Occupational safety and health risk assessment during maintenance stage of construction projects: A multi-pronged fuzzy-based approach - Mohandes, Saeed Reza; Karasan, Ali; Gundogdu, Fatma Kutlu; Singh, Atul Kumar; Mahdiyar, Amir; Sabet, Pejman Ghasemi Poor; Zayed, Tarek (PERGAMON-ELSEVIER SCIENCE LTD, 2025)
This study addresses a crucial gap by analyzing the interconnected risk factors in Repair, Maintenance, Alteration, and Additional (RMAA) operations and their collective impact on occupational health and safety-related risks for the first time in the literature. Unlike prior research that examines risks in isolation, this work introduces a unique, multi-layered fuzzy-based framework to explore how these factors interact, amplify risks, and shape overall safety outcomes. The formulated methodology integrates Intuitionistic Fuzzy sets with Decision Making Trial and Evaluation Laboratory (DEMATEL), Cognitive Map, and Order of Preference by Similarity to Ideal Solution (TOPSIS). Based on the application of the developed framework to the selected case studies, the following contributions are noted: (1) it uncovers and maps how risk factors in RMAA operations are interconnected, providing a clear visual of their combined impact on safety; (2) it ranks these factors by calculating their influence on each other, helping identify the most critical areas for safety improvements; and (3) it prioritizes the key risks, offering a solid foundation for targeted safety measures that address the most urgent issues first. By examining both risk factors and their resulting risks as an interconnected system, the research goes beyond standard risk identification. Instead, it meticulously maps out how different factors influence each other, how they collectively escalate risks, and which ones should be prioritized to improve occupational health and safety outcomes.
Keywords: Risk assessment; Construction industry; MCDM; Fuzzy logic; Occupational health and safety; WORKERS; PERFORMANCE; MANAGEMENT; EQUIPMENT; CLIMATE; Computer Science; Engineering; Operations Research & Management Science