Risk Identification and Assessment in 24x7 Water Supply Scheme for DMA under Smart City project

Abstract

Abstract: The objective of this thesis is to propose a decision support tool for contractors to assess the likelihood of risks in water supply system projects before the execution stage. The approach combines fuzzy logic with the relative importance index (RII) method to quantify the probability of these risks. By conducting a comprehensive literature review and expert interviews, a total of 51 distinct risk factors were identified and categorized into seven groups. The RII method was employed to determine the relative importance of each risk factor, and the ranking of both the factors and groups was established based on their level of importance. The case study results facilitated a discussion on the most influential factors and groups that require attention in terms of risk probability. The outcomes were deemed satisfactory and appropriate for the purpose of this thesis.