Optimization of green sand mould system using Taguchi based grey relational analysis

被引:13
作者
Pulivarti, Srinivasa Rao [1 ]
Birru, Anil Kumar [1 ]
机构
[1] Natl Inst Technol, Mech Engn Dept, Manipur 795004, India
关键词
green sand; bentonite; fly ash; molasses; Taguchi based grey relational analysis; grain fineness number; PROCESS PARAMETERS; CASTINGS; DESIGN;
D O I
10.1007/s41230-018-7188-1
中图分类号
TF [冶金工业];
学科分类号
0806 ;
摘要
The strength of the mould cavity in sand casting is very much significant to attain high-quality castings. Optimization of green sand process parameters plays a vital role in minimizing casting defects. In the present research work, the effect of process parameters such as AFS grain fineness number, water, molasses, bentonite, fly ash, and ramming, and their levels on the resultant mould properties were investigated and optimized using Taguchi based grey relational analysis. The Taguchi L18 orthogonal array and analysis of variance (ANOVA) were used. The quality characteristics viz., green compression strength, permeability, bulk density, mould hardness and shatter index of green sand mould were optimized using grey relational grade, based on the experiments designed using Taguchi's Design of Experiments. ANOVA analysis indicated that water content is the most influential parameter followed by bentonite, and degree of ramming that contributes to the quality characteristics. The results are confirmed by calculating confidence intervals, which lies within the interval limits. Finally, microstructure observations and X-ray diffraction analysis have been performed for the optimal sand parametric combination. Results show that presence of maximum amount of SiO2, which might be the reason for enhancement of the physical properties of the sand.
引用
收藏
页码:152 / 159
页数:8
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