Tag Archives: Aluminum Casting

Figure 1. Aluminum in the automotive industry, model Audi A2

Application of Aluminum and ITS Alloys in the Automotive Industry With Special Emphasis PN Wheel Rims

The Rise of Automotive Aluminum Casting: A Technical Review of Lightweighting Trends and Wheel Rim Innovations This technical summary is based on the academic paper “Application of Aluminum and ITS Alloys in the Automotive Industry With Special Emphasis PN Wheel Rims” by Dragan Adamović, Tomislav Vujinović, Fatima Živić, Jelena Živković, and Marko Topalović, published in

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Fig. 5. Microstructure of AlSi7Mg0.3 whith 0.2% Zr, with HT cast into metal mold, etchant 0.5% HF.

Heat Treatment of AlSi7Mg0.3 Aluminium Alloys with Increased Zirconium and Titanium Content

Unlocking Superior Strength: A Deep Dive into AlSi7Mg0.3 Heat Treatment with Zr and Ti Additives This technical summary is based on the academic paper “Heat Treatment of AlSi7Mg0.3 Aluminium Alloys with Increased Zirconium and Titanium Content” by E. Kantoríková, M. Kuriš, R. Pastirčák, published in ARCHIVES of FOUNDRY ENGINEERING (2021). Keywords Executive Summary The Challenge:

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Fig.1 - Schematic representation of samples drawn from the two different spokes. For confidentiality reasons, the real wheel cannot be shown so a schematic representation is given.

Development of a model for the prediction of mechanical properties for Al-Si-Mg castings

From Simulation to Reality: A Validated Model for Predicting Mechanical Properties in A356 Aluminum Castings This technical summary is based on the academic paper “Development of a model for the prediction of mechanical properties for Al-Si-Mg castings” by C. Ransenigo, M. Tocci, C. Viscardi, M. Serafini, A. Pola, published in La Metallurgia Italiana (2022). Keywords

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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 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. 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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Figure 10: Simulation compared with real casting of cracks

Apply simulation application optimize production process for car industry

Optimize Automotive Die Casting: A Guide to Simulation for Defect Reduction and Efficiency This technical summary is based on the academic paper “Apply simulation application optimize production process for car industry” by Phan Van Tong. Keywords Executive Summary The Challenge: Why This Research Matters for HPDC Professionals In the competitive automotive industry, mass-producing parts from

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Fig. 4. EDX analysis of large iron particle

Influence of Nickel Addition on Properties of Secondary AlSi7Mg0.3 Alloy

Unlocking the Potential of Secondary Aluminum Alloys: How Nickel Addition Mitigates Iron Impurities This technical summary is based on the academic paper “Influence of Nickel Addition on Properties of Secondary AlSi7Mg0.3 Alloy” by L. Richtárech, D. Bolibruchová, M. Brůna, and J.Caiss, published in ARCHIVES of FOUNDRY ENGINEERING (2015). Keywords Executive Summary The Challenge: Why This

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Table 1. The refractory coating for evaporable pattern

APPLICATION OF LOST FOAM CASTING PROCESS FOR MANUFACTURING PARTS IN AUTOMOTIVE INDUSTRY

Optimizing the Lost Foam Casting Process: A Deep Dive into Refractory Coatings and Process Parameters for Automotive Parts This technical summary is based on the academic paper “APPLICATION OF LOST FOAM CASTING PROCESS FOR MANUFACTURING PARTS IN AUTOMOTIVE INDUSTRY” by Marko Pavlović, Tatjana Volkov-Husović, Muhamed Sarvan, Milan Đuričić, Fuad Klisura, and Zagorka Acimović, published in

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Figure 1. Effects of aging temperature on the Vickers hardness curves of die cast Al–Si–Cu–Mg alloy

AGING METALLURGY AND MECHANICAL PRPERTIES ON Al-Si-Cu-Mg DIE CASTING ALLOY

Unlocking Peak Hardness in ADC12 Alloys: A Two-Step Aging Strategy for HPDC This technical summary is based on the academic paper “AGING METALLURGY AND MECHANICAL PRPERTIES ON Al-Si-Cu-Mg DIE CASTING ALLOY” by T. Ando et al., published in the Proceedings of the 16th International Aluminum Alloys Conference (ICAA16) (2018). It has been analyzed and summarized

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