Masters Degrees (Logistics)

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Browsing Masters Degrees (Logistics) by browse.metadata.advisor "Havenga, Jan"

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    Ensuring sufficient capacity of logistical infrastructure for future growth
    (Stellenbosch : Stellenbosch University, 2014-04) Gebhardt, Albertus Johannes; Havenga, Jan; Stellenbosch University. Faculty of Economics and Management Sciences. Dept. of Logistics.
    ENGLISH ABSTRACT: This study explore how forecasting techniques can be combined in linear programming (LP) as a tool to optimise the parameters of forecasting methods in order to ensure sufficient capacity of logistic infrastructure exist for future growth. This study will use greenfield and brownfield projects from Sasol, a petrochemical company from South Africa, to test the methodology on. The methodology followed in the study was to firstly look at previous literature studies on logistical infrastructure and how to create sufficient capacity. Secondly, understandings of supply chain planning principles in general as well as supply chain planning in context of Sasol were investigated. Thirdly, different forecasting methods like; qualitative include judgemental, life cycle, Delphi method, market research etc. and quantitative methods including time series and causal methodologies had been investigated. Fourthly, decision making tools to incorporate multiple forecasts were investigated to understand why Sasol decided to use i2. Fifthly, the current capital project approach in Sasol had been investigated to fully understand where room for improvements would be possible. Finally the theory from the study was applied on two different projects in Sasol, one greenfield and one brownfield project. The results found that by using sound supply chain planning methodologies, sound supply chain design principles and multiple forecasts being combined by using LP decision making tools a better decision can be made with regards to logistical infrastructure investment as well as ensuring sufficient logistical infrastructure capacity. The two case studies have shown that this approach is flexible enough, apart from a few minor changes and can be adopted for both scenarios and that great results can be achieved. Logistical infrastructure could be optimised due to collaboration and the overall costs and performance of a supply chain improved.