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QRAM a Qualitative Occupational Safety Risk Assessment Model for the construction industry that incorporate uncertainties by the use of fuzzy sets Abel Pinto ⇑ Safe@Work, Independent Safety Research Group, Avenida do Mar, no. 30, 5 esq, 2825-476 Costa da Caparica, Portugal a r t i c l e i n f o Article history: Received 16 August 2013 Received in revised form 19 October 2013 Accepted 29 October 2013 Available online 27 November 2013 Keywords: Qualitative risk assessment Construction industry Occupational safety Fuzzy sets Qualitative model a b s t r a c t Occupational safety risk assessment is the core of safety practices. Is a complex process that requires the consideration of sundry parameters, which are often difficult to quantify. This paper presents the new developed fuzzy QRAM model, which intends to support construction companies in carrying out their responsibilities to reduce occupational safety risks. The innovative aspects of QRAM model is to embody assess of the safety climate and the safety barriers effectiveness as assessment dimensions and the use of fuzzy sets theory to enhance the use of imprecise and incomplete information, elicited by linguistic variables. The QRAM model was designed based on the best academic and empirical knowledge about safety risks on construction industry, biomechanical data and laws of physics, chemistry and engineering. The lack of credible and accurate data, resulting from the in-depth investigation of work accidents in construction industry was the greatest difficulty in carry-out this work. QRAM was, firstly evaluated by ‘‘peer’’ review, with 12 safety experts from Brazil (2), Bulgaria (1), Greece (3), Turkey (3) and Portugal (3) and, then, appraised by comparing QRAM with 2 other occupational safety risk assessment techniques. The safety experts evaluators concluded that: (a) QRAM is a versatile tool to assess occupational safety risk assessment on construction sites; ( the specific checklists for knowledge elicitation are a good aid and enhance the process objectivity, and © the use of linguistic variables is a better way to rate the risk factors thus to render the risk assessment process more objective and reliable. 1-s2.0-S092575351300252X-main.pdf