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    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/64873

    Título
    Stochastic-earned duration analysis for project schedule management
    Autor
    Acebes Senovilla, FernandoAutoridad UVA Orcid
    Poza Garcia, David JesúsAutoridad UVA Orcid
    González Varona, José ManuelAutoridad UVA Orcid
    López Paredes, AdolfoAutoridad UVA Orcid
    Año del Documento
    2022
    Editorial
    Elsevier
    Descripción
    Producción Científica
    Documento Fuente
    Engineering, 2022, 9 (February), 148–161.
    Résumé
    Earned duration management (EDM) is a methodology for project schedule management (PSM) that can be considered an alternative to earned value management (EVM). EDM provides an estimation of deviations in schedule and a final project duration estimation. There is a key difference between EDM and EVM: In EDM, the value of activities is expressed as work periods; whereas in EVM, value is expressed in terms of cost. In this paper, we present how EDM can be applied to monitor and control stochastic projects. To explain the methodology, we use a real case study with a project that presents a high level of uncertainty and activities with random durations. We analyze the usability of this approach according to the activities network topology and compare the EVM and earned schedule methodology (ESM) for PSM.
    Palabras Clave
    Earned duration management; Earned value management; Stochastic project control; Duration forecasting; Uncertainty
    ISSN
    2095-8099
    Revisión por pares
    SI
    DOI
    10.1016/j.eng.2021.07.019
    Patrocinador
    This research has been partially financed by the Regional Government of Castille and Leon (Spain) with Grant (VA180P20).
    Version del Editor
    https://www.sciencedirect.com/science/article/pii/S2095809921003854?via%3Dihub#ab005
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/64873
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
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    • DEP53 - Artículos de revista [98]
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    2022 Engineering.pdf
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    2.505Mo
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