Modeling of Abrasive Water Jet Machining Process using Genetic-Fuzzy System

The present paper deals with the modelling of Abrasive water jet machining (AWJM) process using Fuzzy Logic (FL). It is important to note that the performance of AWJM in terms of required depth of cut in machining depends on various parameters, such as diameter of focusing nozzle, water pressure, abrasive mass flow rate and jet traverse speed. It is to be noted that the performance of the FL system depends on its knowledge base (that is, data base and rule base). The present paper deals with the development of two different approaches. The first approach deals with the development of knowledge base based on the human expertise. The second approach deals with the optimization of data base and rule base using genetic algorithms (GA). This approach will eliminate the need for extensive experimental work to select the most influential AWJM parameters on the depth of cut. The performances of the developed FL-based models have been tested on a number of test cases for predicting the required depth of cut for AWJM process. The prediction accuracy of the FL-based models is found to be satisfactory.