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dc.contributor.authorOluyisola, Olumide Emmanuel
dc.contributor.authorSgarbossa, Fabio
dc.contributor.authorStrandhagen, Jan Ola
dc.date.accessioned2020-05-22T07:09:30Z
dc.date.available2020-05-22T07:09:30Z
dc.date.created2020-05-08T15:15:57Z
dc.date.issued2020
dc.identifier.citationSustainability. 2020, 12 (9), 3791-?.en_US
dc.identifier.issn2071-1050
dc.identifier.urihttps://hdl.handle.net/11250/2655252
dc.description.abstractMany companies are struggling to manage their production systems due to increasing market uncertainty. While emerging ‘smart’ technologies such as the internet of things, machine learning, and cloud computing have been touted as having the potential to transform production management, the realities of their adoption and use have been much more challenging than anticipated. In this paper, we explore these challenges and present a conceptual model, a use-case matrix and a product–process framework for a smart production planning and control (smart PPC) system and illustrate the use of these artefacts through four case companies. The presented model adopts an incremental approach that companies with limited resources could employ in improving their PPC process in the context of industry 4.0 and sustainability. The results reveal that while make-to-order companies are more likely to derive greater benefits from a smart product strategy, make-to-stock companies are more likely to derive the most benefit from pursuing a smart process strategy, and consequently a smart PPC solution.en_US
dc.language.isoengen_US
dc.publisherMDPIen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleSmart Production Planning and Control: Concept, Use-Cases and Sustainability Implicationsen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber3791-?en_US
dc.source.volume12en_US
dc.source.journalSustainabilityen_US
dc.source.issue9en_US
dc.identifier.doihttps://doi.org/10.3390/su12093791
dc.identifier.cristin1809988
dc.description.localcode© 2020 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_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.fulltextpostprint
cristin.qualitycode1


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