A certain aluminum alloy housing is one of important components for automobiles, with a large demand. Reasonable die-casting process design can effectively reduce production costs and improve yield rate. In view of problems existing in actual die-casting production of aluminum alloy housing, die-casting process scheme is simulated, analyzed and optimized for flow field and temperature field, and optimized process scheme is used for trial production, aiming to produce high-quality die-castings and provide a reference for die-casting production of such castings.
In view of problems existing in production of aluminum alloy housing die-castings, a casting mold flow analysis software is used to numerically simulate die-casting process of casting, analyze temperature field of casting, predict locations where shrinkage cavities and shrinkage are prone to occur in casting. Two forced water cooling schemes are proposed to optimize temperature field of casting. Temperature fields of two optimization schemes were compared and analyzed by numerical simulation, and optimal die-casting scheme was obtained. Castings produced by optimization scheme were dissected and found to have good internal quality, shrinkage cavities and shrinkage were completely eliminated.
Graphical results
In view of problems existing in die-casting production of aluminum alloy shell parts, actual production casting process scheme was simulated, analyzed and optimized. By analyzing temperature field distribution of casting and predicting locations where shrinkage cavities and shrinkage are prone to occur in casting, forced water cooling was adopted to strengthen local cooling, two optimization schemes were proposed in combination with casting and mold structure. Two optimization schemes were compared and analyzed by means of numerical simulation, and optimal cooling scheme was obtained. By analyzing castings produced by optimal cooling scheme, internal shrinkage cavities and shrinkage were completely eliminated. Trial production showed that scheme can effectively optimize solidification temperature field. Study shows that forced water cooling process has a significant effect on optimization of temperature field of thick and large parts on periphery of casting. Figure 1 is a schematic diagram of an aluminum alloy shell casting and its pouring system. Casting is made of A356 alloy and weighs about 0.632kg. There are multiple cavities inside it, and mold core pulling parts are more complex. Minimum wall thickness of part is 2.6mm, maximum wall thickness reaches 10.6mm, average wall thickness is about 4.0mm, and wall thickness is uneven. By analyzing structure of casting, it is found that maximum wall thickness is located at periphery of casting A.

 

Figure 1 Schematic diagram of aluminum alloy shell casting and pouring system

Table 1 Simulation parameters and boundary conditions

 

Figure 2 Filling flow field of initial scheme

 

Figure 3 Temperature field simulation of casting of initial scheme

 

Figure 4 Sectional temperature field of casting at A of initial scheme

 

Figure 5 Distribution of shrinkage cavities and shrinkage porosity of initial scheme
In order to optimize solidification temperature field of casting, avoid shrinkage cavities and shrinkage porosity defects at A, it is necessary to take a method of accelerating cooling rate locally. Since wall thickness at A is much larger than surrounding wall thickness, optimization scheme proposes to use forced water cooling to speed up cooling speed. After analyzing casting and mold structure, two optimization schemes were designed near part A, as shown in Figure 6. Diameter of cooling water pipe is φ20mm. When simulating optimization scheme, circulating cooling water temperature is set to 30℃, surface heat transfer coefficient between water and mold is set to 5000W/(㎡·K).

 

Figure 6 Cooling water channel optimization temperature field design scheme

 

Figure 7 Section temperature field at A of Scheme 1

 

Figure 8 Section temperature field at A of Scheme 2

 

Figure 9 Prediction results of shrinkage of castings in Scheme 1 and Scheme 2

 

Figure 10 Analysis of casting A of initial scheme and optimization scheme 2