Annual General Assembly 2004 - Tasmania

Session 5A

Fuzzy Inference As An Approach To Safety Management System (SMS) Analysis

Vladimir A. Loginovsky
Admiral Makarov State Maritime Academy
5, Zanevsky pr., St. Petersburg, 195 112, Russia
lva@sma.spb.ru vl.loginovsky@rambler.ru

ABSTRACT

Safety analysis is one of the major areas of Ship Management company activity that frequently comes face to face with a nontraditional problem of "measurements of safety". The question arises of how to estimate or measure the safety level? There is no doubt that, post-accident, a priori statistical analyses or Formal Safety Assessment are not effective instruments to apply in a real-time interval, especially in emergencies. The majority of problems are directly linked with the human factor, which is very diffi cult to formalize.

The safety analyses generally serve as decision aids. Wise decisions are essential in any safety program. Human decisions depend on numerous factors that transcend requirements and physical response, and many of these can be captured mathematically using fuzzy logic. Fuzzy logic is conceptually easy to understand in SMS applications. It is fl exible. With any given SMS it's easy to massage or layer more functionality on top of it without starting again from scratch, for example: to incorporate ISPS Code procedures into the already working SMS. Fuzzy logic is tolerant of imprecise data and there is a lot of such data in shipping. Fuzzy logic can model nonlinear functions of arbitrary complexity. Fuzzy logic can be built on top of the experience of maritime safety experts and it can be blended with conventional control techniques. The most impressive feature is that fuzzy logic is based on natural language.

The paper highlights some problems mentioned above and contains the research findings on evaluation of technical and human factor impact on safety at sea using fuzzy logic approach and applying such factors (linguistic variables) as safety, fatigue, OOW distractions, defi ciencies, near misses, skill, level of education and training, technical failures, company policy/culture, etc.

Back to Session Index