Effects of Mold Materials on the Interfacial Reaction between Magnesium Alloy and Ceramic Shell Mold during Investment Casting

Y.Hao,; Liu, Jinxue; Du, Jiang; Zhang, Wenjie; Xiao, Yang; Zhang, Shaojun; Yang, Peixu

doi:10.3390/met10080991

Cited by 3 publications

(4 citation statements)

References 32 publications

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“…were used as a face-coats in place of conventional face-coat ZrSiO4 where, some oxides were observed effective to suppress the mold-metal reactions. However, the results were not in agreement with the theoretical stability of face-coats in some cases [17][18][19][20].…”

Section: Fig 4 Ellingham Diagram [16]mentioning

confidence: 64%

Archives of Foundry Engineering

Vyas,

Sutaria

2022

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In the manufacturing sector, the processing of magnesium alloys through the liquid casting route is one of the promising methods to manufacture automotive and aircraft components, for their excellent mechanical properties at the lower weight. Investment casting process has the great cabaility to produce near net shape complex castings for automotive and aircraft applications. The distinct and attractive engineering properties of magnesium alloys have shown to be promising in terms of its potential to replace materials such as cast iron, steel, and aluminum In this regard, the efforts to develop processing technology for these alloys for their wide range of applications in industries have been reported by the scientific and engineering community. For successful production of magnesium alloy castings, it requires specialized foundry techniques because of the particular chemical and physical properties of magnesium; especially the reactive and oxidative nature of these alloys. The industry is young enough, to tap the potential.

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Section: Fig 4 Ellingham Diagram [16]mentioning

confidence: 64%

Archives of Foundry Engineering

Vyas,

Sutaria

2022

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“…They can also initiate forming by other defects or intermetallics (Dezecot & Brochu, 2015). • Chemical reactions that might appear due to refractories used during the forming of the shell mold (Hao et al, 2020). They can be a result of the interaction of the metal used in investment casting and the ceramic mold where the metal is poured.…”

Section: Introductionmentioning

confidence: 99%

Design of Machine Learning method for decision-making support and reliability improvement in the investment casting process

Antoniadou,

Kyprianidis,

Aslanidou

et al. 2023

Linköping Electronic Conference Proceedings

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The need to improve reliability and support decision-making in manufacturing has drawn attention to the application of diagnostic and decision-support tools. Particularly in the investment casting industry, data-driven methods can be the enabler for process diagnostics and decision support. Images from the microscopic examination in the investment casting process are used as data input, to detect defects in produced pieces. The microscopic examination usually relies solely upon the ability of the operator to determine whether an image from the microscope contains a defect. Therefore, an effective strategy for this decision-making process is crucial to improve the reliability of the examination. The use of the machine learning classifier Random Forest is introduced to derive predictions on the existence of a defect in the input image. This work focuses on employing machine learning tools for image recognition and the developed approach constitutes a decision support model to assist the operator and improve the reliability of their assessment.

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“…Unitl now, several studies have been conducted to restrict the unsuitable metal-moulds reactions by changing the casting parameters [3-5,7,8] and using different shell materials and inhibitors [6,9-13]. Silica, alumina, and zircon-based moulds illustrated effective reaction behaviour, due to having high-temperature melting points and free energy [3,5,8-11,14]. Moreover, utilising inhibitors such as silica-free binders, KBF 4 , and NaBF 4 could enhance the reaction resistance of metal–mould [6,13,14].…”

Section: Introductionmentioning

confidence: 99%

“…Unitl now, several studies have been conducted to restrict the unsuitable metal-moulds reactions by changing the casting parameters [3][4][5]7,8] and using different shell materials and inhibitors [6,[9][10][11][12][13]. Silica, alumina, and zircon-based moulds illustrated effective reaction behaviour, due to having high-temperature melting points and free energy [3,5,[8][9][10][11]14]. Moreover, utilising inhibitors such as silica-free binders, KBF 4 , and NaBF 4 could enhance the reaction resistance of metal-mould [6,13,14].…”

Section: Introductionmentioning

confidence: 99%

Complex reaction behaviour of ceramic mould with the molten AZ91 alloy during investment casting

Zarandi

Malekan

Lotfpour

et al. 2021

Materials Science and Technology

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The effects of different pouring temperatures on the reaction behaviour of the ceramic shell with the molten Mg-9%Al-1%Zn-0.4%Mn (all are in wt-%) (AZ91) alloy during investment casting were studied. The scanning electron microscopy (SEM) micrographs with energy dispersive spectroscopy (EDS) analysis illustrated a complex interaction behaviour of the alloy with the mould components at various pouring temperatures. The MgO + MgAl2O4 compounds were formed on the surface of investment cast alloy at the pouring temperature of 600°C. With increasing the temperature to 650°C, the MgO compounds with the Al2O3 particles were observed at the interface of metal/mould. The Al2O3 particles were the main compound on the surface of alloy at the pouring temperature of 700°C. The formation of Al2O3 particles instead of the MgO compounds on the surface was related to the increase of magnesium evaporation by enhancement of the pouring temperature and also diffusion of Al2O3 particles from the ceramic shell to the surface of the alloy.

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Effects of Mold Materials on the Interfacial Reaction between Magnesium Alloy and Ceramic Shell Mold during Investment Casting

Cited by 3 publications

References 32 publications

Archives of Foundry Engineering

Archives of Foundry Engineering

Design of Machine Learning method for decision-making support and reliability improvement in the investment casting process

Complex reaction behaviour of ceramic mould with the molten AZ91 alloy during investment casting

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