@inproceedings{48632, abstract = {{Digital Servitization is one of the significant trends affecting the manufacturing industry. Companies try to tackle challenges regarding their differentiation and profitability using digital services. One specific type of digital services are smart services, which are digital services built on data from smart products. Introducing these kinds of offerings into the portfolio of manufacturing companies is not trivial. Moreover, they require conscious action to align all relevant capabilities to realize the respective business goals. However, what capabilities are generally relevant for smart services remains opaque. We conducted a systematic literature review to identify them and extended the results through an interview study. Our analysis results in 78 capabilities clustered among 12 principles and six dimensions. These results provide significant support for the smart service transformation of manufacturing companies and for structuring the research field of smart services.}}, author = {{Koldewey, Christian and Fichtler, Timm and Scholtysik, Michel and Biehler, Jan and Schreiner, Nick and Sommer, Franziska and Schacht, Maximilian and Kaufmann, Jonas and Rabe, Martin and Sedlmeier, Joachim and Dumitrescu, Roman}}, keywords = {{Digital Servitization, Transformation, Capabilities, Maturity, Smart Services}}, location = {{Hawaii}}, title = {{{Exploring Capabilities for the Smart Service Transformation in Manufacturing: Insights from Theory and Practice}}}, year = {{2024}}, } @inproceedings{49354, author = {{Afroze, Lameya and Merkelbach, Silke and von Enzberg, Sebastian and Dumitrescu, Roman}}, booktitle = {{ML4CPS 2023}}, location = {{Hamburg}}, title = {{{Domain Knowledge Injection Guidance for Predictive Maintenance}}}, year = {{2024}}, } @inproceedings{49363, author = {{Scholtysik, Michel and Rohde, Malte and Koldewey, Christian and Dumitrescu, Roman}}, title = {{{Circular Product-Service-System Ideation Canvas – A Framework for the Design of circular Product-Service-System Ideas}}}, year = {{2024}}, } @inproceedings{49364, author = {{Scholtysik, Michel and Rohde, Malte and Koldewey, Christian and Dumitrescu, Roman}}, title = {{{Business strategy taxonomy and solution patterns for the circular economy}}}, year = {{2024}}, } @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}}, } @article{47800, abstract = {{The introduction of Systems Engineering is an approach for dealing with the increasing complexity of products and their associated product development. Several introduction strategies are available in the literature; nevertheless, the introduction of Systems Engineering into practice still poses a great challenge to companies. Many companies have already gained experience in the introduction of Systems Engineering. Therefore, as part of the SE4OWL research project, the need to conduct a study including expert interviews and to collect the experiences of experts was identified. A total of 78 hypotheses were identified from 13 expert interviews concerning the lessons learned. Using exclusion criteria, 52 hypotheses were validated in a subsequent quantitative survey with 112 participants. Of these 52 hypotheses, 40 could be confirmed based on the survey results. Only four hypotheses were rejected, and eight could neither be confirmed nor rejected. Through this research, guidance is provided to companies to leverage best practices for the introduction of their own Systems Engineering and to avoid the poor practices of other companies.}}, author = {{Wilke, Daria and Grothe, Robin and Bretz, Lukas and Anacker, Harald and Dumitrescu, Roman}}, issn = {{2079-8954}}, journal = {{Systems}}, keywords = {{Information Systems and Management, Computer Networks and Communications, Modeling and Simulation, Control and Systems Engineering, Software}}, number = {{3}}, publisher = {{MDPI AG}}, title = {{{Lessons Learned from the Introduction of Systems Engineering}}}, doi = {{10.3390/systems11030119}}, volume = {{11}}, year = {{2023}}, } @article{47798, abstract = {{Abstract In diesem Beitrag wird die soziotechnische Gestaltung einer Intelligenten Personaleinsatzplanung beim Unternehmen Miele & Cie. KG im Rahmen des Leuchtturmprojekts „InTime“ im Kompetenzzentrum Arbeitswelt.Plus beschrieben. Hierzu werden die Durchführung und Auswertung einer Interviewreihe sowie das daraus erarbeitete Soll-Konzept vorgestellt.}}, author = {{Gabriel, Stefan and Bentler, Dominik and Bansmann, Michael and Andrew Latos, Benedikt and Kühn, Arno and Dumitrescu, Roman}}, issn = {{2511-0896}}, journal = {{Zeitschrift für wirtschaftlichen Fabrikbetrieb}}, keywords = {{Management Science and Operations Research, Strategy and Management, General Engineering}}, number = {{1-2}}, pages = {{64--68}}, publisher = {{Walter de Gruyter GmbH}}, title = {{{Soziotechnische Gestaltung einer intelligenten Personaleinsatzplanung}}}, doi = {{10.1515/zwf-2023-1009}}, volume = {{118}}, year = {{2023}}, }