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Generic simulation modelling of stochastic continuous systems

Thesis (PhD (Industrial Engineering))--University of Pretoria, 2004.

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Other Authors: Kruger, P.S. (Paul Stephanus), 1944-
Format: Thesis
Published: University of Pretoria 2013
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access_status_str Open Access
author2 Kruger, P.S. (Paul Stephanus), 1944-
author_browse Kruger, P.S. (Paul Stephanus), 1944-
author_facet Kruger, P.S. (Paul Stephanus), 1944-
collection Thesis
dc_rights_str_mv © 2004, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria
description Thesis (PhD (Industrial Engineering))--University of Pretoria, 2004.
format Thesis
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institution University of Pretoria (South Africa)
last_indexed 2026-06-10T12:39:29.475Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository
publishDate 2013
publishDateRange 2013
publishDateSort 2013
publisher University of Pretoria
publisherStr University of Pretoria
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source_str UPSpace — University of Pretoria Institutional Repository
spelling oai:repository.up.ac.za:2263/24926 Generic simulation modelling of stochastic continuous systems Kruger, P.S. (Paul Stephanus), 1944- Claasen, S.J. (Schalk Johannes) martina@sadi.co.za Albertyn, Martin Iteration time interval Simul8 Arena Event-driven method Fraction-comparison method Stochastic system Continuous system High-level building block Simulation model Generic methodology UCTD Thesis (PhD (Industrial Engineering))--University of Pretoria, 2004. The key objective of this research is to develop a generic simulation modelling methodology that can be used to model stochastic continuous systems effectively. The generic methodology renders simulation models that exhibit the following characteristics: short development and maintenance times, user-friendliness, short simulation runtimes, compact size, robustness, accuracy and a single software application. The research was initiated by the shortcomings of a simulation modelling method that is detailed in a Magister dissertation. A system description of a continuous process plant (referred to as the Synthetic Fuel plant) is developed. The decision support role of simulation modelling is considered and the shortcomings of the original method are analysed. The key objective, importance and limitations of the research are also discussed. The characteristics of stochastic continuous systems are identified and a generic methodology that accommodates these characteristics is conceptualised and developed. It consists of the following eight methods and techniques: the variables technique, the iteration time interval evaluation method, the event-driven evaluation method, the Entity-represent-module method, the Fraction-comparison method, the iterative-loop technique, the time “bottleneck” identification technique and the production lost “bottleneck” identification technique. Five high-level simulation model building blocks are developed. The generic methodology is demonstrated and validated by the development and use of two simulation models. The five high-level building blocks are used to construct identical simulation models of the Synthetic Fuel plant in two different simulation software packages, namely: Arena and Simul8. An iteration time interval and minimum sufficient sample sizes are determined and the simulation models are verified, validated, enhanced and compared. The simulation models are used to evaluate two alternative scenarios. The results of the scenarios are compared and conclusions are presented. The factors that motivated the research, the process that was followed and the generic methodology are summarised. The original method and the generic methodology are compared and the strengths and weaknesses of the generic methodology are discussed. The contribution to knowledge is explained and future developments are proposed. The possible range of application and different usage perspectives are presented. To conclude, the lessons learnt and reinforced are considered. Industrial and Systems Engineering unrestricted 2013-09-06T18:50:00Z 2005-05-24 2013-09-06T18:50:00Z 2004-12-02 2004 2005-05-24 Thesis Albertyn, M 2004, Generic simulation modelling of stochastic continuous systems, PhDs thesis, University of Pretoria, Pretoria, viewed yymmdd < http://upetd.up.ac.za/thesis/available/etd-05242005-112442 / > http://hdl.handle.net/2263/24926 http://upetd.up.ac.za/thesis/available/etd-05242005-112442/ © 2004, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria application/pdf application/pdf application/pdf application/pdf application/pdf application/pdf application/pdf application/pdf application/pdf University of Pretoria
spellingShingle Iteration time interval
Simul8
Arena
Event-driven method
Fraction-comparison method
Stochastic system
Continuous system
High-level building block
Simulation model
Generic methodology
UCTD
Generic simulation modelling of stochastic continuous systems
title Generic simulation modelling of stochastic continuous systems
title_full Generic simulation modelling of stochastic continuous systems
title_fullStr Generic simulation modelling of stochastic continuous systems
title_full_unstemmed Generic simulation modelling of stochastic continuous systems
title_short Generic simulation modelling of stochastic continuous systems
title_sort generic simulation modelling of stochastic continuous systems
topic Iteration time interval
Simul8
Arena
Event-driven method
Fraction-comparison method
Stochastic system
Continuous system
High-level building block
Simulation model
Generic methodology
UCTD
url http://hdl.handle.net/2263/24926
http://upetd.up.ac.za/thesis/available/etd-05242005-112442/