This article introduces the paper “SYSTEM UNDERSTANDING OF HIGH PRESSURE DIE CASTING PROCESS AND DATA WITH MACHINE LEARNING APPLICATIONS”. Overview: Research Background: Research Purpose and Research Questions: Research Methodology Main Research Results: Conclusion and Discussion: Future Follow-up Research: References: List of Abbreviations Copyright:
Jian Yang ab, Bo Liu ab, Yunbo Zeng c, Yiben Zhang ab, Haiyou Huang de, Jichao Hong bShow moreAdd to MendeleyShareCite https://doi.org/10.1016/j.engappai.2024.108514Get rights and content Abstract This research aims to provide a solution to the scarcity and fragmentation of industrial data on die casting aluminum alloys. Quantifying the coupling between die casting process-composition-properties of aluminum alloys through small datasets, is a critical step in predicting part properties and optimizing process selection. To
by Dirk Lehmhus Fraunhofer Institute for Manufacturing Technology and Advanced Materials IFAM, Wiener Straße 12, 28359 Bremen, GermanyMetals 2024, 14(3), 334; https://doi.org/10.3390/met14030334Submission received: 25 February 2024 / Accepted: 8 March 2024 / Published: 14 March 2024(This article belongs to the Special Issue Advances in Metal Casting Technology) 1. Introduction It is a platitude that science and technology do not necessarily evolve along straight paths.
