Fuzzy logic system approach for quantifying risk associated with the installation of trenchless technologies

摘要

Any trenchless installation project is associated with some level of risk. Conventional risk assessment approach quantifies risk as a product of likelihood and severity of risk, and does not consider the interrelation among different risk input variables. However, in real life installation projects the input factors are interconnected, somewhat overlapped, and exist with fuzziness or vagueness. Fuzzy logic system surpasses this shortcoming and delivers the output through a process of fuzzification, fuzzy inference, fuzzy rules, and defuzzification. In this study, site condition, geological condition, installing geometry (IG), project contract, and trenchless method are addressed as input variables that cause significant risk in the installation of trenchless technologies. It is assumed that input variables are trapezoidal and output variables are triangular fuzzy membership functions. Furthermore, input members are classified as poor, average, and good; whereas, output members are classified as low, medium, and high risk. The fuzzy rules governing the input-output relationship are if-and-then as well as if-or-then. The resulting risk score is observed on a scale of 0 to 7. It is found that the risk score/ranking decreases while the input variables gradually proceed from poor to good. Thus, this paper proposes a novel approach towards the analysis and assessment of risk associated with the installation of trenchless technologies using a fuzzy logic system model.