Category Archives: Aluminium-E

Figure 15: Casting process of liquefied gray cast iron alloy in an electric arc furnace.

Development of Technology for Obtaining Thin-Walled Details from Gray Cast Iron in Sand-Clay Moulds

Unlocking New Potential in Thin-Walled Gray Cast Iron Casting: A Proven Method to Boost Fluidity and Extend Service Life by 30% This technical summary is based on the academic paper “Development of Technology for Obtaining Thin-Walled Details from Gray Cast Iron in Sand-Clay Moulds” by Jamshidbek Khasanov et al., published in the International Journal of

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Fig. 3. Scheme of stand to continuous casting of grey cast iron ingots with circular section

Eliminating Hard Spots in Grey Cast Iron: A Breakthrough in Continuous Casting with Electromagnetic Stirring

This technical summary is based on the academic paper “Influence of continuous casting conditions on grey cast iron structure” by J. Szajnar, M. Stawarz, T. Wróbel, W. Sebzda, B. Grzesik, M. Stępień, published in Archives of Materials Science and Engineering (2010). Keywords Executive Summary The Challenge: Why This Research Matters for HPDC Professionals In high-volume

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Figure 1 Experimental schematic diagram of aluminumalloymelt quality analysis

Enhanced Melt Quality Rapid Analysis of Aluminum Alloy Assisted by Machine Learning

Revolutionizing Aluminum Casting: How Machine Learning Delivers Rapid, Accurate Melt Quality Analysis This technical summary is based on the academic paper “Enhanced Melt Quality Rapid Analysis of Aluminum Alloy Assisted by Machine Learning” by Yunxiang Tan, Juhuai Ma, Haifeng Liu, Jianlei Jia, Liguo Yang, and Qingyan Xu, presented at The 75th World Foundry Congress (2024).

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Figure 6 Surface temperature of sprue core.

High Thermal Conductivity Steel and its Application to Die Casting Tools

How High Thermal Conductivity Steel Revolutionizes Die Casting Molds for Faster Cycles and Higher Quality This technical summary is based on the academic paper “High Thermal Conductivity Steel and its Application to Die Casting Tools” by K. Namiki, Masamichi. Kawano, and Thomas Schade, published in NADCA DIE CASTING CONGRESS & EXPOSITION (2012). It has been

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RECENT GROWING DEMAND FOR MAGNESIUM IN THE AUTOMOTIVE INDUSTRY

Recent Growing Demand for Magnesium in the Automotive Industry

Magnesium Die Casting: Meeting Automotive’s Growing Demand for Lighter, More Efficient Components This technical summary is based on the academic paper “Recent Growing Demand for Magnesium in the Automotive Industry” by María Josefa Freiría Gándara, published in Materiali in tehnologije / Materials and technology (2011). It has been analyzed and summarized for technical experts by

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Figure 5a. Locations (A and B) for the micrographs in Figure 5b

Optimizing the Magnesium Die Casting Process to Achieve Reliability in Automotive Applications

This introduction paper is based on the paper “Optimizing the Magnesium Die Casting Process to Achieve Reliability in Automotive Applications” published by “SAE International”. 1. Overview: 2. Abstract: High pressure die casting is characterized by rapid die filling and subsequent rapid cooling of the molten metal in the die. These characteristics are favourable for magnesium

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Figure 1.0: Aluminum cast centrifugal pump casing. Figure 1.1: Aluminum casting process.

Theoretical Analysis of Liquid Aluminum Flow in Aluminum Casting Processes

Beyond Trial and Error: A New Model for Aluminum Casting Process Optimization This technical summary is based on the academic paper “Theoretical Analysis of Liquid Aluminum Flow in Aluminum Casting Processes” by Taiwo Alare and Feranmi J Adeloye, published in PriMera Scientific Engineering (2023). Keywords Executive Summary The Challenge: Why This Research Matters for HPDC

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Fig.1: An SEM image of an air-pore (A, right), associated with a region of micro-shrinkage porosity (A, left), alongside with a higher magnification view of the air-pore (B), showing the location that the EDX spectrum (C) was sampled from

Towards Location Specific Statistical Fracture Prediction in High Pressure Die Castings

Predicting Failure Before It Happens: A Breakthrough in Statistical Fracture Prediction for HPDC This technical summary is based on the academic paper “Towards Location Specific Statistical Fracture Prediction in High Pressure Die Castings” by R. Watson, W.D. Griffiths, T. Zeguer, and S. Ruffle, published in the proceedings of the 10th European LS-DYNA Conference (2015). Keywords

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Fig. 1: A challenging task: simulating the casting process to predict component properties. The biggest benefit of the casting process is its ability to perform many tasks at the same time. However, it is also its biggest drawback, as many process parameters are linked to each other and have to be considered simultaneously.

Cast iron – a predictable material

From Art to Science: How Advanced Cast Iron Simulation Delivers Predictable Performance and Quality This technical summary is based on the academic paper “Cast iron – a predictable material” by Jörg C. Sturm and Guido Busch, published in The 69th WFC Paper (2011). Keywords Executive Summary The Challenge: Why This Research Matters for HPDC Professionals

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Fig. 1. a) cross section of a slab with solidification cracks, b) Reflection configuration: Excitation laser and detection laser are arranged at the same spot. Ultrasonic waves are induced in the sample by an pulsed excitation laser (red), propagate through the sample and get reflected or scattered by interfaces (cracks, blowholes,…). The detection of reflected and scattered ultrasonic waves is realized with a two wave beam mixing interferometer (green). c) Transmission configuration: Excitation laser (red) and detection laser (green) are arranged at the opposite side of the sample.

Detection of Casting Defects in Aluminum Slabs by Laser Ultrasonic Measurements

Real-Time Defect Detection: How Laser Ultrasonic Testing Is Revolutionizing Aluminum Casting Quality Control This technical summary is based on the academic paper “Detection of Casting Defects in Aluminum Slabs by Laser Ultrasonic Measurements” by Jürgen ROITHER et al., published in the proceedings of the 19th World Conference on Non-Destructive Testing (2016). It has been analyzed

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