AI Summary & Key Takeaways
AI InsightAn excellent correlation was found between experimental hardness results and ANNs hardness results.
📌 3 Key Takeaways
Abstract
A lot of experiments must be conducted in order to find an appropriate technology for the calculation of strength of the materials, which wastes both man power and money. For this reason artificial neural networks (ANNs) have been used to search the optimum technology proper for pre-aged AA 6063 aluminum alloy. In this study, ANNs were used to compare experimental results and test data were used for teaching of the ANNs. This paper examines the changes in the hardness of AA 6063 alloys when heat treated at different pre-aging treatments. The alloy was solution treated for 1 hour at 525±3 $\circ_C$ and quenched in water. After quenching, samples were subjected to five different pre-aging times, 2 hours, 1 day, 3 days, 7 days. On the other hand, some specimens were not pre-aged. Artificial age temperatures were selected as 160 $\circ_C$ and 180 $\circ_C$. The hardness values of these under-aged alloys were measured. When the pre-aging time was 7 days, the hardness values of the specimens increased. An excellent correlation was found between experimental hardness results and ANNs hardness results.