Preliminary studies have shown the superiority of convolutional neural networks (CNNs) compared to other network architectures for determining surface quality friction stir welds. In this paper, CNNs were employed detect cavities inside welds by evaluating inline measured process data. The aim was determine whether are suitable identifying defects exclusively, or if approach is transferable int...

To understand the friction stir welding process, it is very important to know the nature of the material flow in and around the tool. The process is a combination of both thermal as well as mechanical work i.e. it is a coupled thermo-mechanical process. Numerical simulations are very much essential in order to obtain a complete knowledge of the process as well as the physics underlying it. In t...

in this article effects of friction stir welding (fsw) tool rotational and traverse speeds were studied on heat generation and temperature distribution in welding zone of aa1100 aluminium alloy. computational fluid dynamics method was used to simulate the process with commercial cfd fluent 6.4 package. to enhance the accuracy of simulation in this study, the welding line that is located workpie...

In the present study, the effect of material and process parameters on the morphological and hardness properties of friction stir process (FSP) acrylonitrile butadiene styrene (ABS) were investigated. For this purpose, firstly ABS polymeric sheets were injection molded. Then a slot with predetermined depth and width was created on sheets using a horizontal milling machine. Nano type (nanoclay, ...

The axial force measurement plays important role in tool designing and identification of its restrictions. Also, it is vital in design of machine mechanism and optimization of welding process parameters. In this study, a friction stir welded butt join on AA7075-T651 aluminum alloy plate is investigated. With change of some parameters, factors including axial force, mechanical properties, microh...