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dc.contributor.authorPeron, Mirco
dc.contributor.authorSgarbossa, Fabio
dc.contributor.authorStrandhagen, Jan Ola
dc.date.accessioned2021-10-21T06:44:12Z
dc.date.available2021-10-21T06:44:12Z
dc.date.created2020-12-17T10:08:58Z
dc.date.issued2021
dc.identifier.issn0020-7543
dc.identifier.urihttps://hdl.handle.net/11250/2824299
dc.description.abstractThe use of assistive technologies, such as digital instructions (DIs) and collaborative robots (cobots), can improve the productivity of assembly system. However, their implementation remains arbitrary. In this study, a decision support system based on tactical-level variables (i.e. throughput, operator and equipment cost, operation time and type) was proposed with the aim of suggesting when the introduction of assistive technologies becomes profitable. Four different assembly system configurations (i.e. manual assembly, manual assembly with the implementation of DIs, manual assembly with the implementation of cobots and manual assembly with the implementation of both DIs and cobots) were modelled by means of four different cost models and analysed in depth with a parametric analysis carried out by varying the tactical-level variables. The results suggested that, when the throughput is low, the introduction of cobots should be considered only in cases of high operation times, while the introduction of DIs and/or cobots is the best alternative when the throughput is high. Finally, the validity of the approach is proved by comparing the results suggested by the decision support system with those obtained from a case study.en_US
dc.language.isoengen_US
dc.titleDecision support model for implementing assistive technologies in assembly activities: a case studyen_US
dc.typeJournal articleen_US
dc.description.versionsubmittedVersionen_US
dc.rights.holderThis is an original manuscript of an article published by Taylor & Francis, available online: http://dx.doi.org/10.1080/00207543.2020.1856441en_US
dc.source.journalInternational Journal of Production Researchen_US
dc.identifier.doi10.1080/00207543.2020.1856441
dc.identifier.cristin1860883
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.qualitycode2


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