Predicting the solidification time of low pressure die castings using geometric feature-based machine learning metamodels

Title data

Rosnitschek, Tobias ; Erber, Maximilian ; Alber-Laukant, Bettina ; Hartmann, Christoph ; Volk, Wolfram ; Rieg, Frank ; Tremmel, Stephan:
Predicting the solidification time of low pressure die castings using geometric feature-based machine learning metamodels.
In: Procedia CIRP. Vol. 118 (2023) . - pp. 1102-1107.
ISSN 2212-8271
DOI: https://doi.org/10.1016/j.procir.2023.06.189

Official URL:

Abstract in another language

Casting process simulations are commonly used to predict and avoid defect formation. Their integration into structural optimization can enable automated structure- and process-optimized castings. Nevertheless, these simulations are time-consuming and computationally expensive. Therefore, this paper used graph theory and skeletonization techniques to extract geometric features from arbitrary 3D geometries and transferred them to machine learning-metamodels. This method can replace casting process simulation for the prediction of directional solidification in low-pressure die casting. Automated machine learning and hyperparameter optimization were used to systemize the search for well-suited neural network architectures. Two examples were used to train the metamodels, which are subsequently evaluated by a further test example, unknown to the training data and compared to the simulation results. The results showed an accuracy on unknown geometries over 60 and thus emphasized that neural network metamodels are capable of replacing time-consuming casting process simulation for specific objectives.

Further data

Item Type:	Article in a journal
Refereed:	Yes
Keywords:	Directed solidification; casting design; machine learning; process assurance; virtual product development
Institutions of the University:	Faculties > Faculty of Engineering Science > Former Professors > Chair Engineering Design and CAD - Univ.-Prof. Dr.-Ing. Frank Rieg Faculties > Faculty of Engineering Science > Chair Engineering Design and CAD > Chair Engineering Design and CAD - Univ.-Prof. Dr.-Ing Stephan Tremmel
Result of work at the UBT:	Yes
DDC Subjects:	600 Technology, medicine, applied sciences > 620 Engineering
Date Deposited:	19 Jul 2023 06:23
Last Modified:	19 Jul 2023 06:23
URI:	https://eref.uni-bayreuth.de/id/eprint/86175