Optimization of Process Productivity for Multi Phase Carbon Nanotubes (CNT) Reinforced Nanocomposites Using Taguchi-Fuzzy Model

Abstract

The present work is focused on the processing and machining of multiphase carbon nanotubes reinforced nanocomposites. In this work the author has performed electric discharge machining on multiphase carbon nanotubes reinforced nanocomposites. Optimal combination of different process parameters have been decided determined for maximum material removal rate and minimum tool wear rate which results the improvement in productivity of the complete process. In this study four different process parameters (Peak current, gap voltage, pulse on time and duty cycle) are used and the most significant parameter is illustrated. In the present work, the factor material removal rate has been considered as productivity measure. The goal is to determine the best process condition for maximizing material removal rate and simultaneously for minimizing the tool wear rate values, which may be considered as multi-response optimization problem. Taguchi method is a well known optimization technique used for optimizing the single objective function. Consequently the conversion process of objective functions invites ambiguity, uncertainly etc. into the computation. These implications always arises the need to correlate various responses. Hence to overcome these implications a fuzzy reasoning of multiple performance characteristics has been developed. This results in the transformation of multi performance characteristics in single multi-performance characteristics (Productivity) and can be optimized using Taguchi method. Using Taguchi’s design of experiment methodology optimal combination of process parameters will be obtained for various performance measures. Process productivity Optimize using the Fuzzy logic approach and the optimal results were also validated.