COMPREHENSIVE RISK MANAGEMENT USING FUZZY FMEA AND MCDA TECHNIQUES IN HIGHWAY CONSTRUCTION PROJECTS

TLDR

The paper proposes a comprehensive framework for managing highway construction project risks, comprising risk identification, fuzzy FMEA‑based prioritization, and response selection, including an expert system for choosing appropriate risk responses. The framework quantifies cost, time, and quality criteria with fuzzy AHP, applies fuzzy FMEA for risk prioritization, and uses a scope‑expected‑deviation index to determine optimal responses, demonstrated on the Bijar‑Zanjan highway project in Iran. The results show that switching from asphalt pavement to RCC pavement successfully mitigated the tar‑price‑increase risk, yielding the smallest deviation.

Abstract

This paper presents a comprehensive framework to manage the main risk events of highway construction pro­jects within three stages: (1) identification of potential risks; (2) assessment and prioritisation of identified risks based on fuzzy FMEA; (3) identification of appropriate response. The main criteria analysed for prioritising potential risk events are cost, time and quality which are quantified and combined using fuzzy AHP. A new expert system is suggested for identifying an appropriate risk response strategy for a risk event based on risk factor, control number and risk alloca­tion. The best response action for a risk event is then identified with respect to the same criteria using “scope expected deviation” (SED) index. The proposed methodology is demonstrated for management of risk events in a construction project of Bijar-Zanjan highway in Iran. For the risk event of “increase in tar price”, deviation from the target values of the criteria is analysed for business-as-usual state plus two risk response actions using SED index. The results show that the response action of “changing paving construction technology from asphalt pavement to RCC pavement” can success­fully cope with the risk event of “increase in tar price” and have the minimum deviation.