Failure mode and effects analysis

Engineering

Reliability engineering

Materials science

Leak

Computer security

Probabilistic logic

Risk assessment

Data mining

Computer science

Risk analysis (engineering)

Failure mode, effects, and criticality analysis

Matrix (chemical analysis)

Environmental engineering

Operations research

Probabilistic risk assessment

Artificial intelligence

Composite material

Medicine

Fault tree analysis

Journal of Loss Prevention in the Process Industries

The work presented in this paper used a quantitative analysis of relevant risks through the development of fault tree analysis and risk analysis methods to aid real time risk prediction and safety evaluation of leak in a storage tank. Criticality of risk elements and their attributes can be used with real time data to predict potential failures likely to occur. As an example, a risk matrix was used to rank risk of events that could lead to a leak in a storage tank and to make decisions on risks to be allowed based on past statistical data. An intelligent system that recognizes increasing level(s) and draws awareness to the possibility of additional increase before unsafe levels are attained was used to analyse and make critical decisions. After a visual depiction of relationships between hazards and controls had been actualized, dynamic risk modelling was used to quantify the effect controls can potentially have on hazards by applying historical and real-time data into a probabilistic model. The output of a dynamic risk model is near real-time quantitative predictions of risk likelihood. Results from the risk matrix analysis method mixed with RTD and FTA were analyzed, evaluated, and compared.

Safety evaluation of leak in a storage tank using fault tree analysis and risk matrix analysis