Faculty of Engineering & IT (Theses and Dissertations)

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Browsing Faculty of Engineering & IT (Theses and Dissertations) by Author "ABU SERDANEH, AFNAN"

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    Implementing Fuzzy Analytical Hierarchy Process and Similarity Approach to Predict Health and Safety Incidents in Dubai Construction Projects
    (The British University in Dubai (BUiD), 2022-03) ABU SERDANEH, AFNAN
    With the benefit of improving and developing the construction business in the UAE, a smart and resilient system has been generated. The construction sector contributes 7.4% of Dubai’s GDP and is highly exposed to hazards and uncertain events. Various types of risks can be obtained from the construction sites. Therefore, it is essential to explore and study strategies, logical methods and processes that save lives, increase profitability, reduce time, and enhance quality. The chosen case studies of this research study are three innovative buildings established to attract residents and visitors to live in. The selected projects are related to the residential sub-community sector. Although the implementation of these projects was initiated and processed at high standards, unfavourable events occurred during the construction phase. The developed MATLAB program is created to conduct the assessment method of the construction risks. The mathematical techniques utilised in the program are multi-criteria decision matrix, fuzzy analytic hierarchy process and similarity TOPSIS. The selected attributes which are used for the assessment are risks probability, health and safety severity, time delay, cost increment and productivity reduction. Besides, in order to promote accuracy and precision of output data, experts’ decisions must be taken into consideration regarding the attributes ranking and hazards rating. Furthermore, three different ideal solutions criteria will be examined to select the most appropriate results. By assessing and ranking the previous data of risks, project stakeholders will be able to predict future risks and apply mitigation responses prior to events occurrence. This research will propose mitigation plans to overcome uncertain events and reduce errors during the construction of projects.
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