Conceptual Framework for a Data Model to Support Asset Management Decision-Making Process - Inria - Institut national de recherche en sciences et technologies du numérique
Communication Dans Un Congrès Année : 2019

Conceptual Framework for a Data Model to Support Asset Management Decision-Making Process

Adalberto Polenghi
  • Fonction : Auteur
  • PersonId : 1061528
Irene Roda
  • Fonction : Auteur
  • PersonId : 991434
Marco Macchi
  • Fonction : Auteur
  • PersonId : 991431
Alessandro Pozzetti
  • Fonction : Auteur
  • PersonId : 991432

Résumé

Information and data management is nowadays a central issue to support the Asset Management (AM) decision-making process. Manufacturing companies have to take different decisions along the asset lifecycle and at different organisational levels, and, to this end, they require proper information and data management. In the literature, besides the crucial role played by information and data, there is evidence of existing gaps, especially related to information management and integration, and transformation of data into useful information. Thus, a conceptual framework is proposed to guide the definition of a data model to fulfil the previously identified gap. Generally, the framework aims at contributing to the improvement of the integration of information along the AM decision-making process. Specifically, it is intended to be aligned with the AM theory and, in particular, its fundamentals defined in the scientific literature and the ISO 5500x body of standards. Overall, thanks to the improvement of the information management and integration along with the AM decision-making, the expectation is to be capable of achieving more value-oriented decisions for the asset lifecycle.
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hal-02419270 , version 1 (19-12-2019)

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Adalberto Polenghi, Irene Roda, Marco Macchi, Alessandro Pozzetti. Conceptual Framework for a Data Model to Support Asset Management Decision-Making Process. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2019, Austin, TX, United States. pp.283-290, ⟨10.1007/978-3-030-30000-5_36⟩. ⟨hal-02419270⟩
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