About this Research Topic
The goal of this Research Topic is to explore and exchange ideas with regard to the latest research and development activities in introducing modern technologies and solutions, including both hardware and software and a combination of the two, to create more sustainable processes.
Current R&D efforts dedicated to new sensor technologies, signal processing and filtering, data analytics, data mining, machine learning, artificial intelligence, data-driven modelling and optimizations are welcome. Core subjects are novel practical solutions and techniques for i) process understanding and optimization, ii) process failure detection, diagnosis and prognosis, iii) sensor error detection and measurements, iv) soft sensing, v) process key performance modelling and optimization, and vi) environmental impact modelling and mitigation techniques in process industries.
We welcome Original Research, Review, Mini Review, and Perspective articles that include, but are not limited to, the following topics:
• Use of big data in process industries
• Process control and monitoring
• Process optimization, assessment, integration, and modelling
• Decision support and information systems
• Data-driven decision and policymaking
• Modelling, numerical analysis and simulation
• Environmental systems and software.
Keywords: Industry 4.0, data analytics, machine learning techniques, sensor, process modelling and optimization, prediction, knowledge discovery, environmental engineering, chemical processes
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.