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The Impact of Dynamic Risk Interdependencies on the Saudi Precast Concrete Industry

Author(s): ORCID



ORCID
Medium: journal article
Language(s): English
Published in: Buildings, , n. 4, v. 14
Page(s): 875
DOI: 10.3390/buildings14040875
Abstract:

The precast concrete production process faces uncertainties and risks that reduce the efficiency of the Saudi precast concrete industry. Assessing the risk factors’ interdependence yields better results than considering individual analyses only. The previous precast risk studies did not consider the interdependencies among risk factors concerning different process stages. This paper aims to identify precast risk factors and prioritize their importance in Saudi Arabia. Using a dynamic Bayesian network, the assessment considers the interrelationships among the risk factors and different production stages. The risk factors were collected from previous studies, evaluated, and classified into the five construction stages by performing structured interviews with ten experts. The probabilities of the root risks and conditional probabilities of intermediate and leaf risks were assessed based on the ten experts. Then, a Monte Carlo simulation was utilized to provide the status of these probabilities, which were considered input data for the GeNIe program. The main results revealed that erection productivity is the highest risk, with a probability value of 0.87. In addition, the design schedule’s significance directly impacts production capacity, resulting in a probability value of 0.74. However, the site management risk is low, with a 0.32 probability value. This paper assists practitioners in optimizing construction schedules.

Copyright: © 2024 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10773777
  • Published on:
    29/04/2024
  • Last updated on:
    05/06/2024
 
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