Optimization of Process Parameters during Pressure Die Casting of A380: a Silicon-Based Aluminium Alloy Using GA & Fuzzy Methodology

Silicon ◽  
2020 ◽  
Author(s):  
Arun Kumar Gupta ◽  
Satish Kumar ◽  
Pankaj Chandna ◽  
Gian Bhushan
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.


2008 ◽  
Vol 205 (1-3) ◽  
pp. 224-234 ◽  
Author(s):  
Penghuai Fu ◽  
Alan A. Luo ◽  
Haiyan Jiang ◽  
Liming Peng ◽  
Yandong Yu ◽  
...  

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