Development of a Magnesium Alloy Rotor with a Pin-Point Gate Mold

2010 ◽  
Vol 654-656 ◽  
pp. 1460-1463
Author(s):  
Young Cheol Lee ◽  
Hyung Ho Jo ◽  
In Deok Park

The rotor is a key determinant of the performance of a compressor and many attempts have been made to improve the efficiency of compressors by optimising rotor design. Rotors are usually made of several layers of steel sheets with thin cavities through the steel sheets, and aluminium alloys are used to fill the cavities by high pressure die casting process, and so bind the steel sheets together. Because of their high fluidity and good damping ability, magnesium alloys can be a good alternative for a high efficiency rotor. In this study, magnesium alloys were used for manufacturing rotors by high pressure die casting process using pin-point gate mold. By adopting a pin-point gate system, additional machining was eliminated and casting defects were reduced due to good castability of magnesium alloys.

Author(s):  
M. Imad Khan ◽  
Saeid Nahavandi ◽  
Yakov Frayman

This chapter presents the application of a neural network to the industrial process modeling of high-pressure die casting (HPDC). The large number of inter- and intradependent process parameters makes it difficult to obtain an accurate physical model of the HPDC process that is paramount to understanding the effects of process parameters on casting defects such as porosity. The first stage of the work was to obtain an accurate model of the die-casting process using a feed-forward multilayer perceptron (MLP) from the process condition monitoring data. The second stage of the work was to find out the effect of different process parameters on the level of porosity in castings by performing sensitivity analysis. The results obtained are in agreement with the current knowledge of the effects of different process parameters on porosity defects, demonstrating the ability of the MLP to model the die-casting process accurately.


2019 ◽  
Vol 104 ◽  
pp. 177-188 ◽  
Author(s):  
Dorra Abid ◽  
Ahmed Ktari ◽  
Dhouha Mellouli ◽  
Nedia Gafsi ◽  
Nader Haddar

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