Tag Archives: deep learning

Data extension-based analysis and application selection of process-composition-properties of die casting aluminum alloy

Data extension-based analysis and application selection of process-composition-properties of die casting aluminum alloy

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

Read More

Advances in Metal Casting Technology: A Review of State of the Art, Challenges and Trends—Part II: Technologies New and Revived

Advances in Metal Casting Technology: A Review of State of the Art, Challenges and Trends—Part II: Technologies New and Revived

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.

Read More

Figure 7. Images of materials used during the training: The images were split into 200×200 pixel images following the procedure in Figure 5 and used for the prediction task.

Casting Microstructure Inspection Using Computer Vision: Dendrite Spacing in Aluminum Alloys

by Filip Nikolić 1,2,3,Ivan Štajduhar 4,* andMarko Čanađija 1,*1Department of Engineering Mechanics, Faculty of Engineering, University of Rijeka, 51000 Rijeka, Croatia2Research and Development Department, CIMOS d.d. Automotive Industry, 6000 Koper, Slovenia3CAE Department, Elaphe Propulsion Technologies Ltd., 1000 Ljubljana, Slovenia4Department of Computer Engineering, Faculty of Engineering, University of Rijeka, 51000 Rijeka, Croatia*Authors to whom correspondence should be addressed. Abstract This paper

Read More