| Summary: | 碩士 === 國立成功大學 === 航空太空工程學系碩博士班 === 94 === Abstract
Subject: Safety Margin
-Evaluation of the Risk induced by Human Error in Flight
Student: Yu-feng Lin
Advisor: Hung-Sying Jing
A scientific tool, Safety Margin, base on the artificial neural network for evaluation of the risks induced by human errors is proposed in this study. The flight safety margin is an expert system designed to numerically evaluate the perceived consequences caused by human errors. It represents how much room still left for the crew member to operate under the threat from the human error viewing as the suppression of the safe operation margin. That is to say the risk is geometrized as the safety margin. In the field of risk analysis, the key difficulty is in that the risk is a perception problem. Although the possibility of occurrence can be defined precisely, the perceived severity will be different from person to person. In addition to the perception problem, the even more difficult part lies in that the outcome will be different even with the same human error given different situations in which the error occurs, not to say the difficulty of quantification of the human errors. Understanding that situations will be changed to be abnormal with the existence of human error, a group of situation parameters are defined from the SHELL model excluding the livewares. All the situation parameters are used as the inputs of the training examples for the neural network. A questionnaire is designed for the pilots to answer that what kind of performance is needed for the crew to recover from the given situations back to the normal, standard situation. The performance is evaluated from both the physiological and psychological points of view. The results are then converted to the flight safety margin, representing the outputs of the training examples. The corresponding expert system can then be established by using the neural network. The tool has been tested with a real case, meaningful results are obtained although there are still much room for improvement. And it will be evaluated well, if this tool and simulator in one combine.
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