conference paper published Stefan Berlik author 2375290009-0007-3242-4501 Mohammad Seidpisheh author 2580370000-0002-2976-9206 MartinManns editor 10th Changeable, Agile, Reconfigurable and Virtual Production Conference (CARV 2025) and the 12th World Mass Customization and Personalization Conference (MCPC 2025) 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. Springer Nature Switzerland2026Siegen eng 2195-4356 2195-4364 978-3-032-16888-710.1007/978-3-032-16889-4_13 131-141 Berlik, Stefan, and Mohammad Seidpisheh. “A Unified Framework for Intelligent Product Configuration Using Knowledge Graphs and Bayesian Networks.” In <i>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</i>, edited by Martin Manns, 131–41. Lecture Notes in Mechanical Engineering. Cham: Springer Nature Switzerland, 2026. <a href="https://doi.org/10.1007/978-3-032-16889-4_13">https://doi.org/10.1007/978-3-032-16889-4_13</a>. Berlik, S., &#38; Seidpisheh, M. (2026). A Unified Framework for Intelligent Product Configuration Using Knowledge Graphs and Bayesian Networks. In M. Manns (Ed.), <i>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</i> (pp. 131–141). Cham: Springer Nature Switzerland. <a href="https://doi.org/10.1007/978-3-032-16889-4_13">https://doi.org/10.1007/978-3-032-16889-4_13</a> S. Berlik, M. Seidpisheh, in: M. Manns (Ed.), 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, Springer Nature Switzerland, Cham, 2026, pp. 131–141. Berlik, Stefan, and Mohammad Seidpisheh. “A Unified Framework for Intelligent Product Configuration Using Knowledge Graphs and Bayesian Networks.” <i>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</i>, edited by Martin Manns, Springer Nature Switzerland, 2026, pp. 131–41, doi:<a href="https://doi.org/10.1007/978-3-032-16889-4_13">10.1007/978-3-032-16889-4_13</a>. S. Berlik and M. Seidpisheh, “A Unified Framework for Intelligent Product Configuration Using Knowledge Graphs and Bayesian Networks,” in <i>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</i>, Siegen, 2026, pp. 131–141. <span style="font-variant:small-caps;">Berlik, Stefan</span> ; <span style="font-variant:small-caps;">Seidpisheh, Mohammad</span>: A Unified Framework for Intelligent Product Configuration Using Knowledge Graphs and Bayesian Networks. In: <span style="font-variant:small-caps;">Manns, M.</span> (Hrsg.): <i>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</i>, <i>Lecture Notes in Mechanical Engineering</i>. Cham : Springer Nature Switzerland, 2026, S. 131–141 Berlik S, Seidpisheh M. A Unified Framework for Intelligent Product Configuration Using Knowledge Graphs and Bayesian Networks. In: Manns M, ed. <i>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</i>. Lecture Notes in Mechanical Engineering. Cham: Springer Nature Switzerland; 2026:131-141. doi:<a href="https://doi.org/10.1007/978-3-032-16889-4_13">10.1007/978-3-032-16889-4_13</a> @inproceedings{Berlik_Seidpisheh_2026, place={Cham}, series={Lecture Notes in Mechanical Engineering}, title={A Unified Framework for Intelligent Product Configuration Using Knowledge Graphs and Bayesian Networks}, DOI={<a href="https://doi.org/10.1007/978-3-032-16889-4_13">10.1007/978-3-032-16889-4_13</a>}, 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}, publisher={Springer Nature Switzerland}, author={Berlik, Stefan and Seidpisheh, Mohammad}, editor={Manns, MartinEditor}, year={2026}, pages={131–141}, collection={Lecture Notes in Mechanical Engineering} } 71442026-09-07T17:05:29Z2026-09-08T08:45:48Z