| Summary: | This thesis is based on an industry project with Teekay Shipping Co ., which is an international transportation service provider for oil companies, refiners and traders. Teekay is interested in knowing which factors contribute most to its operating incidents and accidents. Based on available data, namely vessel name, team, type, hull, and age, as well as incident and accident records, we quantified in this thesis the effects of these factors on the incident and accident frequency. The thesis presented the technical details of the Poisson regression analysis, which we used for quantifying the risk factors. Teekay is also interested in having a consistent method to present Teekay's overall risk picture, and to indicate best investment areas for its risk reducing purpose. Teekay has already implemented an Online Root Cause Analyses (ORCA) system, which collects the direct cause and root cause soon after an incident happens. We reviewed the ORCA system and made suggestions about certain parts of the system which were subsequently revised. Furthermore, we designed a bubble chart tool to present the overall risk faced by Teekay. The bubble chart tool has the capacity to indicate best investment areas clearly, and it is consistent over time, thereby enabling Teekay to evaluate easily the risk mitigation effect of its earlier investment in risk management. Finally, we designed a continuous monitoring tool, which allows Teekay managers to interactively explore the relationships among near misses, incidents and accidents, and to compare event frequencies of various vessel groups, such as vessel team, age, type and hull structure. The powerful continuous monitoring tool provides Teekay managers a full- range view of the risks the company faces. The design and the sample usage of this continuous monitoring tool are discussed in this thesis. Business, Sauder School of Graduate
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