Recent technological advancements such as IoT and Big Data have granted industries
extensive access to data, opening up new opportunities for integrating artificial intelligence …

Small and medium-sized enterprises (SMEs) often encounter practical challenges and
limitations when extracting valuable insights from the data of retrofitted or brownfield …

Many “Industry 4.0” applications rely on data-driven methodologies such as Machine
Learning and Deep Learning to enable automatic tasks and implement smart factories …

The last few decades have been characterised by a very active application of smart
technologies in various fields of industry. This paper deals with industrial activities, such as …

This study introduces a novel approach using Physics-Informed Neural Networks (PINN) to
predict weld line visibility in injection-molded components based on process parameters …

The growing move toward smart factories can leverage industrial big data to enhance
productivity. In particular, research is being conducted on injection molding and utilizing …

Recycling practices in injection molding can reduce costs and enhance sustainability. This
research especially addresses small-to medium-sized companies. The use of scrap material …

Plastic injection molding is a widespread industrial process in manufacturing. This article
investigates the energy consumption in the injection molding process of fruit containers …

Soil organic carbon (SOC) dataset augmentation, which enables the comprehensive
monitoring of carbon sinks at regional and global scales, is vital for global carbon cycle …

Introduction Develo** and evaluating a machine learning model to predict failures in an
injection moulding process offers significant potential to advance manufacturing …