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.