ANALYSING OF MARITIME ACCIDENTS BY APPROACHING METHOD FOR MINIMIZING HUMAN ERROR

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Abstract

This study clarifies the current traffic situation in the Istanbul Strait, TURKEY based on statistical information; 928 data from across 75 years. The main objective is to investigate the risk profile of maritime accidents in the Istanbul Strait, and then to build up a methodology for minimizing human error. Maritime accidents have occurred in spite of existing safeguards. The main reason is that these safeguards do not concern enough the minimizing of human error. Evaluation methods of human behavior are restricted, and it is very difficult to model it among all parameters of the components in a safety system.
The geographical and physical specifications of the Istanbul Strait are investigated and the potential threats defined as the risk profile. Then, proper analysis will be implemented on the resulting statistical information and the factors discussed are called 4M (Man, Machine, Media and Management) both individually and from an aspect of their mutual related effects. The existing safeguards are so evaluated, and their effectiveness is judged through carrying out experimental studies. For this purpose, the Ship Handling Simulator and actual onboard experiences have been utilized. These studies can provide the necessary data for understanding the human factors involved during navigation.
Keywords Maritime Safety; Istanbul Strait; risk assessment; human error; 4M

Safety Assessment Using Fuzzy Theory

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Uncertain input parameters may result from “fuzziness”, “randomness” or “fuzzy randomness”. With the use of fuzzy set theory, uncertain input parameters may be described mathematically as fuzzy variables or fuzzy random variables and may be integrated into safety assessment analysis. With the aid of α-discretization involving the multiple solution of special optimization problems, fuzzy input parameters are mapped onto the uncertain result set. If the deterministic input data are characterized by “fuzziness”, the fuzzy results are uncertain outcomes of the structural analysis; safety assessment may then be carried out using possibility theory. If the input parameters exist in the form of fuzzy random variables, the computed fuzzy failure probabilities may be used for safety assessment. A fuzzy 1st-order reliability method (FFORM) is proposed, which is capable of handling fuzzy as well as fuzzy random variables.

Control System Design Risk Assessment Using Fuzzy Logic

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Introduction

This manual describes a technique that can be used to assess the impact of the flight control system on aircraft configuration geometry. The primary purpose is to perform trade-off studies between different aircraft configurations in the preliminary design phases of development. It can also be easily automated and adapted for use in aircraft configuration optimization problems.
The underlying approach is to determine the control system structure that is needed to correct deficiencies in the dynamics of the aircraft. The complexity of the control system is assumed to measure the amount of risk associated with that aircraft (if it were built). Configurations that require a very simple control system architecture would incur only a small risk. Configurations with a very complicated control system would be assigned a higher risk.
The required control system architecture is determined using a set of fuzzy logic rules. These rules are developed using experience and knowledge about how control systems are designed. Using this approach, a control system is not actually designed for a given configuration under study. Only the required control system structure is determined. The final design of the control system would come after the final configuration has been selected and detailed aerodynamic and structural models are developed.
This report describes a procedure and rule base to determine the flight control design risk for the longitudinal axis of aircraft motion. Only one specification regarding aircraft flying qualities is considered. However, the rules and methods described in this report could also be expanded to include other design requirements and specifications.

Evaluation Of The Wildfire Ignition Risk By The Aid Of Fuzzy Logic

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The danger of destructive wildfires has become a major issue in the U.S. due to decades of fuel accumulation from fire suppression efforts. With more people moving closer to or living in the wildland-urban interface, the risk of wildfires has increased dramatically. Wildfire risk analysis is aiming at predicting when and where wildfires will likely occur, and measures can be taken in advance to reduce the number and the intensity of disasters. In general, wildfire risk analysis can be divided into ignition risk analysis and fire behavior risk analysis. This study focuses on an ignition fire risk analysis in Rabun County, Georgia. Four fire risk related factors — human activity, illumination, elevation and vegetation type — were derived from spatial datasets. Three of them were used as linguistic variables, and then fuzzy set theory and fuzzy inference were applied to these variables to model wildfire risk levels (low, possible, substantial and high). The final result is a thematic risk level map that suggests that fuzzy logic can be used as a powerful tool in the field of fire risk analysis to predict more interpretable risk levels for a certain area. Some advantages and disadvantages of using fuzzy logic over traditional approaches were also discussed in the paper.

MODUL TAHANAN KAPAL - SHIP RESISTANCE

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TAHANAN KAPAL - SHIP RESISTANCE

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

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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 difficult 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 flexible. 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, deficiencies, near misses, skill, level of education and training, technical failures, company policy/culture, etc.

Risk Assessment of Fishing Vessels

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The work described in this paper is concerned with the systematic analysis of the hazards of fishing vessels. Statistical data is reviewed and analyzed and fault tree analysis is applied to find the relative importance of each component with respect to system reliability. In this analysis, the loss of vessel is chosen as the top event, then branching out to the basic events such as human error, structural failure, fish on deck etc. This method is considered an essential approach for providing a much better basis for safety decision making.
Finally, in order to reduce the accidents to vessels and crew, some suggestions are made to reduce the probability of human error to improve the stability and safety of vessels.
Key Words: Fishing Vessels, Risk Assessment, Fault Tree, Human Error