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dc.contributor.authorLuz, G., Tortorella, G.L., Bouzon, M., Garza-Reyes, J.A., Gaiardelli, P.
dc.date.accessioned2020-10-23T09:26:41Z
dc.date.available2020-10-23T09:26:41Z
dc.date.issued2020-10-19
dc.identifier.citationLuz, G., Tortorella, G.L., Bouzon, M., Garza-Reyes, J.A., Gaiardelli, P. (2020). 'Proposition of a method for stochastic analysis of value streams'. Production Planning & Control: The Management of Operations, pp. 1-48.en_US
dc.identifier.issn0953-7287
dc.identifier.doi10.1080/09537287.2020.1833377
dc.identifier.urihttp://hdl.handle.net/10545/625270
dc.description.abstractThis article aims at proposing a method to stochastically analyze values streams taking into consideration the effect of critical uncertainty sources on lead time. The proposed method combines value stream mapping (VSM) and Monte Carlo simulation to identify improvement opportunities. To illustrate this approach, we carried out a case study in the special nutrition value stream of a Brazilian public hospital. Results show that the proposed method allows the identification of improvement opportunities that would not be considered in the classical deterministic VSM approach. Further, the integration of the stochastic analysis enables the determination of a more realistic lead time, which supports a more assertive planning and scheduling of the value stream. The proposed method addresses a fundamental gap in traditional VSM without adding much complexity to the analysis procedure, which is a common practical issue in previous works that integrated other stochastic methods into VSM.en_US
dc.description.sponsorshipN/Aen_US
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.relation.urlhttps://www.tandfonline.com/doi/full/10.1080/09537287.2020.1833377en_US
dc.rightsCC0 1.0 Universal*
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.subjectValue stream mapping, Monte Carlo simulation, Uncertainty sourcesen_US
dc.titleProposition of a method for stochastic analysis of value streamsen_US
dc.typeArticleen_US
dc.identifier.eissn1366-5871
dc.contributor.departmentUniversidade Federal de Santa Catarina, Brazilen_US
dc.contributor.departmentThe University of Melbourneen_US
dc.contributor.departmentUniversity of Derbyen_US
dc.contributor.departmentUniversità degli Studi di Milanoen_US
dc.identifier.journalProduction Planning and Controlen_US
dcterms.dateAccepted2020-10-04
dc.author.detail780891en_US


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