The purpose of our systematic review is to examine the recently published literature on the
Internet of Manufacturing Things (IoMT), and integrate the insights it configures on deep …

Digital transformation refers to the unprecedented disruptions in society, industry, and
organizations stimulated by advances in digital technologies such as artificial intelligence …

Abstract Internet of Things (IoT) technology, which has made manufacturing processes more
smart, efficient and sustainable, has received increasing attention from the industry and …

Digital twinning is one of the top ten technology trends in the last couple of years, due to its
high applicability in the industrial sector. The integration of big data analytics and artificial …

The complex future power plants require digital twin (DT) architecture to achieve high
reliability, availability and maintainability at lower cost. The available research on DT for …

From the last decade, additive manufacturing (AM) has been evolving speedily and has
revealed the great potential for energy-saving and cleaner environmental production due to …

Green innovation is key to promoting the manufacturing industry's green development and
transformation. One way to promote green innovation in manufacturing enterprises can be …

Data-driven models for industrial energy savings heavily rely on sensor data,
experimentation data and knowledge-based data. This work reveals that too much research …

Abstract In Industry 4.0, the production data obtained from the Internet of Things has reached
the magnitude of big data with the emergence of advanced information and communication …

Purpose This study aims to examine the role of big data analytics (BDA) powered by artificial
intelligence (AI) in improving sustainable performance (SP) through green supply chain …