ESTIMATING MATERIAL WASTE IN THE BUILDING CONSTRUCTION INDUSTRY USING ARTIFICIAL INTELLIGENCE

Abstract

This thesis presents an in-depth pioneer study on the incidence of materials waste in the Egyptian Construction Industry. The study aims to adopt a waste Identification/ Reduction strategy that would aid the decision maker to rethink ways of minimizing the amount of waste in materials in order to minimize the overall cost of the project. The study addresses a theoretical contribution discussed in phase 1, and a practical contribution developed in phase 2. Phase 1 provides the average percentage of materials waste and the dominant causes of waste generation as reported by the respondents using a questionnaire. Phase 2 uses these data as a basis to develop a decision support tool called EWACS for estimating the percentage of waste in cement and reinforcing steel as well as providing recommendations to minimize the amounts of waste in the early stage of the project life cycle.