database. This paper investigates how active learning
can be used to train BERT models (active-BERT) in order to
increase the performance of the models for classifying requi-
rement dependencies of projects with heterogeneous require-
ments. The results show that the performance of the models
increases significantly through active learning. Through active-
BERT, engineers are enabled to model effect chains efficiently
and to handle requirement changes effectively.}},
  author       = {{Gräßler, Iris and Preuß, Daniel}},
  booktitle    = {{Stuttgarter Symposium für Produktentwicklung SSP 2023}},
  editor       = {{Hölzle, Katharina and Kreimeyer, Matthias and Roth, Daniel and Maier, Thomas and Riedel, Oliver}},
  issn         = {{2364-4885}},
  location     = {{Stuttgart}},
  publisher    = {{Fraunhofer IAO}},
  title        = {{{Automatisierte Abhängigkeitsanalyse von Anforderungen zur Wirkkettenmodellierung}}},
  year         = {{2023}},
}

@article{29891,
  author       = {{Gräßler, Iris and Preuß, Daniel and Pottebaum, Jens}},
  issn         = {{0720-8928}},
  journal      = {{Softwaretechnik-Trends}},
  number       = {{1}},
  pages        = {{15--16}},
  publisher    = {{Köllen Druck & Verlag GmbH}},
  title        = {{{Extrahierung von Anforderungen aus natürlich-sprachlichen Lastenheften: Was erschwert eine KI-basierte Extrahierung?}}},
  volume       = {{42}},
  year         = {{2022}},
}

@article{31791,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Requirements changes are a leading cause for project failures. Due to propagation effects, change management requires dependency analysis. Existing approaches have shortcomings regarding ability to process large requirement sets, availability of required data, differentiation of propagation behavior and consideration of higher order dependencies. This paper introduces a new method for advanced requirement dependency analysis based on machine learning. Evaluation proves applicability and high performance by means of a case example, 4 development projects and 3 workshops with industry experts.</jats:p>}},
  author       = {{Gräßler, Iris and Oleff, Christian and Hieb, Michael and Preuß, Daniel}},
  issn         = {{2732-527X}},
  journal      = {{Proceedings of the Design Society}},
  pages        = {{1865--1874}},
  publisher    = {{Cambridge University Press (CUP)}},
  title        = {{{Automated Requirement Dependency Analysis for Complex Technical Systems}}},
  doi          = {{10.1017/pds.2022.189}},
  volume       = {{2}},
  year         = {{2022}},
}

@inproceedings{33892,
  author       = {{Gräßler, Iris and Tusek, Alena Marie and Thiele, Henrik and Preuß, Daniel and Grewe, Benedikt and Hieb, Michael}},
  booktitle    = {{XXXIII ISPIM Innovation Conference Proceedings}},
  isbn         = {{978-952-335-694-8}},
  location     = {{Copenhagen, Denmark}},
  publisher    = {{ LUT Scientific and Expertise Publications}},
  title        = {{{Literature study on the potential of Artificial Intelligence in Scenario-Technique}}},
  year         = {{2022}},
}

@inproceedings{33913,
  author       = {{Gräßler, Iris and Preuß, Daniel and Brandt, Lukas and Mohr, Michael}},
  booktitle    = {{Proceedings of 8th IEEE International Symposium on Systems Engineering 2022}},
  location     = {{Wien}},
  title        = {{{Efficient Extraction of Technical Requirements Applying Data Augmentation}}},
  year         = {{2022}},
}

@article{30213,
  abstract     = {{<jats:p>Requirement changes and cascading effects of change propagation are major sources of inefficiencies in product development and increase the risk of project failure. Proactive change management of requirement changes yields the potential to handle such changes efficiently. A systematic approach is required for proactive change management to assess and reduce the risk of a requirement change with appropriate effort in industrial application. Within the paper at hand, a novel method for Proactive Management of Requirement Changes (ProMaRC) is presented. It is developed in close collaboration with industry experts and evaluated based on workshops, pilot users’ feedback, three industrial case studies from the automotive industry and five development projects from research. To limit the application effort, an automated approach for dependency analysis based on the machine learning technique BERT and semi-automated assessment of change likelihood and impact using a modified PageRank algorithm is developed. Applying the method, the risks of requirement changes are assessed systematically and reduced by means of proactive change measures. Evaluation shows high performance of dependency analysis and confirms the applicability and usefulness of the method. This contribution opens up the research space of proactive risk management for requirement changes which is currently almost unexploited. It enables more efficient product development.</jats:p>}},
  author       = {{Gräßler, Iris and Oleff, Christian and Preuß, Daniel}},
  issn         = {{2076-3417}},
  journal      = {{Applied Sciences}},
  keywords     = {{Fluid Flow and Transfer Processes, Computer Science Applications, Process Chemistry and Technology, General Engineering, Instrumentation, General Materials Science}},
  number       = {{4}},
  publisher    = {{MDPI AG}},
  title        = {{{Proactive Management of Requirement Changes in the Development of Complex Technical Systems}}},
  doi          = {{10.3390/app12041874}},
  volume       = {{12}},
  year         = {{2022}},
}

@article{31647,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Effect chain modeling approaches are applied to model cause-effect relations and analyze affected elements and dependencies. In this paper a systematic literature research is conducted to derive main characteristics and limitations of existing approaches. Then, the Model-based Effect Chain Analysis (MECA) method is introduced. Evaluation proves applicability of the method by means of a case example. This is done in the context of a project with a German automotive company. In the project 66 workshops were conducted to model certification-compliant effect chains in accordance to the UN ECE 156.</jats:p>}},
  author       = {{Gräßler, Iris and Wiechel, Dominik and Koch, Anna-Sophie and Preuß, Daniel and Oleff, Christian}},
  issn         = {{2732-527X}},
  journal      = {{Proceedings of the Design Society}},
  pages        = {{1885--1894}},
  publisher    = {{Cambridge University Press (CUP)}},
  title        = {{{Model-Based Effect-Chain Analysis for Complex Systems}}},
  doi          = {{10.1017/pds.2022.191}},
  volume       = {{2}},
  year         = {{2022}},
}

@inproceedings{23391,
  abstract     = {{In der Softwareentwicklung werden Requirement Mining-Ansätze eingesetzt, um in der Ermittlung von Anforderungen Informationen aus Benutzerrezensionen zu extrahieren. Auf der Online-Plattform Amazon werden verschiedene mechatronische Produkte des B2C-Markts vertrieben und deren Benutzerrezensionen gesammelt. Aufgrund der Komplexität mechatronischer Produkte werden Defizite selten nachvollziehbar im Benutzer-Feedback dokumentiert. In diesem Beitrag wird die Forschungsfrage beantwortet, ob Requirement Mining-Ansätze auch in der Produktgenerationenentwicklung mechatronischer Produkte des B2C-Markts anwendbar sind. Etablierte Requirement Mining-Ansätze werden in einer Literaturstudie identifiziert und die Anwendbarkeit initial bewertet. Der vielversprechendste Ansatz wird für eine weitergehende Analyse ausgewählt. Hierzu wird ein Fallbeispiel untersucht, indem Benutzeranforderungen eines Staubsauger- Roboters ausgewertet werden. Die Ergebnisse zeigen, dass die Informationsqualität hoch ist und Anforderungsingenieure diese Informationen zur Dokumentation der Bedürfnisse der Benutzer verwenden können.}},
  author       = {{Gräßler, Iris and Preuß, Daniel}},
  booktitle    = {{Digital-Fachtagung VDI Mechatronik 2021; 24. - 25. Mrz. 2021}},
  editor       = {{Bertram, Torsten and Corves, Burkhard and Janschek, Klaus and Rinderknecht, Stephan}},
  pages        = {{68--73}},
  title        = {{{Anwendbarkeit von Requirement Mining in Benutzerrezensionen für die Entwicklung mechatronischer Produkte im B2C-Markt}}},
  year         = {{2021}},
}

@inproceedings{24017,
  abstract     = {{In developing complex technical systems, requirements are subject to continuous change. Systematic and holistic change impact analysis and proactive measures are required for reducing the number of requirement changes and their negative impact. There is no method to analyse the holistic impact of a requirement change in the context of developing complex technical systems. Holistic analysis requires to consider the local effects of requirement changes as well as effects from change propagation. To develop an approach for holistic change propagation and impact analysis, twelve performance goals are defined. Those are derived from a state of research analysis as well as an industry workshop. A three-step method is proposed. Firstly, requirement dependencies that cause change propagation are detected. Secondly, critical requirements are automatically identified based on a Page Rank algorithm. Thirdly, change impact of critical requirements is analysed based on a guideline. Validation proves that ten goals are fulfilled and two are partly fulfilled. The method addresses major shortcomings of preceding research and enables sound decision making for development engineers both before a change occurs and during decision process on a change request. This helps to reduce negative change impact in development projects and the risk of project failure.}},
  author       = {{Gräßler, Iris and Oleff, Christian and Preuß, Daniel}},
  editor       = {{Wagner, Beverly and Wilson, Juliette}},
  location     = {{Strathclyde/Glasgow}},
  title        = {{{Holistic change propagation and impact analysis in requirements management}}},
  year         = {{2021}},
}

@article{24037,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Innovation projects are characterized by numerous uncertainties. Typical concepts in development management like the application of safety coefficients imply limitations of the solution space. In contrast, explicit handling of uncertainties can support engineers in understanding the problem space and in utilising the full potential of the design space along iterative product development steps. As a result from literature analysis, there is a lack of a support for product development that addresses the specific problem of uncertainty and risk in the context of requirement changes. The aim of the contribution at hand is to enhance the efficient development of complex interdisciplinary systems by enabling uncertainty handling in requirements change management. Based on a classification of uncertainty types resulting in a descriptive model, risk management measures are identified to support requirements engineers. The proposed method includes identification &amp; modelling, analysis, treatment and monitoring of risks and counter-measures. By applying this method, engineers are supported in adopting agile approaches and enabling flexible Requirements Engineering.</jats:p>}},
  author       = {{Gräßler, Iris and Pottebaum, Jens and Oleff, Christian and Preuß, Daniel}},
  issn         = {{2732-527X}},
  journal      = {{Proceedings of the Design Society}},
  location     = {{Gothenburg}},
  pages        = {{1687--1696}},
  title        = {{{Handling of explicit Uncertainty in Requirements Change Management}}},
  doi          = {{10.1017/pds.2021.430}},
  volume       = {{1}},
  year         = {{2021}},
}

@inproceedings{26866,
  author       = {{Gräßler, Iris and Roesmann, Daniel and Wiechel, Dominik and Preuß, Daniel and Pottebaum, Jens}},
  booktitle    = {{54th CIRP Conference on Manufacturing Systems}},
  location     = {{Athens}},
  title        = {{{Determine similarity of assembly operations using semantic technology}}},
  doi          = {{https://doi.org/10.1016/j.procir.2021.11.209 }},
  year         = {{2021}},
}

@misc{27680,
  author       = {{Gräßler, Iris and Hentze, Julian and Hesse, Philipp and Preuß, Daniel and Thiele, Henrik and Wiechel, Dominik and Bothen, Martin and Bruckmann, Tobias  and Dattner, Michael and Ehl, Thomas and Hawlas, Martin and Krimpmann, Christoph and Lachmayer, Roland and Knöchelmann, Marvin and Mock, Randolf and Mozgova, Iryna and Schneider, Maximilian and Stollt, Guido}},
  pages        = {{67}},
  publisher    = {{Ed.: VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik}},
  title        = {{{VDI/VDE 2206 - Entwicklung mechatronischer und cyber-physischer Systeme}}},
  year         = {{2021}},
}

@inproceedings{23505,
  author       = {{Gräßler, Iris and Preuß, Daniel and Oleff, Christian}},
  booktitle    = {{Proceedings of the 31st Symposium Design for X (DFX2020); 16. - 18. Sep. 2020}},
  editor       = {{Krause, Dieter and Paetzold, Kristin and Wartzack, Sandro}},
  pages        = {{199--208}},
  title        = {{{Automatisierte Identifikation und Charakterisierung von Anforderungsabhängigkeiten – Literaturstudie zum Vergleich von Lösungsansätzen}}},
  doi          = {{10.35199/dfx2020.21}},
  year         = {{2020}},
}

@inproceedings{23720,
  abstract     = {{Die Instandsetzung von sicherheitskritischen Komponenten durch Besatzungsmitglieder auf See erfordert technische und organisa-torische Unterstützungsmaßnahmen. Zur Instandsetzung kritischer Systeme auf See bietet AR-Technologie erkennbare Potenziale (Räumliche Visualisierung, Kontextualisierung). Zugleich sollen Instandsetzungs-Einsätze im Sinne des informellen arbeits- und einsatzbezogenen Lernens zum Kompetenzerwerb genutzt werden. Dazu wird eine AR-Architektur vorgestellt, die das Lernen im Anwendungsfall ‚Instandsetzung‘ integriert.}},
  author       = {{Gräßler, Iris and Pottebaum, Jens and Taplick, Patrick and Roesmann, Daniel and Preuß, Daniel}},
  booktitle    = {{Go-3D 2019 "Mit 3D Richtung Maritim 4.0" - Tagungsband zur Konferenz Go-3D 2019}},
  editor       = {{Lukas, Uwe and Bauer, Kristine and Dolereit, Tim}},
  pages        = {{45--57}},
  publisher    = {{Fraunhofer Verlag}},
  title        = {{{Unterstützung des Lernens für kritische Situationen: Potenzial von Augmented Reality für die Instandsetzung auf See}}},
  year         = {{2019}},
}