FUZZY MODELING AND PARAMETRIC ANALYSIS OF NON-TRADITIONAL MACHINING PROCESSES

The application of artificial intelligence (Al) 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.