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Assessing Construction Labours’ Safety Level: A Fuzzy MCDM Approach

Author(s):






Medium: journal article
Language(s): English
Published in: Journal of Civil Engineering and Management, , n. 2, v. 26
Page(s): 175-188
DOI: 10.3846/jcem.2020.11926
Abstract:

Risk decision matrix has widely been favoured by the researchers in the area of construction safety risk assessment. Although it provides the construction safety professionals with the final illustration of the risks magnitude, it suffers from major shortcomings, including inability to considering the importance of probability and severity, impaired analysis resulting from the use of raw numbers for ratings, and the limited range of classifications for assessing the risks. All these shortages give an impaired insight to the concerned parties, deteriorating the involved workers’ safety. As such, this paper aims to develop a novel Risk Assessment Model (RAM) through the integration of the Fuzzy Best Worst Method (FBWM) with the Interval-Valued Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (IVFTOPSIS). Based on the application of RAM to a real-life case study, it was observed that the developed RAM contributes to the body of construction safety risk assessment in five unique ways: (1) computing the importance of the two risk parameters (i.e. probability and severity) using fuzzy-reference_based comparisons, (2) obviating the needs for having statistical data, (3) prioritizing the identified risks using the combination of interval-valued triangular fuzzy numbers with TOPSIS, (4) providing the safety analysts with wider ranges of classifications for conducting risk assessment, and (5) providing the safety professionals with appropriate evaluation strategies for controlling the analysed risks. The developed model in the study can be applied to any projects, giving a conclusive plan to the concerned safety professionals for adopting the further prudent mitigation measurements.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.3846/jcem.2020.11926.
  • About this
    data sheet
  • Reference-ID
    10414417
  • Published on:
    26/02/2020
  • Last updated on:
    26/02/2020
 
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