Abstract
This paper discusses the optimization of an abrasive water jet machining process with multiple characteristics, using the Taguchi orthogonal array and grey relational analysis (GRA). The machining process variables, such as mesh size, nozzle diameter, abrasive flow rate, water pressure, stand-off distance, and feed rate, were optimized with respect to multiple performance characteristics, namely, the surface roughness and the kerf angle. Experiments were performed using an L18 orthogonal array, and the optimum machining process variables were determined, using GRA. Analysis of variance was used to identify the most significant factor in the machining performance. A confirmatory test was performed to verify the improvement of the performance characteristics. The microstructure of the machined surfaces was also examined by scanning electron microscopy and atomic force microscopy. The results showed that the surface roughness and kerf angle were minimized under optimal machining conditions.
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