In the process of industrial production, products with different specifications (ie, the
difference in geometry, process conditions, and machine conditions, etc.) have different …

The transformation of production mode leads to the need to strictly ensure the order in-time
delivery. The global control ability of manufacturing workshops has become a necessary …

Multivariate machining quality prediction of thin-walled parts with multiple machining
features is a complex problem due to different data distribution between training and …

In recent years, there has been a growing surge of interest in the application of data
analytics (DA) within the realm of supply chain management (SCM), attracting attention from …

Due to the abundance of information, Artificial Intelligence (AI) research and development is
a major focus in academia and industry. As the data volume increases, organizations face …

The product quality has become increasingly important for the modern manufacturing
processes. Due to the measurement delay, data-driven soft sensor models are usually built …

In quest of improving the productivity and efficiency of manufacturing processes, Artificial
Intelligence (AI) is being used extensively for response prediction, model dimensionality …

Traditional closed-set diagnostic methods assume identical label spaces for the source and
target domains. Nevertheless, unlike the source domain, the target domain can include …

This computational study explores the potential of several soft-computing techniques for
wind turbine (WT) output power (kW) estimation based on seven input variables of wind …

Quality prediction, as a means of identifying potential quality issues in products, plays a
crucial role in increasing the level of quality control within enterprises. The data from the …