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Abstract

The application of artificial intelligence (AI) in modeling of various machining processes has

been the topic of immense interest among the researchers since several years. In this direction,

the principle of fuzzy logic, a paradigm of AI technique, is effectively being utilized

to predict various performance measures (responses) and control the parametric settings of

those machining processes. This paper presents the application of fuzzy logic to model two

non-traditional machining (NTM) processes, i.e. electrical discharge machining (EDM) and

electrochemical machining (ECM) processes, while identifying the relationships present between

the process parameters and the measured responses. Moreover, the interaction plots

which are developed based on the past experimental observations depict the effects of changing

values of different process parameters on the measured responses. The predicted response

values derived from the developed models are observed to be in close agreement with those

as investigated during the past experimental runs. The interaction plots also play significant

roles in identifying the optimal parametric combinations so as to achieve the desired

responses for the considered NTM processes.

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Authors and Affiliations

Shankar Chakraborty
Partha Protim Das

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