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Optimization of Machining Parameters Using Fuzzy Based Principal Component Analysis during dry turning operation of Inconel 625 – A hybrid approach
, , Saxena V, Pandey R, Harsha T, Kumar G.
Published in Elsevier BV
Volume: 97
Pages: 668 - 676
The paper presents a hybrid approach for optimization of machining parameters during dry turning operation of Inconel 625. Inconel 625 is known to be the most difficult to cut material and processing of which is a major challenge to the manufacturing sector. Various researches have been conducted to optimize the machining parameter using utility theory, grey relational theory in combination with Taguchi method. In this paper fuzzy based Principal component function coupled with Taguchi's design of experiment is used for optimization of machining parameters for minimum surface roughness, and power consumption, and maximum material removal rate. Taguchi based design of experiment facilitates the finding of the most relevant information about the feature of the system to be optimized. L9 orthogonal array has been chosen as the design of experiment for the current study. The multiple responses are aggregated into a single multi-performance index using fuzzy based Principal component function. To avoid uncertainty, imprecision and vagueness, fuzzy system is incorporated in this research work. The fuzzy reasoning grades so obtained are optimized using the Taguchi. The optimal setting and the influence of the process parameters on the multi-performance index is determined using response table, response graph and analysis of variance. Finally, optimal cutting conditions for the minimum machinability properties were highlighted. © 2014 Published by Elsevier Ltd.
About the journal
JournalData powered by TypesetProcedia Engineering
PublisherData powered by TypesetElsevier BV
Open AccessNo