63031 2025 eng 470 485 1 1 conferenceobject Springer Cham 1 -- -- -- The manufacturing of large components is, in comparison to small components, cost intensive. This is due to the sheer size of the components and the limited scalability in number of produced items. To take advantage of the effects of small component production we segment the large components into smaller parts and schedule the production of these parts on regular-sized machine tools. We propose to apply and adapt recent developments in reinforcement learning in combination with heuristics to efficiently solve the resulting segmentation and assignment problem. In particular, we solve the assignment problem up to a factor of 8 faster and only a few percentages less accurate than a classic solver from operations research. Machine Learning and Principles and Practice of Knowledge Discovery in Databases 10.1007/978-3-031-74640-6_38 false <div class="errorPage"> <h2>Anwendungsfehler</h2> <div class="exceptionMessage"> Unable to Connect to ssl://api.crossref.org:443. Error #110: Connection timed out </div> </div> publish European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2023 Turin, Italy 18.09.2023 22.09.2023 05.05.2025 Nathalie Paul Alexander Kister Thorben Schnellhardt Maximilian Fetz Dirk Hecker Tim Wirtz eng uncontrolled Reinforcement Learning eng uncontrolled Assignment Problem eng uncontrolled Large component manufacturing Ingenieurwissenschaften und zugeordnete Tätigkeiten Material Verlagsliteratur Datei im Netzwerk der BAM verfügbar ("Closed Access") Wissenschaftliche Artikel der BAM Additive Fertigung VP Vizepräsident VP.1 eScience