The University of Southampton
University of Southampton Institutional Repository

Approaches to modeling the gas-turbine maintenance process

Approaches to modeling the gas-turbine maintenance process
Approaches to modeling the gas-turbine maintenance process
Discrete-event modeling has long been used for logistics and scheduling problems, while multi--agent modelling closely matches human decision-making process. In this paper a metric-based comparison between the traditional discrete-event and the emerging agent-based modeling approaches is reported. The case study involved the implementation of two functionally identical models based on a realistic, non-trivial, civil aircraft gas turbine global repair operation. The size, structural complexity, and coupling metrics from the two models were used to gauge the benefits and drawbacks of each modeling paradigm. The agent-based model was significantly better than the discrete-event model in terms of execution times, scalability, understandability, modifiability, and structural flexibility. In contrast, and importantly in an engineering context, the discrete-event model guaranteed predictable and repeatable results and was comparatively easy to test because of its single-threaded operation. However, neither modeling approach on its own possesses all these characteristics nor can each handle the wide range of resolutions and scales frequently encountered in problems exemplified by the case study scenario. It is recognized that agent-based modeling can emulate high-level human decision-making and communication closely while discrete-event modeling provides a good fit for low-level sequential processes such as those found in manufacturing and logistics.
1530-9827
011007-[9pp]
Yu, Tai-Tuck
13211fd2-7998-4376-8396-2ba9e61a7ef8
Scanlan, James P.
7ad738f2-d732-423f-a322-31fa4695529d
Crowder, Richard M.
ddeb646d-cc9e-487b-bd84-e1726d3ac023
Wills, Gary B.
3a594558-6921-4e82-8098-38cd8d4e8aa0
Yu, Tai-Tuck
13211fd2-7998-4376-8396-2ba9e61a7ef8
Scanlan, James P.
7ad738f2-d732-423f-a322-31fa4695529d
Crowder, Richard M.
ddeb646d-cc9e-487b-bd84-e1726d3ac023
Wills, Gary B.
3a594558-6921-4e82-8098-38cd8d4e8aa0

Yu, Tai-Tuck, Scanlan, James P., Crowder, Richard M. and Wills, Gary B. (2012) Approaches to modeling the gas-turbine maintenance process. Journal of Computing and Information Science in Engineering, 12 (1), 011007-[9pp]. (doi:10.1115/1.3647876).

Record type: Article

Abstract

Discrete-event modeling has long been used for logistics and scheduling problems, while multi--agent modelling closely matches human decision-making process. In this paper a metric-based comparison between the traditional discrete-event and the emerging agent-based modeling approaches is reported. The case study involved the implementation of two functionally identical models based on a realistic, non-trivial, civil aircraft gas turbine global repair operation. The size, structural complexity, and coupling metrics from the two models were used to gauge the benefits and drawbacks of each modeling paradigm. The agent-based model was significantly better than the discrete-event model in terms of execution times, scalability, understandability, modifiability, and structural flexibility. In contrast, and importantly in an engineering context, the discrete-event model guaranteed predictable and repeatable results and was comparatively easy to test because of its single-threaded operation. However, neither modeling approach on its own possesses all these characteristics nor can each handle the wide range of resolutions and scales frequently encountered in problems exemplified by the case study scenario. It is recognized that agent-based modeling can emulate high-level human decision-making and communication closely while discrete-event modeling provides a good fit for low-level sequential processes such as those found in manufacturing and logistics.

Text
JCISE-2010-123_Approaches_to_modeling_the_gas__Crowder.pdf - Other
Download (409kB)
Text
272547WILLS11.pdf - Other
Restricted to Repository staff only
Request a copy

More information

e-pub ahead of print date: 21 December 2011
Published date: 1 March 2012
Organisations: Agents, Interactions & Complexity, Electronic & Software Systems

Identifiers

Local EPrints ID: 272547
URI: http://eprints.soton.ac.uk/id/eprint/272547
ISSN: 1530-9827
PURE UUID: 9a35fca3-51b6-46e2-8468-b31d1270c8ef
ORCID for Gary B. Wills: ORCID iD orcid.org/0000-0001-5771-4088

Catalogue record

Date deposited: 07 Jul 2011 17:42
Last modified: 07 Oct 2020 05:36

Export record

Altmetrics

Contributors

Author: Tai-Tuck Yu
Author: Richard M. Crowder
Author: Gary B. Wills ORCID iD

University divisions

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 http://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.

×