|Educational Degree||Master of Technology (M.Tech.)|
|Subject Domain (in DDC)||Technology ♦ Manufacturing|
|Subject Keyword||Production Engineering|
|Abstract||In recent years, aluminum alloy based metal matrix composites (MMC) are gaining importance in several aerospace and automobile applications. Aluminum has been used as matrix material owing to its excellent mechanical properties coupled with good formability. Addition of SiCp as reinforcement in aluminium system improves mechanical properties of the composite. In the present investigation, Al-SiCp composite was prepared by powder metallurgy route. Powder metallurgy homogeneously distributes the reinforcement in the matrix with no interfacial chemical reaction and high localized residual porosity. SiC particles containing different weight fractions (10 and 15 wt. %) and mesh size (300 and 400) is used as reinforcement .Though AlSiC possess superior mechanical properties, the high abrasiveness of the SiC particles hinders its machining process and thus by limiting its effective use in wide areas. Rapid tool wear with poor performance even with advanced expensive tools categories it as a difficult-to-cut material. Non-conventional processes such as electrical discharge machining (EDM) could be one of the best suited method to machine such composites. Four machining parameters such as discharge current (Ip), pulse duration (Ton), duty cycle (),flushing pressure (Fp) and two material properties weight fraction of SiCp and mesh size, and four responses like material removal rate (MRR), tool wear rate (TWR), circularity and surface roughness (Ra) are considered in this study. Taguchi method is adopted to design the experimental plan for finding out the optimal setting. However, Taguchi method is well suited for single response optimization problem. In order to simultaneously optimize multiple responses, a hybrid approach combining principal component analysis (PCA) and fuzzy inference system is coupled with Taguchi method for the optimization of multiple responses. The influence of each parameter on the responses is established using analysis of variances (ANOVA) at 5% level of significance. It is found that discharge current, pulse duration, duty cycle and wt% of SiC contribute significantly, where flushing pressure and mesh size of SiCp contribute least to the multiple performance characteristic index.|
|Education Level||UG and PG|
|Learning Resource Type||Thesis|
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