With growing evidence of deep learning-assisted smart process planning, there is an
essential demand for comprehending whether cyber-physical production systems (CPPSs) …

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 …

Understanding the interactions of Industry 4.0 and sustainability is a cutting-edge research
topic. The present study aims to contribute to this research topic by explaining how Industry …

With significant advancement in information technologies, Digital Twin has gained
increasing attention as it offers an enabling tool to realise digitally-driven, cloud-enabled …

Data analytics in massive manufacturing data can extract huge business values while can
also result in research challenges due to the heterogeneous data types, enormous volume …

Abstract The Fourth Industrial Revolution (Industry 4.0) leads to mass personalisation as an
emerging manufacturing paradigm. Mass personalisation focuses on uniquely made …

With the development of manufacturing, machining data applications are becoming a key
technological component of enhancing the intelligence of manufacturing. The new …

The notion of smart cities has remained under evolution as its global implementations are
challenged by numerous technological, economic, and governmental obstacles. Moreover …

The wide proliferation of various wireless communication systems and wireless devices has
led to the arrival of big data era in large-scale wireless networks. Big data of large-scale …

The study's primary objective is to identify the implications of Industry 4.0 (I4. 0)
implementation for renewable energy management and materials development. The study …