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dc.contributor.authorCharnley, F
dc.contributor.authorTiwari, D
dc.contributor.authorHutabarat, W
dc.contributor.authorMoreno, M
dc.contributor.authorOkorie, OS
dc.contributor.authorTiwari, A
dc.date.accessioned2019-06-21T08:00:35Z
dc.date.issued2019-06-19
dc.description.abstractThis paper presents an investigation on how simulation informed by the latest advances in digital technologies such as the 4th Industrial Revolution (I4.0) and the Internet of Things (IoT) can provide digital intelligence to accelerate the implementation of more circular approaches in UK manufacturing. Through this research, a remanufacturing process was mapped and simulated using discrete event simulation (DES) to depict the decision-making process at the shop-floor level of a remanufacturing facility. To understand the challenge of using data in remanufacturing, a series of interviews were conducted finding that there was a significant variability in the condition of the returned product. To address this gap, the concept of certainty of product quality (CPQ) was developed and tested through a system dynamics (SD) and DES model to better understand the effects of CPQ on products awaiting remanufacture, including inspection, cleaning and disassembly times. The wider application of CPQ could be used to forecast remanufacturing and production processes, resulting in reduced costs by using an automatised process for inspection, thus allowing more detailed distinction between “go” or “no go” for remanufacture. Within the context of a circular economy, CPQ could be replicated to assess interventions in the product lifecycle, and therefore the identification of the optimal CE strategy and the time of intervention for the current life of a product—that is, when to upgrade, refurbish, remanufacture or recycle. The novelty of this research lies in investigating the application of simulation through the lens of a restorative circular economic model focusing on product life extension and its suitability at a particular point in a product’s life cycle.en_GB
dc.description.sponsorshipEngineering and Physical Sciences Research Council (EPSRC)en_GB
dc.description.sponsorshipRoyal Academy of Engineering (RAEng)en_GB
dc.description.sponsorshipAirbusen_GB
dc.identifier.citationVol. 11(12), 3379en_GB
dc.identifier.doi10.3390/su11123379
dc.identifier.urihttp://hdl.handle.net/10871/37609
dc.language.isoenen_GB
dc.publisherMDPIen_GB
dc.rights© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).en_GB
dc.subjectcircular economyen_GB
dc.subjectcircular 4.0en_GB
dc.subjectremanufacturingen_GB
dc.subjectdiscrete event simulation (DES)en_GB
dc.subjectsystem dynamics (SD)en_GB
dc.titleSimulation to enable a data-driven circular economyen_GB
dc.typeArticleen_GB
dc.date.available2019-06-21T08:00:35Z
dc.descriptionThis is the final version. Available on open access from MDPI via the DOI in this record.en_GB
dc.descriptionThe underlying data can be accessed at 10.15131/shef.data.8246912en_GB
dc.identifier.journalSustainabilityen_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2019-06-12
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2019-06-12
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2019-06-19T15:51:56Z
refterms.versionFCDVoR
refterms.dateFOA2019-06-21T08:00:42Z
refterms.panelCen_GB


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© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's licence is described as © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).