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Intelligent Resource Use to Deliver Waste Valorisation and Process Resilience in Manufacturing Environments

Fisher, Oliver J.; Watson, Nicholas J.; Escrig, Josep E.; Gomes, Rachel L.

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Authors

Oliver J. Fisher

Nicholas J. Watson

Josep E. Escrig

RACHEL GOMES rachel.gomes@nottingham.ac.uk
Professor of Water & Resource Processing



Abstract

© 2020 Johnson Matthey Circular economy (CE) thinking has emerged as a route to sustainable manufacture, with related cradle-to-cradle implications requiring implementation from the design stage. The challenge lies in moving manufacturing environments away from the traditional linear economy paradigm, where materials, energy and water have often been designed to move out of the system and into receivership of waste management bodies after use. Recent applications of industrial digital technologies (IDTs: for example internet of things, data-driven modelling, cyber-physical systems, cloud manufacturing, cognitive computing) to manufacturing may be instrumental in transforming manufacturing from linear to circular. However, although IDTs and CE have been the focus of intensive research, there is currently limited research exploring the relationship between IDTs and the CE and how the former may drive the implementation of CE. This article aims to close the knowledge gap by exploring how an IDT (data-driven modelling) may facilitate and advance CE principles within process manufacturing systems, specifically waste valorisation and process resilience. These applications are then demonstrated through two real-world manufacturing case studies: (a) minimising resource consumption of industrial cleaning processes and (b) transforming wastewater treatment plants (WWTPs) into manufacturing centres.

Citation

Fisher, O. J., Watson, N. J., Escrig, J. E., & Gomes, R. L. (2020). Intelligent Resource Use to Deliver Waste Valorisation and Process Resilience in Manufacturing Environments. Johnson Matthey Technology Review, 64(1), 93-99. https://doi.org/10.1595/205651320x15735483214878

Journal Article Type Article
Acceptance Date Jan 12, 2019
Online Publication Date Jan 13, 2020
Publication Date Jan 13, 2020
Deposit Date Jan 15, 2020
Publicly Available Date Jan 15, 2020
Journal Johnson Matthey Technology Review
Electronic ISSN 2056-5135
Peer Reviewed Peer Reviewed
Volume 64
Issue 1
Pages 93-99
DOI https://doi.org/10.1595/205651320x15735483214878
Public URL https://nottingham-repository.worktribe.com/output/3730019
Publisher URL https://www.technology.matthey.com/article/64/1/93-99/

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