Realistic interplays between data science and chemical engineering in the first quarter of the 21st century, part 2: Dos and don’ts

AI-assisted chemistry research: a comprehensive analysis of evolutionary paths and hotspots through knowledge graphs

“…The ''trade'' report in 2018 stated that this ''once-in-a-lifetime'' opportunity will create an astonishing value of $100 trillion, resulting in changes across all industries due to data science. 1 Traditionally, chemical research relied heavily on empirical guidance, extensive experimentation, and limited computer simulations, consuming a considerable amount of human resources, time, materials, and resources. 2 The inherent limitations of human cognitive abilities make it a challenge for humans to absorb and process vast amounts of literature and data, causing chemists to spend a considerable amount of time on repetitive experiments.…”

Difficulties and Critical Success Factors for Implementing Industry 4.0 Technologies in the Continuous Process Chemical Industry

“…The new technologies that follows Industry 4.0 are based on network communication and data management. Information can be obtained from a more volumous, fast and heterogeneous data (Big Data) to generate a virtual copy of the production facilities (PICCIONE et al, 2021) [6]. Cyber-physical systems (CPS) monitor the physical processes in real time, through sensors, actuators and simulators, increasing the process efficiency through decentralized decision-making (AITHAL, 2020; HERMANN et al, 2016; SHEVTSOVA et al, (2020) [5], [7], [8].…”