Closure to “Construction Robot Path-Planning for Earthwork Operations” by Sung-Keun Kim, Jeffrey S. Russell, and Kyo-Jin Koo

Novel artificial neural network model for evaluating hardness of stir zone of submerge friction stir processed Al 6061-T6 plate

“…In recent years, Al alloys have attracted the attention of many researchers, engineers and designers as promising structural materials for automotive industry or aerospace applications. [1][2][3] Especially, 6xxx Al alloys have been studied extensively because of their benefits, such as medium strength, formability, weldability, corrosion resistance and low cost, compared to other Al alloys. [2][3][4] It is expected that substitution of such Al alloys for steels will result in great improvements in energy economy, recyclability and life cycle cost.…”

“…[1][2][3] Especially, 6xxx Al alloys have been studied extensively because of their benefits, such as medium strength, formability, weldability, corrosion resistance and low cost, compared to other Al alloys. [2][3][4] It is expected that substitution of such Al alloys for steels will result in great improvements in energy economy, recyclability and life cycle cost. However, to achieve higher wear resistance for further applications to the industries, it is necessary to improve the surface hardness.…”

“…Artificial neural network (ANN) is a very useful tool to model the interrelationship between the input and the output of complicated systems such as welding process. [3][4][5] Vasudevan et al developed a model to predict ferrite number in austenitic stainless steel and zircaloy-2 welds. They used ANN for assessing the quality of welds in terms of weld microstructure, mechanical properties and weld defects.…”