Low pressure casting technology and forming process analysis of metal mold based on ProCAST FEA procedure

Panzhong, Lin; Li, Ning

doi:10.1080/15376494.2020.1818013

Cited by 7 publications

(2 citation statements)

References 13 publications

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“…The usage of numerical simulation software like ProCAST ® for the modelling of casting processes has been essential in the development of the casting industry, diminishing drastically the duration required for the design and manufacturing of end products, enhancing the product quality through the examination of multiple manufacturing technology variations in a virtual environment, and results in cost savings related to technology development. ProCAST ® can comprehensively track the entire casting process, including mould filling, alloy cooling and crystallisation, defect formation, residual stress growth, and casting distortion [ 23 , 24 , 25 , 26 ].…”

Section: Introductionmentioning

confidence: 99%

Development of the Low-Pressure Die Casting Process for an Aluminium Alloy Part

Monteiro,

Soares,

Madureira

et al. 2024

Materials

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The low-pressure die casting (LPDC) process was experimentally and numerically studied to produce AlSi7Mg0.3 components such as steering knuckles. Steering knuckles are important safety components in the context of a vehicle’s suspension system, serving as the mechanical interface that facilitates the articulation of the steering to control the front wheel’s orientation, while simultaneously bearing the vertical load imposed by the vehicle’s weight. This work focuses on the development of a numerical model in ProCAST®, replicating the production of the aforementioned part. The model analyses parameters such as the filling dynamics, solidification process, and presence of shrinkage porosities. For the purpose of evaluating the quality of the castings, six parts were produced and characterised, both mechanically (tensile and hardness tests) and microstructurally (porosity and optical microscopy analysis). When correlating simulation results with the available experimental data, it is possible to conclude that the usage of the LPDC process is a viable alternative to the use of steels and other metals for the production of very high-quality castings while using lighter alloys such as aluminium and magnesium in more demanding applications.

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Section: Introductionmentioning

confidence: 99%

Development of the Low-Pressure Die Casting Process for an Aluminium Alloy Part

Monteiro,

Soares,

Madureira

et al. 2024

Materials

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“…This model successfully predicted the pore size distribution and pore number density. To model the low-pressure casting process, Lin et al [ 22 ] employed the ProCAST Visual-Cast 13.5 software to simulate the temperature field of an aluminum alloy. A process design to successfully reduce shrinkage was proposed after a thorough analysis of the changes in the temperature field, velocity field, solid phase rate, and defect location was carried out using the ProCAST software.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization of The Low-Pressure Casting of Large-Size Aluminum Alloy Wheels through a Systematic Optimization Idea

He,

Lu,

et al. 2023

Materials

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The process parameters in the low-pressure casting of large-size aluminum alloy wheels are systematically optimized in this work using numerical casting simulation, response surface methodology (RSM), and genetic algorithm (NSGA-II). A nonlinear input–output relationship was established based on the Box–Behnken experimental design (BBD) for the crucial casting parameters (pouring temperature, mold temperature, holding pressure, holding time), and response indicators (defect volume fraction, spokes large plane mean secondary dendrite spacing (SDAS)), and a mathematical model was developed by regression analysis. The Isight 2017 Design Gateway and NSGA-II algorithm were used to increase the population and look for the best overall solution for the casting parameters. The significance and predictive power of the model were assessed using ANOVA. Casting numerical simulation was used to confirm the best option. To accomplish systematic optimization in its low-pressure casting process, the mold cooling process parameters were adjusted following the local solidification rate. The results showed that the mathematical model was reliable. The optimal solutions were a pouring temperature of 703 °C, mold temperature of 409 °C, holding pressure of 1086 mb, and holding time of 249 s. The mold cooling process was further optimized, and the sequence solidification of the optimal solution was realized under the optimized cooling process. Finally, the wheel hub was manufactured on a trial basis. The X-ray detection, mechanical property analysis, and metallographic observation showed that the wheel hub had no X-ray defects and its mechanical properties were well strengthened. The effectiveness of the system optimization process scheme was verified.

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