Asset Risk Criticality Analysis of Process Operations Using Fuzzy Logic

Asset risk mitigation is important especially for the offshore industries like refineries and petrochemical industries to reduce the accident rate as well as the operation cost. Though there are many existing methods which can be used to identify the asset risk level, most of the approaches do not consider the uncertainties involved in the process operations. Therefore, this work aims to model the asset risk using traditional Risk Based Maintenance (RBM) method and fuzzy RBM as it is a very effective tool to incorporate the uncertainties in the system. A case study has been performed in a crude oil refinery. Both models have been developed considering several factors like maintenance cost, operational impact and flexibility, safety and environmental impact for the failures of an asset and the unit has been found as non-critical in both approaches. A Fuzzy risk matrix has been developed describing the transitional conditions from one criticality level to another criticality level whereas two different risk matrixes are required for the traditional method without presenting any transition. The proposed model can be used to prioritize the assets according to their risk value which enables to prepare the precedence list for taking action.