Towards a simulation-based understanding of smart remanufacturing operations: a comparative analysis
dc.contributor.author | Okorie, O | |
dc.contributor.author | Charnley, F | |
dc.contributor.author | Ehiagwina, A | |
dc.contributor.author | Tiwari, D | |
dc.contributor.author | Salonitis, K | |
dc.date.accessioned | 2020-06-16T13:55:52Z | |
dc.date.issued | 2020-06-12 | |
dc.description.abstract | While the majority of literature on remanufacturing operations examines an end-of-life (EOL) strategy which is both manual and mechanised, authors generally agree that digitalisation of remanufacturing is expected to increase in the next decade. Subsequently, a new research area described as digitally-enabled remanufacturing, remanufacturing 4.0 or smart remanufacturing is emerging. This is an automated, data-driven system of remanufacturing by means of Industry 4.0 (I4.0) paradigms. Insights into smart remanufacturing can be provided through simulation modelling of the remanufacturing process. While the use of simulation modelling in order to predict responses and behaviour is prevalent in remanufacturing, the use of these tools in smart remanufacturing is still limited in literature. The goal of this research is to present, as a first of its kind, a comparative understanding of simulation modelling in remanufacturing in order to suggest the ideal modelling tool for smart remanufacturing. The proposed comparison includes system dynamics, discrete event simulation and agent based modelling techniques. We apply these modelling techniques on a smart remanufacturing space of a sensor-enabled product and use assumptions derived from industry experts. We then proceed to model the remanufacturing operation from sorting and inspection of cores to final inspection of the remanufactured product. Through our analysis of the assumptions utilised and simulation modelling results we conclude that, while individual modelling techniques present important strategic and operational insights, their individual use may not be sufficient to offer comprehensive knowledge to remanufacturers due to the challenge of data complexity that smart remanufacturing offers. | en_GB |
dc.description.sponsorship | Engineering and Physical Sciences Research Council (EPSRC) | en_GB |
dc.identifier.citation | Published online 12 June 2020 | en_GB |
dc.identifier.doi | 10.1007/s13243-020-00086-8 | |
dc.identifier.grantnumber | EP/R032041/1 | en_GB |
dc.identifier.grantnumber | EP/S018034/1 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/121479 | |
dc.language.iso | en | en_GB |
dc.publisher | Springer Verlag | en_GB |
dc.rights | © The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. | en_GB |
dc.title | Towards a simulation-based understanding of smart remanufacturing operations: a comparative analysis | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2020-06-16T13:55:52Z | |
dc.identifier.issn | 2210-464X | |
dc.description | This is the final version. Available on open access from Springer Verlag via the DOI in this record | en_GB |
dc.identifier.journal | Journal of Remanufacturing | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2020-05-21 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2020-05-21 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2020-06-16T13:53:09Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2020-06-16T13:55:55Z | |
refterms.panel | C | en_GB |
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Except where otherwise noted, this item's licence is described as © The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
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appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and
indicate if changes were made. The images or other third party material in this article are included in the article's
Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included
in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or
exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy
of this licence, visit http://creativecommons.org/licenses/by/4.0/.