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During the last few years, the prediction and optimization of cutting process parameters in various machining processes have received more attention than ever before, from research community all over the world. The soft computing techniques which are used for predicting and optimizing the cutting process parameters offer a number of advantages over the traditional numerical methods. In this book, the effect of the cutting process parameters in boring tool with and without impact dampers has been studied. The impact dampers made up of Copper, Phosphor Bronze, Brass, Gun Metal, EN8, Cast Iron and Aluminium were used and the cutting parameters and their effect on cutting responses in boring tool with and without dampers have been studied experimentally. Then the experimental values obtained were modelled for prediction with the help of Artificial Neural Network (ANN). The optimum set of readings was determined using Response Surface Methodology (RSM) and the interaction effect cutting parameter on cutting responses were discussed using Analysis of Variance (ANOVA) method.
In one volume it provides data acquisition by DIP techniques, its analysis by statistical techniques, and its presentation by computer graphics plus the use of rapid prototyping technologies to speed up the entire process.
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