Thesis (B.S.) -- Cagayan State University, 2025.

The fuzzy logic risk assessment model was utilized in this study to identify and rank the key delay factors affecting government-sponsored flood control projects in the 3rd District of Cagayan. Thirty-six risk factors were categorized into seven categories: Client/Owner, Contractor, Consultant, Material, Equipment, Labor, and External-related. Calculation of the Risk Index for Delay (FID) was carried out using a fuzzy inference system that took into account both Probability and Severity Indexes, allowing for the ranking of risk magnitude under heavy uncertainty of expert judgment. The major delay factors identified include weather effects, change orders from the client, insufficient workforce, inadequate manpower and equipment, force majeure events, delays in delivery of materials, low labor productivity, and malfunctioning of equipment. External-related factors are contributing most to delays. The fuzzy modeling approach is shown to be effective in comparison to conventional methods for prioritization of risks and for better decision-making. Recommendations to minimize delays are better project planning, allocation of resources, permitting that involves less time, and inter-agency collaboration. Future works can focus on construction projects of other types and locations, have more expert respondents, and consider applying other fuzzy membership functions or decision-making tools such as AHP, TOPSIS, or PROMETHEE. From the findings of this study, a solid ground is provided in the management of construction delays for timely delivery of infrastructure that safeguards vulnerable communities.

Keywords: fuzzy logic, risk assessment, construction delay, flood control projects