The quantitative risk of oil tanker groundings
By:  Michael D. Amrozowicz
Publisher: Available from National Technical Information Service
Published: 1996
Place of publication: Springfield, Va
Language: eng
Number of pages: 114
Description: The culture, design, and operation of the maritime industry all contribute to create an error-inducing system. As      oil tankers have become larger, the tolerance for error has decreased as the consequences have increased.      Tankers are the largest contributor by vessel type to worldwide oil spill volume. Human error has consistently      been attributed to 80 percent of the marine accidents. A closer look reveals that many accidents attributed to      human error are system errors. In fact, the term human error is unwarranted in many high-risk accidents and its      use is a perforation of the context. The maritime industry has been identified as a high risk operation, requiring      an active risk management program. A probabilistic risk assessment (PRA) provides a formal process of      determining the full range of possible adverse occurrences, probabilities, and expected costs for any undesirable      event. A PRA can identify those areas that offer the greatest risk-reducing potential. This thesis focuses on the      first level of a proposed three-level risk model to determine the probability of a tanker grounding. The approach      utilizes fault trees and event trees and incorporates The Human Error Rate Prediction data to quantify individual      errors. The result allows the identification of high-leverage factors in order to determine the most effective and      efficient use of resources to reduce the probability of grounding; showing that the development of the Electronic      Chart Display and Information System incorporated with the International Safety Management Code can      significantly reduce the probability of grounding.
Notes: Theses advisor(S): Michael W, Golay, Alan J. Brown.

Thesis (Degrees of Naval Engineer and M.S. in Ocean Systems Management) Massachusetts Institute  of Technology, June 1996.

Bibliography: leaves 119-124.

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