The properties and serviceability of 3D-printed metal parts depend on a variety of attributes.
These include the chemical composition, phases, morphology, spatial distributions of grain …

Driven by the ongoing migration towards Industry 4.0, the increasing adoption of artificial
intelligence (AI) has empowered smart manufacturing and digital transformation. AI …

Additive manufacturing (AM) has undergone significant development over the past decades,
resulting in vast amounts of data that carry valuable information. Numerous research studies …

Additive manufacturing facilitates producing of complex parts due to its design freedom in a
wide range of applications. Despite considerable advancements in additive manufacturing …

Additive manufacturing (AM) has emerged as a disruptive digital manufacturing technology.
However, its broad adoption in industry is still hindered by high entry barriers of design for …

The quick-emerging paradigm of additive manufacturing technology has revealed salient
advantages in enabling the tailored-design of structural components with more exceptional …

Abstract Machine learning (ML) has shown to be an effective alternative to physical models
for quality prediction and process optimization of metal additive manufacturing (AM) …

The quality of powder used in powder bed-based additive manufacturing plays a key role
concerning process performance and end part properties. Even though this is a generally …

Although applications of additive manufacturing (AM) have been significantly increased in
recent years, its broad application in several industries is still under progress. AM also …

In recent years, machine learning (ML) techniques have been extensively investigated to
strengthen the understanding of the complex process dynamics underlying metal additive …