dc.contributor.author
Escrig, Josep
dc.contributor.author
Fischer, Oliver J.
dc.contributor.author
Gomes, Rachel L.
dc.contributor.author
Watson, Nicholas
dc.date.accessioned
2022-09-28T15:32:30Z
dc.date.accessioned
2024-12-09T15:44:18Z
dc.date.available
2022-09-28T15:32:30Z
dc.date.available
2024-12-09T15:44:18Z
dc.date.issued
2020-01-01
dc.identifier.uri
https://hdl.handle.net/2072/522724
dc.description.abstract
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.
eng
dc.format.extent
7 p.
cat
dc.relation.ispartof
Johnson Matthey Technology Review
cat
dc.relation.ispartofseries
Volum 64;Núm. 1
dc.rights
From January 2016 to October 2022 the Johnson Matthey Technology Review was licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
You may share, copy and redistribute the material in any medium or format for any lawful purpose. You must give appropriate credit to the author and publisher. You may not use the material for commercial purposes without prior permission. You may not distribute modified material without prior permission.
The rights of users under exceptions and limitations, such as fair use and fair dealing, are not affected by the CC licenses.
dc.source
RECERCAT (Dipòsit de la Recerca de Catalunya)
dc.subject.other
Industry
cat
dc.subject.other
Artificial Intelligence & Big Data
cat
dc.title
Intelligent Resource Use to Deliver Waste Valorisation and Process Resilience in Manufacturing Environments
cat
dc.type
info:eu-repo/semantics/article
cat
dc.type
info:eu-repo/semantics/publishedVersion
cat
dc.identifier.doi
/10.1595/205651320X15735483214878
cat
dc.rights.accessLevel
info:eu-repo/semantics/openAccess