Abstract Machine learning (ML) methods have received immense attention as potential
models for modeling different manufacturing systems. This paper presents a comprehensive …

This review is on the various techniques and methodologies applied to sensor based
monitoring of the quality and control of defects in an advanced joining process named …

In the current scenario, industries need to have continuous improvement in their
manufacturing processes. Digital twin (DT), a virtual representation of a physical entity …

Advances in artificial intelligence (AI) techniques that can be used for different purposes
have enabled it to be used in many different industrial applications. These are mainly used …

In the present work, a novel cloud-based remote and real time monitoring and control
scheme has been developed for a manufacturing process named friction stir welding (FSW) …

In the current research, a coupled Eulerian and Lagrangian method is used to model the
friction stir welding process. Volume of fluid principle is used to predict the formation of …

This study proposes a strategy for developing force-data-driven machine learning models to
precisely predict defects and their types in friction stir welding (FSW). The characteristics of …

随着人-信息-物理系统(Human-cyber-physical systems, HCPS) 的发展与演进,
人机关系由人机共存, 人机交互, 人机合作逐渐发展到人机协作. 与此同时, 数字孪生等新兴使能 …

In this paper, the characteristics of traverse force (Fx), lateral force (Fy), and axial force (Fz)
in bobbin tool friction stir welding (BTFSW) and their relationship with welding defects were …

Abstract The Friction Stir Welding (FSW) process is known as a solid state welding process
comparably stable against external disturbances in its steady state. Therefore, the process is …