The University of Southampton
University of Southampton Institutional Repository

A hybrid fuzzy system dynamics approach for risk analysis of AUV operations

A hybrid fuzzy system dynamics approach for risk analysis of AUV operations
A hybrid fuzzy system dynamics approach for risk analysis of AUV operations
The maturing of autonomous technology has fostered a rapid expansion in the use of Autonomous Underwater Vehicles (AUVs). To prevent the loss of AUVs during deployments, existing risk analysis approaches tend to focus on technicalities, historical data and experts’ opinion for probability quantification. However, data may not always be available and the complex interrelationships between risk factors are often neglected due to uncertainties. To overcome these shortfalls, a hybrid fuzzy system dynamics risk analysis (FuSDRA) is proposed. The approach utilises the strengths while overcoming limitations of both system dynamics and fuzzy set theory. Presented as a three-step iterative framework, the approach was applied on a case study to examine the impact of crew operating experience on the risk of AUV loss. Results showed not only that initial experience of the team affects the risk of loss, but any loss of experience in earlier stages of the AUV program have a lesser impact as compared to later stages. A series of risk control policies were recommended based on the results. The case study demonstrated how the FuSDRA approach can be applied to inform human resource and risk management strategies, or broader application within the AUV domain and other complex technological systems.
1343-0130
Loh, Tzu Yang
f21489db-1aa9-4cdf-bcb0-ad784a98b2fb
Brito, Mario
82e798e7-e032-4841-992e-81c6f13a9e6c
Bose, Neil
37b8d6e4-fd93-4bbe-827c-f060e0ce0851
Xu, Jingjing
879c88fa-1ef9-4288-8bb8-27479b6274ec
Nikolova, Nataliya
ad9d4e9b-824d-4537-ae27-3ceaaca22598
Tenekedjiev, Kiril
82dd0d80-2ee5-4db2-b04a-654cc703bd47
Loh, Tzu Yang
f21489db-1aa9-4cdf-bcb0-ad784a98b2fb
Brito, Mario
82e798e7-e032-4841-992e-81c6f13a9e6c
Bose, Neil
37b8d6e4-fd93-4bbe-827c-f060e0ce0851
Xu, Jingjing
879c88fa-1ef9-4288-8bb8-27479b6274ec
Nikolova, Nataliya
ad9d4e9b-824d-4537-ae27-3ceaaca22598
Tenekedjiev, Kiril
82dd0d80-2ee5-4db2-b04a-654cc703bd47

Loh, Tzu Yang, Brito, Mario, Bose, Neil, Xu, Jingjing, Nikolova, Nataliya and Tenekedjiev, Kiril (2019) A hybrid fuzzy system dynamics approach for risk analysis of AUV operations. Journal of Advanced Computational Intelligence and Intelligent Informatics. (In Press)

Record type: Article

Abstract

The maturing of autonomous technology has fostered a rapid expansion in the use of Autonomous Underwater Vehicles (AUVs). To prevent the loss of AUVs during deployments, existing risk analysis approaches tend to focus on technicalities, historical data and experts’ opinion for probability quantification. However, data may not always be available and the complex interrelationships between risk factors are often neglected due to uncertainties. To overcome these shortfalls, a hybrid fuzzy system dynamics risk analysis (FuSDRA) is proposed. The approach utilises the strengths while overcoming limitations of both system dynamics and fuzzy set theory. Presented as a three-step iterative framework, the approach was applied on a case study to examine the impact of crew operating experience on the risk of AUV loss. Results showed not only that initial experience of the team affects the risk of loss, but any loss of experience in earlier stages of the AUV program have a lesser impact as compared to later stages. A series of risk control policies were recommended based on the results. The case study demonstrated how the FuSDRA approach can be applied to inform human resource and risk management strategies, or broader application within the AUV domain and other complex technological systems.

Text
JACIII_27Aug_R2_accept_track - Accepted Manuscript
Restricted to Repository staff only until 29 August 2020.
Request a copy

More information

Accepted/In Press date: 29 August 2019

Identifiers

Local EPrints ID: 433810
URI: https://eprints.soton.ac.uk/id/eprint/433810
ISSN: 1343-0130
PURE UUID: 71dc7af9-3658-4c7a-94cd-7d632755dbc6

Catalogue record

Date deposited: 04 Sep 2019 16:30
Last modified: 29 Nov 2019 17:31

Export record

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×