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

Sensors play a crucial role in factory automation in making the system intellectual. Different
types of sensors are available as per the suitability and applications; some of them are …

Artificial intelligence (AI) embedded within digital models of manufacturing processes can be
used to improve process productivity and product quality significantly. The application of …

Friction stir welding is a method used to weld together materials considered challenging by
fusion welding. FSW is primarily a solid phase method that has been proven efficient due to …

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 …

Job shop manufacturing is characterized by excellent job flexibility and highly customizable
products. The dynamic nature of jobs in this manufacturing segment poses a relatively high …

With remarkable learning capabilities and swift operational speeds, artificial intelligence (AI)
can assist researchers in swiftly extracting valuable patterns, trends, and associations from …

The precision and performance of machined flexible parts are under influence of
deformation errors during end milling operations. Thus, prediction and compensation of …

The demand for high quality and effective manufacturing has raised the need for defect
identification in friction stir welding. This work aims to identify the tunnel defect inside the …

The fourth industrial revolution, Industry 4.0, has brought internet, artificial intelligence (AI),
and machine learning (ML) concepts into manufacturing. There is an immediate need to …