A hybrid approach for selection of optimal process parameters in abrasive water jet cutting

This paper presents a hybrid approach combining fuzzy logic principles and a genetic approach for selecting optimal parameters in abrasive water jet cutting of any material with predetermined thickness. A fuzzy model is built with the knowledge base formed by means of experimental data that is generated by varying the process parameters such as water jet pressure, jet traverse rate and abrasive flowrate at five levels each. This particular model predicts the depth of cut achievable with any given set of process parameters. A genetic algorithm employed in combination with a fuzzy model automatically determines the best combination of process parameters in abrasive water jet cutting of any material. The effectiveness of the proposed approach is demonstrated by a case study dealing with abrasive water jet cutting of black granite.