@inproceedings{55308,
  abstract     = {{Established companies are undertaking major transformation initiatives of their corporate structures and organisational forms to cope with the complexity during the engineering of cyber-physical production systems (CPPS). A frequently discussed issue is the measurability of this transformation progress. This paper conducts a systematic literature analysis of approaches regarding measurability of transformation and evaluates their application in the context of a systems engineering transformation. Measure-ment criteria are derived from the identified approaches, categorised, and finally evaluated by industry experts regarding their applicability. The categorised measurement criteria can be used to accurately measure the progress of a transformation process.}},
  author       = {{Gräßler, Iris and Grewe, Benedikt}},
  keywords     = {{Organizational Transformation, Systems Engineering, Meausrement, Metrics, Organizational Change}},
  location     = {{Ischia, Italy}},
  title        = {{{Measuring Systems Engineering Transformation: A systematic literature review}}},
  doi          = {{https://doi.org/10.1016/j.procir.2026.01.202}},
  year         = {{2026}},
}

@inproceedings{64602,
  author       = {{Gräßler, Iris and Hesse, Philipp and Jahnke, Ulrich and Habdank, Matthias}},
  booktitle    = {{Procedia CIRP}},
  issn         = {{2212-8271}},
  pages        = {{915--920}},
  publisher    = {{Elsevier BV}},
  title        = {{{Verification of CO2 emissions for the generative design of lightweight mobility systems using digital product passport}}},
  doi          = {{10.1016/j.procir.2026.01.158}},
  volume       = {{138}},
  year         = {{2026}},
}

@inproceedings{64603,
  author       = {{Gräßler, Iris and Tusek, Alena Marie}},
  booktitle    = {{Procedia CIRP}},
  issn         = {{2212-8271}},
  pages        = {{945--950}},
  publisher    = {{Elsevier BV}},
  title        = {{{Sustainability criteria for future foresight in manufacturing companies}}},
  doi          = {{10.1016/j.procir.2026.01.163}},
  volume       = {{138}},
  year         = {{2026}},
}

@article{59478,
  author       = {{Gräßler, Iris and Rarbach, Sven and Pottebaum, Jens}},
  issn         = {{2942-6170}},
  journal      = {{Industry 4.0 Science}},
  number       = {{2}},
  publisher    = {{GITO mbH Verlag}},
  title        = {{{Data Quality in the Engineering of Circular Products - Decision support for circular value creation through data ecosystems}}},
  doi          = {{10.30844/i4se.25.2.12}},
  volume       = {{2025}},
  year         = {{2025}},
}

@article{58076,
  abstract     = {{This paper presents the concept of Information Circularity Assistance, which provides decision support in the early stages of product creation for Circular Economy. Engineers in strategic product planning need to proactively predict the quantity, quality, and timing of secondary materials and returned components. For example, products with high recycled content will only be economically sustainable if the material is actually available in the future product life. Our assumption is that Information Circularity Assistance enables decision makers to incorporate insights from extreme data – high-volume, high-velocity, heterogeneous and distributed data from the product life – into product creation through intelligent Digital Twins. Artificial Intelligence can help to derive sustainable actions in favor of circular products by processing extreme data and enriching it with expert knowledge. The research contributes in three key dimensions. First, a comprehensive literature review is conducted. This review covers concepts of intelligence in Scenario-Technique for strategic product planning, Digital Twin-based analysis of extreme data and relevant technologies from Data Science and Artificial Intelligence. In all areas, the state of the art and emerging trends are identified. Secondly, the study identifies information needs along the steps of the Scenario-Technique and information offerings based on Digital Twins. The concept of Information Circularity Assistance results from the coupling of these demands and offerings, extending the Scenario-Technique beyond traditional expert-based methods. Third, we extend existing Digital Twin methods used in circularity and discuss the deployment of Data Science and Artificial Intelligence algorithms within the product creation process. Our approach uses extreme data to provide a strategic advantage in optimizing product life cycle planning, which is illustrated by two sample applications. The aim is to provide Information Circularity Assistance that will support experienced product planners, developers, and decision makers in the future.}},
  author       = {{Gräßler, Iris and Weyrich, Michael and Pottebaum, Jens and Kamm, Simon}},
  issn         = {{0178-2312}},
  journal      = {{at - Automatisierungstechnik}},
  keywords     = {{Scenario-Technique, Artificial Intelligence, Digital Twin, Large Language Models}},
  number       = {{1}},
  pages        = {{3--21}},
  publisher    = {{Walter de Gruyter GmbH}},
  title        = {{{Information Circularity Assistance based on extreme data}}},
  doi          = {{10.1515/auto-2024-0039}},
  volume       = {{73}},
  year         = {{2025}},
}

@article{58650,
  abstract     = {{Technical systems are characterized by increasing interdisciplinarity, complexity and networking. A product and its corresponding production systems require interdisciplinary multi-objective optimization. Sustainability and recyclability demands increase said complexity. The efficiency of previously established engineering methods is reaching its limits, which can only be overcome by systematic integration of extreme data. The aim of "hybrid decision support" is as follows: Data science and artificial intelligence should be used to supplement human capabilities in conjunction with existing heuristics, methods, modeling and simulation to increase the efficiency of product creation.}},
  author       = {{Gräßler, Iris and Pottebaum, Jens and Nyhuis, Peter and Stark, Rainer and Thoben, Klaus-Dieter and Wiederkehr, Petra}},
  issn         = {{2942-6170}},
  journal      = {{Industry 4.0 Science}},
  keywords     = {{AI, artificial intelligence, Data Science, decision support, extreme data, Künstliche Intelligenz, product creation, product development}},
  number       = {{1}},
  publisher    = {{GITO mbH Verlag}},
  title        = {{{Hybrid Decision Support in Product Creation - Improving performance with data science and artificial intelligence}}},
  doi          = {{10.30844/i4sd.25.1.18}},
  volume       = {{2025}},
  year         = {{2025}},
}

@inproceedings{61057,
  abstract     = {{Verification and Validation (V&V) are essential processes in engineering Cyber-Physical Systems. However, the role of V&V engineers is often not given sufficient attention. Based on a systematic literature analysis and practical observations, a four-step method for Test-oriented Resilient Requirements Engineering (ToRRE) is developed. The steps are planning V&V, executing V&V activities, documenting V&V activities and analyzing results of V&V activities. Applying ToRRE ensures continuous information flow and traceability. Engineers are enabled to analyze requirements using engineering artifacts connected through Model-Based Systems Engineering. Adopting methods for Model-Based Effect Chain analysis to evaluated test cases and test scenarios, conclusions on requirements engineering and change management are enabled. The method is evaluated in an EU research project.}},
  author       = {{Gräßler, Iris and Ebel, Marcel}},
  booktitle    = {{Proceedings of the Design Society}},
  issn         = {{2732-527X}},
  keywords     = {{systems engineering (SE), product modelling/models, design methods, verification & validation, test cases & test scenarios}},
  location     = {{Dallas, Texas, USA}},
  pages        = {{3031--3040}},
  publisher    = {{Cambridge University Press (CUP)}},
  title        = {{{Test-oriented Resilient Requirements Engineering (ToRRE): extending model-based effect chain analysis to verification objectives}}},
  doi          = {{10.1017/pds.2025.10317}},
  volume       = {{5}},
  year         = {{2025}},
}

@inproceedings{61060,
  abstract     = {{In early operational phases of severe weather events, a lack of
information challenges emergency management teams to gain
an overview of the situation and make informed decisions. To
support situational exploration, unmanned aerial and ground
vehicles attract increasing attention, primarily used to
document operational sites. However, they offer further
potential in early operational phases. To ensure their reliable
use for exploration, decision-makers must be aware of
opportunities and limitations under prevailing conditions. For
this, use cases for robotic simulation in emergency response
are presented, considering technical restrictions and dynamic
influences from weather impacts. The approach of integrating
rescue robot simulation into the response phase is developed
following a five-step research design. Existing use cases of
rescue robot simulation are identified in a systematic literature
analysis. The results are extended with use cases developed for
urban flooding scenarios. Subsequently, use cases are assessed
and selected for implementation in the simulation environment
Gazebo. Finally, the results are validated with end users in the
EU research project CREXDATA, which focuses on decision
support based on processing extreme data. The implemented
use cases demonstrate the potential of robotic simulation in
emergency response to accelerate action planning in decisionmaking and provide a more detailed picture, enabling betterinformed decisions. }},
  author       = {{Gräßler, Iris and Döhner, Niklas and Ebel, Marcel and Pottebaum, Jens}},
  booktitle    = {{Mensch und Computer 2025 - Workshopband}},
  keywords     = {{robotic simulation, rescue robots, emergency response, extreme weather}},
  location     = {{Chemnitz}},
  title        = {{{Shifting boundaries from preparedness to response: Using simulation of rescue robots in weather-induced emergencies}}},
  doi          = {{10.18420/muc2025-mci-ws01-187}},
  year         = {{2025}},
}

@inproceedings{61109,
  author       = {{Pottebaum, Jens and Gräßler, Iris and Ebel, Marcel and Özcan, Deniz and Döhner, Niklas and Pratzler-Wanczura, Sylvia and Derin, Enes and Krüger, Oliver and Kruijff-Korbayova, Ivana and Stampa, Merlin}},
  location     = {{Koblenz, Deutschland}},
  pages        = {{81--94}},
  publisher    = {{LibreCat University}},
  title        = {{{EU-Projekt CREXDATA: Erkenntnisse und Handlungsempfehlungen zum Einsatz KI-generierter Lageinformationen für die Lagebewertung und Maßnahmenplanung in Extremwetterlagen}}},
  doi          = {{10.5281/ZENODO.16740824}},
  year         = {{2025}},
}

@inproceedings{61043,
  abstract     = {{<jats:p>Dynamic market conditions, technological disruption and social change require organizations to continuously adapt and evolve. However, studies on organizational change show that the majority of transformations undertaken fail because they are characterized by a lack of clarity, overload and ineffective measures. This paper shows how a clear structure as a critical success factor can make the chaos and challenges of a transformation manageable.  The focus here is on a practice-oriented framework that divides a transformation into nine essential building blocks with activities that are critical to success. The structure of the framework is understood as a flexible organizing principle for a transformation without hindering creativity and dynamics. Case studies show the adaptability and applicability of the framework to different characteristics and dimensions of transformation. The transformation framework provides an operative structure and enables transformation managers for transparent orchestration and implementation of transformation.</jats:p>}},
  author       = {{Gräßler, Iris and Grewe, Benedikt and Fritzen, Marc}},
  booktitle    = {{AHFE International}},
  issn         = {{2771-0718}},
  location     = {{Pula, Croatia}},
  publisher    = {{AHFE International}},
  title        = {{{The importance of structure in transformation chaos: A Transformation Framework}}},
  doi          = {{10.54941/ahfe1006790}},
  volume       = {{198}},
  year         = {{2025}},
}

@inproceedings{61055,
  abstract     = {{<jats:title>ABSTRACT:</jats:title><jats:p>Challenges of increasing system complexity and the need for interdisciplinary collaboration are prompting companies to reorganize towards Systems Engineering (SE). As part of the implementation of large-scale transformation programs, transformation progress is of great interest to management and employees involved. Existing maturity models lack measurable variables and reliable forecast. For this reason, a maturity model for evaluating SE Transformation is developed, that builds on quantitative metrics and enables an overarching view on transformation considering cultural aspects. Literature-based criteria for evaluating SE Transformation lay the foundation for measures and referenced metrics and indicators. Due to its data-centricity, the model presented enables a more comprehensive, fact-based decision-making basis for the design and steering of SE Transformation programs.</jats:p>}},
  author       = {{Graessler, Iris and Grewe, Benedikt and Felgen, Luc}},
  booktitle    = {{Proceedings of the Design Society}},
  issn         = {{2732-527X}},
  location     = {{Dallas, USA}},
  pages        = {{1081--1090}},
  publisher    = {{Cambridge University Press (CUP)}},
  title        = {{{Data-driven decision support in the design and controlling of systems engineering transformation: a maturity model}}},
  doi          = {{10.1017/pds.2025.10122}},
  volume       = {{5}},
  year         = {{2025}},
}

@article{60140,
  abstract     = {{<jats:title>Abstract</jats:title>
	  <jats:p>The increasing prevalence of embedded software in today’s vehicles is leading to growing complexity, which can only be managed effectively through the use of reliable interdisciplinary engineering processes. With this in mind, systems engineering (SE) is currently being introduced on a large scale into the automotive industry. Pilot projects have demonstrated the potential for implementing changes, but these have not yet been accompanied by viable implementation concepts for SE. In the context of the proposed application-based research, the SETup automotive method (<jats:bold>S</jats:bold>ystems <jats:bold>E</jats:bold>ngineering <jats:bold>T</jats:bold>ransformation <jats:bold>u</jats:bold>nder <jats:bold>p</jats:bold>iloting in the <jats:bold>automotive</jats:bold> industry) is presented, which comprises a step-by-step procedure of introducing SE into large automotive companies. By introducing SE by pilot projects first, both an in-process tailoring of all processes, methods, tools and structures (PMTS) required for the introduction and an in-process validation of the pilot scheme elaborated by the pilot projects are achieved. The presented method builds upon fundamental approaches to change management, which have been developed over many years in both research and practice. It has been validated by the industrial practice of SE transformation at German car manufacturers and suppliers. As a result, decision-makers, transformation managers and systems engineers are provided with a scientifically based and field-tested set of steps for the introduction of SE in their own company.</jats:p>}},
  author       = {{Graessler, Iris and Grewe, Benedikt}},
  issn         = {{2053-4701}},
  journal      = {{Design Science}},
  publisher    = {{Cambridge University Press (CUP)}},
  title        = {{{SETup automotive: a Method for Systems Engineering Transformation in automotive industry}}},
  doi          = {{10.1017/dsj.2025.10}},
  volume       = {{11}},
  year         = {{2025}},
}

@article{60940,
  author       = {{Gräßler, Iris and Rarbach, Sven and Grewe, Benedikt}},
  issn         = {{2942-6170}},
  journal      = {{Industry 4.0 Science}},
  number       = {{3}},
  publisher    = {{GITO mbH Verlag}},
  title        = {{{Strategic Product Planning Model – Digital twins for circular products and production processes}}},
  doi          = {{10.30844/i4se.25.3.24}},
  volume       = {{2025}},
  year         = {{2025}},
}

@inproceedings{61099,
  author       = {{Gräßler, Iris and Rarbach, Sven}},
  booktitle    = {{Procedia CIRP}},
  issn         = {{2212-8271}},
  pages        = {{207--212}},
  publisher    = {{Elsevier BV}},
  title        = {{{Model-based Impact Analysis for Engineering Sustainable Products in Value Creation Networks}}},
  doi          = {{10.1016/j.procir.2025.08.037}},
  volume       = {{136}},
  year         = {{2025}},
}

@inproceedings{62153,
  author       = {{Gräßler, Iris and Grewe, Benedikt}},
  booktitle    = {{Procedia CIRP}},
  issn         = {{2212-8271}},
  pages        = {{936--942}},
  publisher    = {{Elsevier BV}},
  title        = {{{Structuring Systems Engineering Transformation: A three-step cycle of Transformation}}},
  doi          = {{10.1016/j.procir.2025.08.159}},
  volume       = {{136}},
  year         = {{2025}},
}

@inproceedings{60013,
  author       = {{Gräßler, Iris and Pottebaum, Jens and Nyhuis, Peter and Schmidt, Matthias and Grewe, Benedikt and Vollenkemper, Felix and Hesse, Thomas and Meinecke, Tim}},
  booktitle    = {{Stuttgarter Symposium für Produktentwicklung (SSP) 2025}},
  editor       = {{Hölzle, Katharina and Kreimeyer, Matthias and Roth, Daniel and Maier, Thomas and Riedel, Oliver}},
  location     = {{Stuttgart}},
  pages        = {{509--518}},
  publisher    = {{Fraunhofer IAO}},
  title        = {{{Evolving Design for Assembly, Disassembly and Reassembly into a new paradigm: Design-for-Capabilities with Hybrid Decision Support as an enabler for circular products}}},
  year         = {{2025}},
}

@article{58236,
  abstract     = {{<jats:p>In the engineering of complex technical systems, Systems Engineering (SE) is a key approach that is becoming increasingly relevant in more and more industries due to the ever-increasing complexity of systems. Over the decades of practical application and research, various specializations and forms of the Systems Engineering approach have developed, but there has so far been a lack of an overarching context and positioning in meaningful stages for the introduction of Systems Engineering in companies. For this reason, this research will systematize common Systems Engineering approaches and bring them together in a stage model for Systems Engineering. Based on a systematic literature review, use cases are identified for each approach and stage, which support companies in selecting an approach suitable for their own organization.</jats:p>}},
  author       = {{Gräßler, Iris and Grewe, Benedikt}},
  issn         = {{2079-8954}},
  journal      = {{Systems}},
  keywords     = {{Systems Engineering Transformation, maturity, Systems Engineering stages, approaches, SE}},
  number       = {{1}},
  publisher    = {{MDPI AG}},
  title        = {{{Stages of Systems Engineering: An Analysis and Characterization of Systems Engineering Approaches}}},
  doi          = {{10.3390/systems13010053}},
  volume       = {{13}},
  year         = {{2025}},
}

@inproceedings{62181,
  abstract     = {{<jats:p>This research investigates how Artificial Intelligence (AI) can be systematically integrated into existing business processes by combining suitable competencies with graphical AI workflow modelling. While AI offers a high potential for automation and increased efficiency, its implementation often fails due to a lack of interdisciplinary competencies that bridge the gap between domain expertise and IT know-how. Low-code platforms and visual modelling tools are increasingly recognised as enablers, empowering non-programmers to intuitively create graphical AI- based workflows. Nevertheless, specific competencies are required to realise the full potential of AI, the domain specific knowledge and align technical understanding with AI capabilities. The paper reviews the state of the art in AI-driven business process automation and competencies for visual low-code approaches. It then presents a practical solution to identify and systematise essential competence areas. Based on this, a practical competence model is developed to support the design of user-friendly, AI-enabled workflows. This is tested in a practical application context — emergency management — where it supports critical decision-making processes and is validated through expert feedback. The study concludes by offering actionable recommendations to help organisations foster the necessary competencies and methods for competently integrating AI into their digital processes.</jats:p>}},
  author       = {{Gräßler, Iris and Özcan, Deniz}},
  booktitle    = {{AHFE International}},
  issn         = {{2771-0718}},
  location     = {{Split}},
  publisher    = {{AHFE International}},
  title        = {{{Graphical AI workflow modelling: Identifying relevant competencies in AI-based automation of business processes}}},
  doi          = {{10.54941/ahfe1006785}},
  volume       = {{198}},
  year         = {{2025}},
}

@book{62182,
  abstract     = {{<p> Executive summary Die vorliegende Zukunftsstudie „Automation 2035“ gibt einen Ausblick auf die Entwicklung der Automatisierungstechnik in den nächsten 10 Jahren. Neben der Beschreibung von Trends wie Kreislaufwirtschaft, Automatisierung der Märkte, Biologisierung, autonome Systeme und Robotik sowie IT-Sicherheit wird die zu erwartende Veränderung in der Bildung beschrieben. Dazu verwenden wir Methoden der Zukunftsforschung und arbeiten mit der Szenarientechnik, um Zukunftsperspektiven der Automation aufzuzeigen. Personas werden eingesetzt, um die zukünftigen Entwicklungen plastisch aus den Augen der Personen im Jahr 2025 und in der Zukunft im Jahr 2035 zu beschreiben. Schlüsselthemen und Trends: ... ... Inhalt Executive summary 1 1 Einführung 3 2 Zukunftsfelder für die Automatisierungstechnik 2035 4 2.1 Kreislaufwirtschaft 4 2.2 Automatisierung der Märkte 7 2.3 Biologisierung 8 2.4 Autonome Systeme und Robotik 10 2.5 Security 12 2.6 Veränderung der Ausbildung 13 3 Szenario der Automation 2035 16 4 Personas 18 4.1 Unternehmer 18 4.2 Ingenieurin 19 4.3 Schüler 20 5 Thesen und Ausblick 22 Methodik 24 Autorenteam 25 Schrifttum 26... </p>}},
  author       = {{Gräßler, Iris and Özcan, Deniz and Tusek, Alena Marie and Bilgic, Attila and Lange, Christian and Stich, Christian and Maul, Christine and Heizmann, Michael and Weyrich, Michael and Dessel,, Sascha and Miny, Torben and Jumar, Ulrich}},
  isbn         = {{9783911670180}},
  publisher    = {{VDI Verlag}},
  title        = {{{Automation 2035}}},
  doi          = {{10.51202/9783911670180}},
  year         = {{2025}},
}

@inproceedings{62688,
  author       = {{Gräßler, Iris and Pottebaum, Jens and Rarbach, Sven}},
  booktitle    = {{The 11th World Sustainability Forum (WSF11)}},
  location     = {{Barcelona}},
  publisher    = {{MDPI}},
  title        = {{{Potentials of Product Lifecycle Management to Enhance Circular Economy}}},
  doi          = {{10.3390/proceedings2025131047}},
  year         = {{2025}},
}