Fuzzy logic-based expert system for prediction of depth of cut in abrasive water jet machining process

Abstract

The development of an expert system for abrasive water jet machining (AWJM) process is considered in the present work. The expert system has been developed by using fuzzy logic (FL). It is to be noted that the performance of AWJM in terms of depth of cut depends on various process parameters, such as diameter of focusing nozzle, water pressure, abrasive mass flow rate and jet traverse speed. Three approaches have been developed to predict the depth of cut in AWJM using FL system. The first Approach deals with the construction of Mamdani-based fuzzy logic system. It is important to note that the performance of the FL depends on its knowledge base. In Approach 2, the data base and rule base of the FL-system are optimized, whereas in the third Approach, the total FL-system is evolved automatically. A binary-coded genetic algorithm has been used for the said purpose. The developed expert system eliminates the need of extensive experimental work, to select the most influential AWJM parameters on the depth of cut. The performances of the developed FL-systems have been tested to predict the depth of cut in AWJM process with the help of test cases. The prediction accuracy of the automatic FL-system (i.e. Approach 3) is found to be better than the other two approaches.