Effects of Casting Conditions for Reduced Pressure Test on Melt Quality of Al-Si Alloy

Jang, Ho Sung; Kang, Ho Jung; Park, Jin Young; Choi, Yoon Suk; Shin, Sang‐Wook

doi:10.3390/met10111422

Cited by 5 publications

(2 citation statements)

References 16 publications

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“…Jang et al found that increasing the mold pre-heating temperature increased the DI of an aluminum alloy up to a point after which further temperature increases decreased the DI. 50 In this study, the DI is included as monitored variables.…”

Section: Causes Of Porosity Defects In Lpdcmentioning

confidence: 99%

Industry 4.0 Foundry Data Management and Supervised Machine Learning in Low-Pressure Die Casting Quality Improvement

et al. 2022

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Low-pressure die cast (LPDC) is widely used in high performance, precision aluminum alloy automobile wheel castings, where defects such as porosity voids are not permitted. The quality of LPDC parts is highly influenced by the casting process conditions. A need exists to optimize the process variables to improve the part quality against difficult defects such as gas and shrinkage porosity. To do this, process variable measurements need to be studied against occurrence rates of defects. In this paper, industry 4.0 cloud-based systems are used to extract data. With these data, supervised machine learning classification models are proposed to identify conditions that predict defectives in a real foundry Aluminum LPDC process. The root cause analysis is difficult, because the rate of defectives in this process occurred in small percentages and against many potential process measurement variables. A model based on the XGBoost classification algorithm was used to map the complex relationship between process conditions and the creation of defective wheel rims. Data were collected from a particular LPDC machine and die mold over three shifts and six continuous days. Porosity defect occurrence rates could be predicted using 36 features from 13 process variables collected from a considerably small sample (1077 wheels) which was highly skewed (62 defectives) with 87% accuracy for good parts and 74% accuracy for parts with porosity defects. This work was helpful in assisting process parameter tuning on new product pre-series production to lower defectives.

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Section: Causes Of Porosity Defects In Lpdcmentioning

confidence: 99%

Industry 4.0 Foundry Data Management and Supervised Machine Learning in Low-Pressure Die Casting Quality Improvement

et al. 2022

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“…The addition of Si in commercial Al-Si-Mg alloys, such as Silafont™, Castasil™, Aural™, and Mercalloy™, induced a hypoeutectic or near-eutectic composition that ranges from 6.0 to 12 wt.%. Moreover, it is essential to ensure that the concentration of Mg does not exceed 0.7 wt.% because it is likely to significantly damage the mechanical properties of the alloy through the formation of brittle intermetallic phases that contain trace elements, such as Fe, Ni, and Cu [7][8][9]. Furthermore, the addition of Sr (0.01-0.02 wt.%) modifies the eutectic Si, thereby improving the ductility of the alloy.…”

Section: Introductionmentioning

confidence: 99%

Influence of the Solution and Artificial Aging Treatments on the Microstructure and Mechanical Properties of Die-Cast Al–Si–Mg Alloys

Kang

Park

Choi

et al. 2021

Metals

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Heat treatment is widely used to improve the properties of Al–Si–Mg alloys and its outcomes are influenced by the parameters applied during the treatment. This study describes the effect of the solution and artificial aging treatments on the microstructure and mechanical properties of die-cast Al–Si–Mg alloys. The microstructure of the as-cast Al–Si–Mg alloy was mainly composed of α-Al, complex needle-type eutectic Si particles, Mg2Si, and α-AlFeMn. The complex needle-type eutectic Si particles disintegrated into spheroidal morphologies, while the Mg2Si was dissolved due to the solid solution treatment. The maximum yield strength (YS) and ultimate tensile strength (UTS) values were 126.06 and 245.90 MPa at 520 °C after 90 min of solution heat treatment, respectively. Although the YS and UTS values of the Al–Si–Mg alloys reduced due to the solution treatment, the elongation (EL) of the solid solution heat-treated Al–Si–Mg alloys was improved in comparison to that of the as-cast Al–Si–Mg alloy. The maximum YS and UTS of 239.50 and 290.93 MPa were obtained after performing artificial aging at 180 °C for 180 min, respectively. However, the EL of the aging heat-treated alloy was reduced by a minimal value.

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Particularities of the Formation and Modification of Si and Mg2si as Second Phases in Casting Al Alloys: Use of Shape Descriptors and Fractal Dimension

Soto

González

Aguilar

et al. 2022

Trans Indian Inst Met

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Effects of Casting Conditions for Reduced Pressure Test on Melt Quality of Al-Si Alloy

Cited by 5 publications

References 16 publications

Industry 4.0 Foundry Data Management and Supervised Machine Learning in Low-Pressure Die Casting Quality Improvement

Industry 4.0 Foundry Data Management and Supervised Machine Learning in Low-Pressure Die Casting Quality Improvement

Influence of the Solution and Artificial Aging Treatments on the Microstructure and Mechanical Properties of Die-Cast Al–Si–Mg Alloys

Particularities of the Formation and Modification of Si and Mg2si as Second Phases in Casting Al Alloys: Use of Shape Descriptors and Fractal Dimension

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