Abstract
Managing uncertainty in risk assessment is a crucial issue for better decision making and especially when it is adapted to the three standards ISO 9001, OHSAS 18001 and ISO 14001. This paper proposes a new risk assessment approach able to manage risk in the context of integrated management system (IMS-QSE) while taking into account the uncertainty characterizing the whole process. The proposed approach is mainly based on fuzzy set theory and Monte Carlo simulation to provide an appropriate risk estimation values and adequate decisions regarding the three management systems Quality, Security and Environment. In order to show the effectiveness of our approach, we have performed simulations on real database in the petroleum field at TOTAL TUNISIA company.
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© 2015 Springer International Publishing Switzerland
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Ben Aissia, M., Badereddine, A., Amor, N.B. (2015). Uncertainty Management in Multi-leveled Risk Assessment: Context of IMS-QSE. In: Ali, M., Kwon, Y., Lee, CH., Kim, J., Kim, Y. (eds) Current Approaches in Applied Artificial Intelligence. IEA/AIE 2015. Lecture Notes in Computer Science(), vol 9101. Springer, Cham. https://doi.org/10.1007/978-3-319-19066-2_1
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DOI: https://doi.org/10.1007/978-3-319-19066-2_1
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