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Human Reliability assessment in oil tanker operations

Subramaniam, K (2010) Human Reliability assessment in oil tanker operations. Doctoral thesis, Liverpool John Moores University.

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Abstract

This research is carried out to improve Human Reliability Analysis (HRA) in oil tanker operations in general, to extend and enhance in specific Cognitive Reliability and Error Analysis Method (CREAM), with the aim of reducing human error and thus subsequently preventing oil tanker spills. It is concentrated on oil tanker operations to address the limitation of availability of human reliability data in the maritime domain. The continual occurrence of oil tanker spills, which was substantiated with analysis of historical data of oil tanker incidents/accidents from 1970 to 2008, provides a judicious reason to conduct this research. The critical review of Formal Safety Assessment (FSA) and HRA results in the development of a conceptual framework of HRA facilitating FSA and incorporating Human Organisational Factors (HOF), which addresses the shortcomings of the generic HRA and FSA methodologies that exist independently in the management of oil tankers to prevent oil spills. The CREAM is reviewed due to its prominent use in identifying the root causes of human error. However, its inability of providing solutions to an incident/accident investigation and robust quantification of human reliability features stimulates the development of an advanced CREAM and a human reliability quantification model using a combined Analytic Hierarchical Process (AHP) and fuzzy logic approach in this research. In addition to facilitating identification of the root causes of human error, the advanced CREAM also provides the solutions to a quantification model, which enables the development of HRA data in the maritime domain. Furthermore, lack of CREAM studies on relationships among Common Performance Conditions (CPCs) is addressed by proposing a Decision Making Trial and Evaluation Laboratory (DEMATEL) model, which allows for a comprehensive understanding of relationships and interdependencies among the CPCs. The model could also be used toappreciate and assimilate the relationships and interdependencies among human factor variables involved in other transportation systems and industrial fields. Finally, the research is concluded with an integrated AHP and fuzzy Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) model for determining the selection of an appropriate risk control option (RCO) while performing an incident/accident investigation by taking subjective judgments of decision makers into consideration. This research as a pioneer work in developing and applying advanced techniques to improve the generic CREAM in oil tanker operations establishes a foundation for future effort to improve the use of CREAM in other industries. The techniques developed can also be tailored to investigate and deal with an incident/accident effectively, resulting in the reduction of human error within the system management of any organisation

Item Type: Thesis (Doctoral)
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD61 Risk Management
T Technology > TC Hydraulic engineering. Ocean engineering
Divisions: Maritime and Mechanical Engineering
Date Deposited: 16 Mar 2017 11:03
Last Modified: 16 Mar 2017 11:03
URI: http://researchonline.ljmu.ac.uk/id/eprint/5968

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