A Fuzzy AHP-based Decision Support Model for Quantifying Failure Risk of Excavation Work

Abstract

In recent years, excavation work of high-rise buildings has been becoming increasingly complex in the congested urban areas and frequently exposed to substantial hazards, impediment to safety as well as financial loses. For these reasons, advanced sensor-based systems have been used to accurately monitor and diagnose the failure risk of an excavation work; however, it is often tricky to anticipate and assess the impacts of changeable variables, such as human factors, site conditions, material loadings, and mobile equipment, because of the lack of proper tools to explain the unforeseen phenomena. This study proposed a decision support model to concretize effectively experts' and practitioners' subjectivities and to quantify the failure risk. The model is fundamentally constructed on fuzzy analytic hierarchy process, which weights the environmental influences that can derive a failure. The outcomes are used as an input for fuzzy comprehensive operations to compute the quantitative failure risk. Three illustrative cases have been examined to explain the capabilities of the proposed model. The results have shown the possibility that the model can be helpful for developing safety precautions with a warning signal during the planning and controlling stages of a new or ongoing excavation work.