This introduction paper is based on the paper “Casting Microstructure Inspection Using Computer Vision: Dendrite Spacing in Aluminum Alloys” published by “Metals”. 1. Overview: 2. Abstract: This paper investigates the determination of secondary dendrite arm spacing (SDAS) using convolutional neural networks (CNNs). The aim was to build a Deep Learning (DL) model for SDAS prediction
The content of this introduction paper is based on the article “Performance Enhancement of BLDC Motor for Electric Vehicle Applications” published by “www.isteonline.in”. 1. Overview: 2. Abstract: In today’s technologically advanced society, people are increasingly seeking out more modern, convenient, and environmentally friendly options. One area where this is particularly evident is the transportation industry,
This introductory paper is the research content of the paper [“Predicting Die Cracking in Die-Cast Products Using a Surrogate Model Based on Geometrical Features”] published by [Computer-Aided Design & Applications] 1. Overview: 2. Abstracts or Introduction This paper explores the development and application of a surrogate model for predicting die cracks in die-cast products, focusing
This article introduces the paper ‘INDUSTRY 4.0 FOUNDRY DATA MANAGEMENT AND SUPERVISED MACHINE LEARNING IN LOW-PRESSURE DIE CASTING QUALITY IMPROVEMENT’ published by ‘International Journal of Metalcasting’. 1. Overview: 2. Abstracts or Introduction Low-pressure die casting (LPDC) is essential for producing high-performance aluminum alloy automobile wheel castings, where porosity defects are unacceptable. Maintaining the quality of
This article introduces the paper ‘DESIGNING AN INNOVATIVE MODULAR PLATFORM FOR SPORTS CARS USING THE GENERATIVE DESIGN METHOD’ published by ‘Università di Bologna’. 1. Overview: 2. Abstracts Traditional methods, where chassis components are tailored for each vehicle type, lack flexibility and efficiency. The concept of current modular platforms, allows the reuse of components across different
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.
