Volume 26, Number 4 (IJIEPR 2015)                   IJIEPR 2015, 26(4): 229-241 | Back to browse issues page



DOI: 10.22068/ijiepr.26.4.229

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Zare Mehrjerdi Y, Haqiqat E. Developing a conceptual model based upon the Latin Hypercube Sampling for integrating OHS into project risk evaluation. IJIEPR. 2015; 26 (4) :229-241
URL: http://ijiepr.iust.ac.ir/article-1-523-en.html

Associate Professor Yazd University , yazm2000@yahoo.com
Abstract:   (1345 Views)

Abstract Project management in construction industry, in many cases, is imperfect with respect to the integration of Occupational Health and Safety (OHS) risks. This imperfection exhibits itself as complications affecting the riskiness of industrial procedures and is illustrated usually by poor awareness of OHS within project teams. Difficulties on OHS regularly came about in the construction industry. The integration of OHS risk is not systematic in construction areas in spite of progressing laws and management systems. As project safety and risk evaluation in construction industry is an important issue, thus, the way on doing evaluation and liability of estimation is necessary. In this paper, we propose a new systematic approach based on Latin Hypercube Sampling (LHS) for integrating occupational health and safety into project risk evaluation. This approach tries to identify and evaluate reinforcement effects in a systematic approach for integrating OHS risks into project risk assessment. Furthermore, the proposed method allows evaluating and comparing OHS risks before and after the mitigation plan. A case study is used to prove the workability, credibility of the risk evaluation approach and uncomplicated integration of OHS risks at a construction project. This approach enables continual revaluation of criteria over the direction of the project or when new information is obtained. This model enables the decision makers such as project managers to integrate OHS risks toward schedule plan and compare them before and after the mitigation plan. The mentioned model is found to be useful for predicting OHS risks in construction industries and thus avoiding accidents over the path of the project.

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Type of Study: Research | Subject: Engineering Economics
Received: 2013/05/6 | Accepted: 2013/11/23 | Published: 2016/03/16

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