With the ongoing digitization of the manufacturing industry and the ability to bring together
data from manufacturing processes and quality measurements, there is enormous potential …

Under the trend of economic globalization, intelligent manufacturing has attracted a lot of
attention from academic and industry. Related enabling technologies make manufacturing …

The importance of data-driven decisions and support is increasing day by day in every
management area. The constant access to volume, variety, and veracity of data has made …

Abstract Process Systems Engineering (PSE) is the scientific discipline of integrating scales
and components describing the behavior of a physicochemical system, via mathematical …

Due to growing concerns regarding climate change and environmental protection, smart
power generation has become essential for the economical and safe operation of both …

Sustainable energy sources are promising solutions for reducing carbon footprint and
environmental impacts within the building sectors. Reducing energy consumption while …

The use of machine learning and data-driven methods for predictive analysis of power
systems offers the potential to accurately predict and manage the behavior of these systems …

In the literature, machine learning (ML) and artificial intelligence (AI) applications tend to
start with examples that are irrelevant to process engineers (eg classification of images …

Abstract Machine learning models are often considered as black-box solutions which is one
of the main reasons why they are still not widely used in operation of process engineering …

The design of chemical-based products and functional materials is vital to modern
technologies, yet remains expensive and slow. Artificial intelligence and machine learning …