Optimation of AMC's Tensile Properties Using Adaptive Neuro-Fuzzy Inference System (ANFIS)

Abstract

The addition of organoclay to Aluminium Matrix Composite (AMC) with heat treatment and setting process variables was able to change the microstructure affecting its mechanical properties. The method used in this study was a hot press. The pressure used was of 137.8951458634 MPa, and the temperature varies from 490-600 °C with a holding time of 3 hours. Characterization was carried out using XRD, optical microscope, hardness tester, and ultrasonic tester. The data analysis showed that the hardness increased from 126 to 197 HVN. Furthermore, the mass density also increased, and reached an optimal value with the addition of 1% wt of organoclay at a temperature of 550 °C. The microstructure exhibited that AMC was formed and increased the hardness and density. XRD results indicated that aluminium phase was successfully detected. From the results of several characterizations, it can be concluded that the optimal material has the composition by adding 1% wt of organoclay with a heating temperature of 550 °C, a pressure of 13.7859558534 MPa and a long press time of 3 hours. In this study, we construct a relationship between process variables based on experimental, computational design and use the Inference Adaptive Neuro-Fuzzy inference (ANFIS) method. Furthermore, the prediction accuracy made by the model was investigated based on the test case. The results showed that the hot press method had a relationship with the attraction properties having the same conclusion using experiments and ANFIS.