Asset information decision-making framework for the South African navy

Fourie, Christian (2020-03)

Thesis (MEng)--Stellenbosch University, 2020.

Thesis

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.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/107882
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