Optimization of abrasive waterjet machining using multi-objective cuckoo search algorithm

Abrasive waterjet (AWJ) machining is widely applied in the fields of civil and mechanical engineering. In this study, a general and theoretical analysis procedure was presented before computing application. It mainly focused on the kinetic energy model and wear rate model in machining process. Then, the multi-objective cuckoo algorithm was employed for optimization design of AWJ cutting head model, making sure to maximize the output energy and minimize the nozzle erosion rate while keeping the other factors constant. To demonstrate the effectiveness of the above strategy, a practical AWJ machining system was selected for investigation purpose. The proposed model was compared with experimental data for investigating the difference between the initial design and the optimized model. The results showed that the multi-objective cuckoo algorithm has great ability in prediction of outlet power and wear rate. Meanwhile, the optimized parameters were also superior to the original design, compared with experimental test data. The developed model can be used as a systematic approach for prediction in an advanced manufacturing process.