Optimization of composition of heat-treated chromium white cast iron casting by phosphate graphite mold

• Published in: Journal of alloys and compounds 2008-10, Vol.466 (1), p.273-280
• Main Authors: Cai, An-hui, Zhou, Yong, Tan, Jing-ying, Luo, Yun, Li, Tie-lin, Chen, Min, An, Wei-ke
• Format: Article
• Language: English
• Subjects: Applied sciences; Artificial neural network; Exact sciences and technology; Foundry engineering; Fuzzy optimum design; Heat treatment; Metals. Metallurgy; Orthogonal design; Other casting methods. Solidification; Other heat treatments; Production techniques; White cast iron
• ISSN: 0925-8388; 1873-4669
• DOI: 10.1016/j.jallcom.2007.11.042

In present work, the difference among orthogonal design, Fuzzy optimum design and artificial neural network ANN was performed on the basis of the optimization of chemical composition of chromium white cast iron. It is found that Fuzzy optimum design is suitable for multi-objective comprehensive evaluation, and the optimum composition of white cast iron is Cr 4%, Si 3.5%, Mn 3% and Cu 1% in the orthogonal array. On the other hand, the orthogonal analysis is suitable for analyzing the effect of each factor on the performances and obtaining the theoretical optimum combination of each factor for the performances and the optimum theoretical performances, respectively. Moreover, the prediction and simulation results show that the RBFANN not only can be used to establish the model with high accuracy for the orthogonal test but also outperforms the traditional orthogonal analysis method. Therefore, the combination of three methods can more effectively deal with the optimization of chemical composition of materials.