Analysing the machinability of magnesium alloy AZ91

In this experimental research, turning machinability of AZ91D magnesium alloy has been investigated by using Taguchi method. Results of surface roughness obtained from the experiments are modeled with Artificial Neural Networks (ANN), and experimental data as well as ANN model are compared. In the experiments, turning parameters were selected by taking into consideration the parameters used for machining other materials which show similar mechanical properties to magnesium in the literature. Uncoated DCGT, VCGT and CCGT carbide inserts were used for the experiments. Dry cutting and minimum quantity lubrication conditions were applied due to different chemical and physical characteristics of magnesium alloys. In the experiments, three different cutting speeds (500, 750 and 1000 m/min), three different cutting depths (0,5, 1 and 1,5 mm) and three different feed rates (0,05, 0,1 and 0,2 mm/dev) were used. The results of cutting force, surface roughness and wear/ build-up edge obtained from the experiments conducted by cutting values and cooling type have been investigated. The results showed that relatively lower cutting forces have been detected during turning of magnesium alloys. Each experimental result of cutting forces was evaluated. According to the experimental findings, surface roughness values increased as the cutting forces increased. Moreover, adhesion of magnesium alloys has been has been observed on the cutting tools. Comparison of the data obtained from the ANN and experimental results showed that they showed a good compatibility. In this work, a novel results and approaches have been developed about the machining of AZ91D magnesium alloys. The Taguchi method greatly reduces the cost of time and of machining to find the optimum machining solution for this expensive material.