Part design and the possibilities of production are disrupted by the increased usage of additive manufacturing (AM). Featuring excellent creative freedom due to the layer-by-layer buildup of components, AM leads to profound changes in future part design and enables previously impossible geometries. Laser powder bed fusion (LPBF) technology already allows to manufacture small quantities of parts with high productivity and material efficiency. Due to the specific process characteristics, the resulting surface finish of these parts is insufficient for a wide range of applications, and post-processing is usually unavoidable. Specifically for functional surfaces, this post-processing is often done by machining processes, which can pose challenges for intricate and complex AM parts due to excessive machining forces. In the present paper, the influence and the possibilities of the LPBF process parameters on the subtractive post-processing are shown. A novel weakened structure is developed to selectively reduce the strength of the material and improve the cutting conditions. Chip formation, cutting forces and vibrations during drilling as well as cutting forces during an orthogonal cut are examined. To quantify the differences, a comparison of the machinability between bulk material, standard support structures and the weakened structure is carried out.
Additive manufacturing changes the classical possibilities of production. However, post-processing is usually unavoidable for these components to achieve functional performance. To obtain an optimum product, knowledge of the characteristics of the additive manufactured part and the machining mechanisms depending on these characteristics is required. In this paper, the influence and the interaction of the laser powder bed fusion process parameters on the subtractive post-processing are shown. The effects of the parameters on the geometry of bores are examined and subsequently the precision machinability is analysed using reaming. In addition, a process simulation is carried out to correlate the simulated deformation to the required machining allowance for subsequent reaming. The aim of this investigation is to examine the capabilities of the laser powder bed fusion process to produce bores at angles of 90° (vertical), 60° and 45° that can be machined directly with a reaming tool without the need for drilling.
Der Werkzeugverschleiß und das Zeitspanvolumen bestimmen maßgeblich die Produktionskosten eines zerspanten Bauteils. Entscheidungsunterstützungen für den Werkzeugwechsel, die auf maschinellem Lernen (ML) basieren, bieten großes Potenzial, Werkzeuge effizienter einzusetzen. ML-Modelle sind jedoch meist nicht ohne weiteres auf reale, veränderliche Zerspanprozesse anwendbar. Der Einsatz von Transfer Learning in der Zerspanung adressiert diese Problemstellung, indem Wissen von verwandten, bereits gelernten Aufgaben genutzt wird, um ML-Modelle schneller für neue, aber verwandte Aufgaben trainieren zu können. In diesem Beitrag wird ein Konzept vorgestellt, wie Transfer Learning in der industriellen Praxis für Zerspanprozesse nutzbar gemacht werden kann.
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