@inproceedings{7144,
  abstract     = {The increasing complexity of product configurations demands intelligent systems that effectively integrate customer requirements, dependencies, and uncertainties. This paper introduces a unified framework combining Knowledge Graphs (KGs) and Bayesian Networks (BNs) to enhance the efficiency and adaptability of product configuration processes. KGs provide a semantic foundation for product information, ensuring interoperability and explicit relationship modeling. BNs enhance this through probabilistic reasoning, allowing the system to manage uncertainties and dynamically generate optimal configurations. The integration of deterministic, rule-based reasoning from ontologies with the probabilistic nature of BNs automates suggestions, predicts user preferences, and reduces complexity. This framework streamlines user interactions through intelligent form pre-filling and contextually relevant suggestions, even under uncertainty. By employing an ontology-based representation of BNs, the components fit seamlessly into the KG, creating a cohesive and unified framework that balances scalability and user-centric design to address modern configuration challenges.                },
  author       = {Berlik, Stefan and Seidpisheh, Mohammad},
  booktitle    = {New Paradigms for Anticipated Uncertainty. Proceedings of the 10th Changeable, Agile, Reconfigurable and Virtual Production Conference (CARV 2025) and the 12th World Mass Customization and Personalization Conference (MCPC 2025), Siegen, Germany, September 2025},
  editor       = {Manns, Martin},
  isbn         = {978-3-032-16888-7},
  issn         = {2195-4364},
  location     = {Siegen},
  pages        = {131--141},
  publisher    = {Springer Nature Switzerland},
  title        = {{A Unified Framework for Intelligent Product Configuration Using Knowledge Graphs and Bayesian Networks}},
  doi          = {10.1007/978-3-032-16889-4_13},
  year         = {2026},
}

@inbook{2727,
  author       = {Lück, Sönke and Naumann, Rolf},
  booktitle    = {Advances in Dynamics of Vehicles on Roads and Tracks. Proceedings of the 26th Symposium of the International Association of Vehicle System Dynamics, IAVSD 2019, August 12-16, 2019, Gothenburg, Sweden},
  editor       = {Klomp, Matthijs and Bruzelius, Fredrik and Nielsen, Jens and Hillemyr, Angela},
  isbn         = {978-3-030-38076-2},
  issn         = {2195-4364},
  keywords     = {Multibody Simulation, Railway Accident, Complex System Simulation, Vehicle Dynamics, Braking},
  location     = {Göteborg},
  pages        = {292--302},
  publisher    = {Springer International Publishing},
  title        = {{Scenario Substructure Method (SSM) for Simulation of Long Trains}},
  doi          = {10.1007/978-3-030-38077-9_35},
  year         = {2020},
}