Abstract Design and process optimization are key aspects of manufacturing engineering.
This contribution details a machine learning (ML) methodology capable of learning from …

This research introduces a machine learning (ML)-based methodology for the optimal blank
design of components manufactured through the deep drawing process, considering the …

Drawbeads are used when forming drawpieces with complex shapes to equalise the flow
resistance of a material around the perimeter of the drawpiece or to change the state of …

This study presents an innovative methodology for preform design in metal forging
processes based on the convolution neural network (CNN) algorithm. The proposed …

Electrical, metal, plastic, and food manufacturing are among the major energy-consuming
industries in the US Since 1981, the US Department of Energy Industrial Assessments …

Single point incremental forming (SPIF) is one of the most promising technologies for the
manufacturing of sheet metal prototypes and parts in small quantities. Similar to other …

Sheets' buckling instability, also known as oil canning, is an issue that characterizes the
resistance to denting in thin metal panels. The oil canning phenomenon is characterized by …

Fiber reinforcement orientation in thermoplastic injection-molded components is both a
strength as well as a weak point of this largely employed manufacturing process. Optimizing …

In the present work, a digital twin of a radial-axial ring rolling machine was built by modelling
the time series of the positions of the tools and control signals rather than the metrics of the …

Designing magnesium sheet alloys for room temperature (RT) forming is a challenge due to
the limited deformation modes offered by the hexagonal close-packed crystal structure of …