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A fuzzy logic approach to model delays in construction projects

Al-Humaidi, Hanouf M.
http://rave.ohiolink.edu/etdc/view?acc_num=osu1185539202

Abstract Details

2007, Doctor of Philosophy, Ohio State University, Civil Engineering.
Delays in construction projects are inevitable; as a result claims and disputes arise among different construction parties. Different causes of delay can come into play, therefore, there is a need to identify and classify different causes of project delay. Estimation of the likelihood of delay resulting from different factors that contribute to project delay is essential to project success. Different factors that contribute to project delay affect the likelihood of project delay in different effectiveness degrees. There is a pressing need to estimate the likelihood of delay by implementing analysis methods and examining these methods. Probabilistic fault tree analysis and fuzzy fault tree analysis are two methods suggested by this research to estimate the likelihood of delay. Fuzzy fault tree analysis is performed by planners and managers since they select the delay causes that are applicable to a given project and categorize these delay causes into enabling, triggering, and procedural causes. Then, managers assess the degree of effectiveness of each cause of delay to overall project delay. Assessment of the contributing causes of delay and their degree of effectiveness on project delay uses subjective judgment linguistic terms. The result of the fuzzy fault tree analysis is a likelihood of delay membership function that is compared to the predefined fuzzy logic model to assess the degree of severity of the likelihood of delay. Likelihood of delay membership function is further quantified using the weighted average defuzzification method. Different fuzzy logic models are implemented into the fuzzy fault tree analysis, using Visual Basic software, these models are Baldwin’s rotational model, the Angular model, the Translational model and the Triangular model. Recommendation of the fuzzy logic model that is best applied to a given scenario needs further sensitivity analysis and is beyond the scope of this research. Validation of the fuzzy fault tree analysis computer model is performed. Some suggestions by experts are implemented into the computer model while other suggestions are deferred to future research. The computer software suggested by this study is an attempt to help reduce delays in construction projects that can cause time loss.
Fabian Tan (Advisor)
224 p.
Engineering, Civil
Fuzzy Logic; Likelihood of Project Delay; Fuzzy Fault Tree Analysis; Fuzzy Logic Models; Translational Fuzzy Logic Model; Rotational Fuzzy Logic Model; Triangular Fuzzy Logic Model; Angular Fuzzy Logic Model; Delays in Projects

Recommended Citations

Citations

  • Al-Humaidi, H. M. (2007). A fuzzy logic approach to model delays in construction projects [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1185539202

    APA Style (7th edition)

  • Al-Humaidi, Hanouf. A fuzzy logic approach to model delays in construction projects. 2007. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1185539202.

    MLA Style (8th edition)

  • Al-Humaidi, Hanouf. "A fuzzy logic approach to model delays in construction projects." Doctoral dissertation, Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=osu1185539202

    Chicago Manual of Style (17th edition)

osu1185539202
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© 2007, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.