Full Text Available

Note: Clicking the button above will open the full text document at the original institutional repository in a new window.

Asset information decision-making framework for the South African navy

Thesis (MEng)--Stellenbosch University, 2020.

Saved in:
Bibliographic Details
Main Author: Fourie, Christian
Other Authors: Jooste, J. L.
Format: Thesis
Language:English
Published: Stellenbosch : Stellenbosch University 2020
Subjects:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1867613846854696960
access_status_str Open Access
author Fourie, Christian
author2 Jooste, J. L.
author_browse Fourie, Christian
Jooste, J. L.
author_facet Jooste, J. L.
Fourie, Christian
author_sort Fourie, Christian
collection Thesis
dc_rights_str_mv Stellenbosch University
description Thesis (MEng)--Stellenbosch University, 2020.
format Thesis
id oai:scholar.sun.ac.za:10019.1/107882
institution Stellenbosch University (South Africa)
language English
last_indexed 2026-06-10T12:42:38.497Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository
publishDate 2020
publishDateRange 2020
publishDateSort 2020
publisher Stellenbosch : Stellenbosch University
publisherStr Stellenbosch : Stellenbosch University
record_format dspace
source_str SUNScholar — Stellenbosch University Repository
spelling oai:scholar.sun.ac.za:10019.1/107882 Asset information decision-making framework for the South African navy Fourie, Christian Jooste, J. L. Stellenbosch University. Faculty of Industrial Engineering. Dept. of Industrial Engineering. Decision making South Africa. Navy -- Inventory control Asset information Asset management UCTD Thesis (MEng)--Stellenbosch University, 2020. ENGLISH ABSTRACT: Asset Information (AI) is essential for effective Asset Management (AM). Decision-makers rely on it for AM decision-making, where productive decisionmaking underpins success in AM. It became apparent that the effect of AI on the output of the mission-performing systems in the SA Navy (SAN) is not defined. Without defining the value of individual AI elements to organisational outputs it is difficult to determine which critical AI elements to acquire and maintain, and which are not beneficial. The purpose of this research is therefore to develop a framework to support decision making regarding AI elements in the SAN. The intention with this framework is to optimise AI in terms of cost effectiveness and support of higher order decision making requiring AI. Operational Availability (AO) is a performance metric that is directly linked to the core outputs of the SAN and falls within the scope of AM. Therefore determining the effect of AI on the AO of the SAN’s systems is at the crux of this research. This framework is developed from two sources in the research, theoretical knowledge and fieldwork. The literature study provides the theoretical base for the thesis as a whole and the Multi-Criteria Decision Making algorithm forms the structure of the framework. Research in the field, making use of experts in the SAN environment provides the content of the framework. Due to the complexity in firstly identifying critical AI elements and secondly determining their value to AO, an exploratory mixed method design is used to collect data. After the first round of data collection a preliminary framework based on Analytical Hierarchy Process and Multi-Attribute Utility Theory (AHP-MAUT) principles are developed. The preliminary framework is used for the second round data collection. Data analysis is carried out using a combination of qualitative and quantitative methods. The final framework is presented in an Excel format (for ease of use) with automated processes that calculates the ranking of AI elements as well as statistical analysis which assists decision makers by offering some suggestions regarding the management of the AI elements. The framework is validated through face validation and user assessment, both via questionnaires posed to an expert panel. According to the expert panel the framework is perceived as 1) useful 2) easy to use 3) practical 4) understandable and 5) flexible. Construct validity is also established, mainly via feedback from the face validation panel. The framework is a baseline version in an unexplored field in the SAN. As part of the conclusion of the thesis is noted that further refinements and validation in the field is required to verify the findings from this thesis. AFRIKAANSE OPSOMMING: Bateinligting (BI) is noodsaaklik vir effektiewe batebestuur. Besluitnemers vertrou daarop vir batebestuur-besluitneming, waar produktiewe besluitneming sukses in batebestuur bekragtig. Dit het duidelik geword dat die effek van BI op die uitset van sisteme wat missies uitvoer in die SA Vloot (SAV) nie gedefinieër is nie. Sonder om die waarde van individuele BI-elemente ten opsigte van organisatoriese uitsette te definieër, is dit moeilik om te bepaal watter kritieke BI-elemente om te bekom en te onderhou, asook watter glad nie voordelig is nie. Die doel van hierdie navorsing is dus om ’n raamwerk te ontwikkel wat besluitneming rakende BI-elemente in die SAV sal ondersteun. Die doel van hierdie raamwerk is om BI te optimaliseer ten opsigte van kosteeffektiwiteit en ter ondersteuning van hoër-orde besluitneming. Operasionele beskikbaarheid is ’n werkverrigting maatstaf wat direk verband hou met die kernuitsette van die SAV, en ook binne bestek van batebestuur val. Die bepaling van die effek van BI op die operasionele beskikbaarheid van SAV stelsels is dus die kern van hierdie navorsing. Hierdie raamwerk word ontwikkel vanuit twee navorsing bronne, teoretiese kennis en veldwerk. Die literatuurstudie bied die teoretiese basis vir die tesis in geheel en die Multi-kriteria Besluitneming algoritme vorm die struktuur van die raamwerk. Die raamwerk se inhoud bestaan uit navorsing ingewin van kundiges in die SAV omgewing. Vanweë die ingewikkeldheid om eerstens kritiese BI-elemente te identifiseer en tweedens die waarde daarvan vir operasionele beskikbaarheid te bepaal, word ’n verkennede ontwerp vir gemengde metodes gebruik om data in te samel. Na die eerste rondte van data-insameling word ’n voorlopige raamwerk, gebaseer op die Analitiese Hiërargie Proses en Multi-kenmerk nutsteorie beginsels ontwikkel. Die voorlopige raamwerk word gebruik vir die tweede rondte van data-insameling. Data-analise word uitgevoer met behulp van ’n kombinasie van kwalitatiewe en kwantitatiewe metodes. Die finale raamwerk word aangebied in ’n Excel-formaat (vir gebruikersgemak) met outomatiese prosesse wat die rangorde van BI-elemente bereken, sowel as statistiese ontleding, wat besluitnemers help deur voorstelle te maak rakende die bestuur van die BI-elemente. Die raamwerk word gevalideer deur middel van gesigsvalidering asook assessering deur gebruikers, beide deur middel van vraelyste wat aan ’n paneel kundiges voorgelê word. Volgens die paneel kundiges word die raamwerk beskou as 1) bruikbaar 2) maklik om te gebruik 3) prakties 4) verstaanbaar en 5) aanpasbaar. Konstruksiegeldigheid word ook vasgestel, hoofsaaklik deur terugvoering van die gesigvalideringspaneel. Die raamwerk is ’n basislyn weergawe in ’n onverkende veld in die SAV. As deel van die afsluiting van hierdie tesis word opgemerk dat verdere verfynings en validering in die veld nodig is om die bevindinge van die tesis ver verifieer. Masters 2020-02-06T11:00:52Z 2020-04-28T12:07:43Z 2020-02-06T11:00:52Z 2020-04-28T12:07:43Z 2020-03 Thesis http://hdl.handle.net/10019.1/107882 en Stellenbosch University xvii, 175 leaves : illustrations (some color) application/pdf Stellenbosch : Stellenbosch University
spellingShingle Decision making
South Africa. Navy -- Inventory control
Asset information
Asset management
UCTD
Fourie, Christian
Asset information decision-making framework for the South African navy
title Asset information decision-making framework for the South African navy
title_full Asset information decision-making framework for the South African navy
title_fullStr Asset information decision-making framework for the South African navy
title_full_unstemmed Asset information decision-making framework for the South African navy
title_short Asset information decision-making framework for the South African navy
title_sort asset information decision making framework for the south african navy
topic Decision making
South Africa. Navy -- Inventory control
Asset information
Asset management
UCTD
url http://hdl.handle.net/10019.1/107882
work_keys_str_mv AT fouriechristian assetinformationdecisionmakingframeworkforthesouthafricannavy