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Predictive Modeling for Developing Maintenance Management in Construction Projects

Auteur(s):


Médium: article de revue
Langue(s): en 
Publié dans: Civil Engineering Journal, , n. 4, v. 5
Page(s): 892-900
DOI: 10.28991/cej-2019-03091297
Abstrait:

Maintenance is one of the most important global issue and it taking an increasing recognition in numerous study field. Meanwhile, in Iraq with the absence of an efficient building maintenance management and a lack of appropriate predictive maintenance tool of the current buildings can have a significant negative impact on future building development. Currently, there is a paradigm shift in management of building maintenance from corrective to preventive and predictive approaches that is attainable through creating of an evaluative model to evaluate a variety of alternative decisions. This paper aimed at developing mathematical models for the buildings maintenance. This was achieved through the division of building according to the methods of division based on a number of global maintenance manuals and previous studies. Consequently, based on literature review and interviews with experts on building maintenance, questionnaire was designed that included most of the maintenance items of building. Then, the results of the questionnaire were processed using the Statistical Package for Social Sciences (SPSS), to determine the most important maintenance items, the Weighted Sum Model (WSM) technique was used. Finally, this research recommended adoption the model for quick evaluation and appropriately monitoring of buildings. It will also help architects and engineers to make predictions throughout scientific methods instead dependence on personal decisions.

Copyright: © 2019 Noor S. Omar, Wadhah A. Hatem, Hafeth I. Najy
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

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    sur cette fiche
  • Reference-ID
    10340764
  • Publié(e) le:
    14.08.2019
  • Modifié(e) le:
    02.06.2021