@article{54565, author = {{Wiederkehr, Ingrid and Schlegel, Michael and Koldewey, Christian and Rapp, Simon and Dumitrescu, Roman and Albers, Albert}}, issn = {{2212-8271}}, journal = {{Procedia CIRP}}, location = {{Kapstadt}}, pages = {{816--821}}, publisher = {{Elsevier BV}}, title = {{{Interacting Forces for a Resilient, Future-robust Evolution of Product Portfolios}}}, doi = {{10.1016/j.procir.2023.09.081}}, volume = {{120}}, year = {{2023}}, } @article{54566, author = {{Göllner, Denis and Dzienus, Sophie and Rasor, Rik and Anacker, Harald and Dumitrescu, Roman}}, issn = {{2212-8271}}, journal = {{Procedia CIRP}}, location = {{Kapstadt}}, pages = {{1433--1438}}, publisher = {{Elsevier BV}}, title = {{{Guidelines for providing digital twins}}}, doi = {{10.1016/j.procir.2023.09.189}}, volume = {{120}}, year = {{2023}}, } @inproceedings{54568, author = {{Machon, Fabian and Haarmann, Lennard and Rabe, Martin and Dumitrescu, Roman and Bierbüsse, Marie and Tack, Mareen and Hanke, Rebecca and Kinder, Daniel}}, booktitle = {{Vorausschau und Technologieplanung}}, editor = {{Dumitrescu, Roman and Hölzle, Katharina}}, isbn = {{978-3-947647-32-3}}, location = {{Berlin}}, title = {{{Mehr Innovationen durch Venture Clienting – Fallstudie zur Initiative „Stratosfare“}}}, volume = {{413}}, year = {{2023}}, } @inproceedings{54569, author = {{Wiederkehr, Ingrid and Koldewey, Christian and Dumitrescu, Roman and Schlegel, Michael and Albers, Albert }}, location = {{Ljubljana}}, title = {{{Bridging the Gap between Product Innovation and Product Planning: A literature-based Conceptual Investigation}}}, year = {{2023}}, } @inproceedings{54571, author = {{Schlegel, Michael and Wiederkehr, Ingrid and Rapp, Simon and Koldewey, Christian and Albers, Albert and Dumitrescu, Roman}}, booktitle = {{Procedia CIRP}}, editor = {{Liu, Ang and Kara, Sami}}, issn = {{2212-8271}}, location = {{Sydney}}, pages = {{764--769}}, publisher = {{Elsevier BV}}, title = {{{Ontology for Future-robust Product Portfolio Evolution: A Basis for the Development of Models and Methods}}}, doi = {{10.1016/j.procir.2023.01.017}}, volume = {{119}}, year = {{2023}}, } @inproceedings{54574, author = {{Weller, Julian and Nico Migenda, Nico Migenda and Rui Liu, Rui Liu and Arthur Wegel, Arthur Wegel and Martin Kohlhase, Martin Kohlhase and Wolfram Schenck, Wolfram Schenck and Sebastian von Enzberg, Sebastian von Enzberg and Dumitrescu, Roman}}, location = {{Hamburg}}, title = {{{Towards a systematic approach for Prescriptive Analytics use cases in smart factories}}}, year = {{2023}}, } @inproceedings{54618, author = {{Wilke, Daria and Grewe, Carolin and Thavathilakarjah, Dhusjanth and Anacker, Harald and Dumitrescu, Roman}}, location = {{Kapstadt}}, title = {{{Method Engineering – a Systematic Literature Review on Scopus Base}}}, year = {{2023}}, } @inproceedings{54620, author = {{Seidenberg, Tobias and Ayoub, Joe and Figge, Mike and Anacker, Harald and Dumitrescu, Roman}}, location = {{Bangkok}}, title = {{{Method to support the selection of localization technologies for Industry 4.0}}}, year = {{2023}}, } @inproceedings{54621, author = {{Schreiner, Nick and Kürpick, Christian and Kühn, Arno and Dumitrescu, Roman}}, location = {{Buenos Aires}}, title = {{{Sustainability Data Map: Framework for Data-Based Product Carbon Footprinting of Technical Products}}}, year = {{2023}}, } @misc{54622, author = {{Gabriel, Stefan and Fechtelpeter,, Christian and Wulf, Jessica and Leßmann, Salome and Dumitrescu, Roman}}, title = {{{Transferkonzept eines Kompetenzzentrums der Arbeitsforschung in einer von mittelständischen Unternehmen geprägten Region}}}, year = {{2023}}, } @inproceedings{37553, author = {{Schrader, Elena and Bernijazov, Ruslan and Foullois, Marc and Hillebrand, Michael and Kaiser, Lydia and Dumitrescu, Roman}}, booktitle = {{2022 IEEE International Symposium on Systems Engineering (ISSE)}}, publisher = {{IEEE}}, title = {{{Examples of AI-based Assistance Systems in context of Model-Based Systems Engineering}}}, doi = {{10.1109/isse54508.2022.10005487}}, year = {{2023}}, } @inproceedings{45793, abstract = {{The global megatrends of digitization and sustainability lead to new challenges for the design and management of technical products in industrial companies. Product management - as the bridge between market and company - has the task to absorb and combine the manifold requirements and make the right product-related decisions. In the process, product management is confronted with heterogeneous information, rapidly changing portfolio components, as well as increasing product, and organizational complexity. Combining and utilizing data from different sources, e.g., product usage data and social media data leads to promising potentials to improve the quality of product-related decisions. In this paper, we reinforce the need for data-driven product management as an interdisciplinary field of action. The state of data-driven product management in practice was analyzed by conducting workshops with six manufacturing companies and hosting a focus group meeting with experts from different industries. We investigate the expectations and derive requirements leading us to open research questions, a vision for data-driven product management, and a research agenda to shape future research efforts.}}, author = {{Grigoryan, Khoren and Fichtler, Timm and Schreiner, Nick and Rabe, Martin and Panzner, Melina and Kühn, Arno and Dumitrescu, Roman and Koldewey, Christian}}, booktitle = {{Procedia CIRP 33}}, keywords = {{Product Management, Data Analytics, Data-Driven Design, Product-related data, Lifecycle Data, Tool-support}}, location = {{Sydney}}, title = {{{Data-Driven Product Management: A Practitioner-Driven Research Agenda}}}, year = {{2023}}, } @inproceedings{45812, author = {{Özcan, Leon and Fichtler, Timm and Kasten, Benjamin and Koldewey, Christian and Dumitrescu, Roman}}, keywords = {{Digital Platform, Platform Strategy, Strategic Management, Platform Life Cycle, Interview Study, Business Model, Business-to-Business, Two-sided Market, Multi-sided Market}}, location = {{Ljubljana}}, title = {{{Interview Study on Strategy Options for Platform Operation in B2B Markets}}}, year = {{2023}}, } @article{47420, author = {{Kürpick, Christian and Rasor, Anja and Scholtysik, Michel and Kühn, Arno and Koldewey, Christian and Dumitrescu, Roman}}, issn = {{2212-8271}}, journal = {{Procedia CIRP}}, keywords = {{General Medicine}}, pages = {{614--619}}, publisher = {{Elsevier BV}}, title = {{{An Integrative View of the Transformations towards Sustainability and Digitalization: The Case for a Dual Transformation}}}, doi = {{10.1016/j.procir.2023.02.155}}, volume = {{119}}, year = {{2023}}, } @book{48666, abstract = {{Unter dem Einfluss der Digitalisierung wandeln sich mechatronische Produkte zunehmend in cyber-physische Systeme (CPS). Diese sind in der Lage, umfangreiche Daten während ihres Betriebs zu sammeln und über digitale Netzinfrastrukturen zur Verfügung zu stellen. Gemeinsam mit weiteren Daten aus der Betriebsphase versprechen sie wertvolle Erkenntnisse über das Produkt und dessen Nutzer, welche für die Hersteller der CPS insbesondere für die Planung zukünftiger Produktgenerationenrelevant sind. Die zielgerichtete Nutzung von Betriebsdaten in der strategischen Produktplanung stellt produzierende Unternehmen jedoch noch vor zahlreiche Herausforderungen, z. B. hinsichtlich der Identifizierung Erfolg versprechender Use Cases. Das vorliegende Buch greift diese Herausforderungen auf und stellt ein Instrumentarium vor, das produzierende Unternehmen zur datengestützten Produktplanung befähigt. Neben der Vorstellung praxiserprobter Methoden und Werkzeuge werden Einblicke in vier Pilotprojekte gegeben. Das Instrumentarium entstand im Forschungsprojekt „DizRuPt“, das vom Bundesministerium für Bildung und Forschung (BMBF) gefördert wurde.}}, editor = {{Dumitrescu, Roman and Koldewey, Christian}}, publisher = {{Heinz Nixdorf Institut}}, title = {{{Datengestützte Produktplanung}}}, doi = {{10.17619/UNIPB/1-1667}}, volume = {{408}}, year = {{2023}}, } @inproceedings{64265, author = {{Rohde, Jannik and Meyer, Olga and Duc, Quy Luu and Jürgenhake, Christoph and Sankal, Talib and Dumitrescu, Roman and Schmitt, Robert H.}}, booktitle = {{2022 Sixth IEEE International Conference on Robotic Computing (IRC)}}, publisher = {{IEEE}}, title = {{{Teleoperation of an Industrial Robot using Public Networks and 5G SA Campus Networks}}}, doi = {{10.1109/irc55401.2022.00012}}, year = {{2023}}, } @inproceedings{64261, author = {{Kurpick, Christian and Dumitrescu, Roman and Falkowski, Tommy and Fechtelpeter, Christian and Kühn, Arno}}, booktitle = {{2022 IEEE 28th International Conference on Engineering, Technology and Innovation (ICE/ITMC) & 31st International Association For Management of Technology (IAMOT) Joint Conference}}, publisher = {{IEEE}}, title = {{{Digitalization and Sustainability in Strategic Management: Research Agenda toward Dual Transformation}}}, doi = {{10.1109/ice/itmc-iamot55089.2022.10033146}}, year = {{2023}}, } @inproceedings{49318, author = {{Tissen, Denis and Koldewey, Christian and Dumitrescu, Roman}}, location = {{Ljubljana, Slovenia}}, title = {{{A process-model for tailoring prototyping of cyber-physical systems}}}, year = {{2023}}, } @inproceedings{29149, author = {{Koldewey, Christian and Dumitrescu, Roman and Rabe, Martin }}, booktitle = {{Proceedings of the 55th Hawaii International Conference on System Sciences}}, location = {{Hawaii, USA}}, title = {{{Introduction to the Data-driven Services in Manufacturing Minitrack - Exploring Management, Engineering, and Organizational Transformation}}}, year = {{2022}}, } @inproceedings{29380, abstract = {{Cyber-physical systems generate and collect huge amounts of usage data during operation. Analyzing these data may enable manufacturing companies to identify weaknesses and learn about the users of their products. Such insights are valuable in the early phases of product development like product planning, as they facilitate decision-making for product improvement. The analysis and exploitation of usage data in product planning, however, is a new task for manufacturing companies. To reduce mistakes and improve the results, companies should build upon a suitable reference process model. Unfortunately, established models for analyzing data cannot be easily applied for product planning. In this paper, we propose a reference process model for usage data-driven product planning. It builds on three well-established models for analyzing data and addresses the unique characteristics of usage data-driven product planning. Finally, we customize the model for a manufacturing company and demonstrate how it could be implemented in practice.}}, author = {{Meyer, Maurice and Wiederkehr, Ingrid and Panzner, Melina and Koldewey, Christian and Dumitrescu, Roman}}, booktitle = {{Proceedings of the 55th Hawaii International Conference on System Sciences}}, pages = {{6105--6114}}, title = {{{A Reference Process Model for Usage Data-Driven Product Planning}}}, year = {{2022}}, }