The South African sugar industry is a large industry which relies on expensive capital equipment to harvest, transport and process sugarcane. An average of 23 million tons of sugarcane are annually supplied to 14 mills from over 2 000 large-scale commercial growers and 48 000 small-scale growers. Supply chain stakeholders can benefit if operations are successfully streamlined. Computer-based mathematical models have been used in other industries to improve supply chains, especially in forestry, and are expected to play an increasingly important role in future planning and management. Management of sugar supply chains has historically focussed on generating competitive individual supply chain components. However, inter-component optimisation generally disregards many important intra-component interactions. Hence, efficiency improvements may be significantly limited. Integrated supply chain modelling provides a suitable approach for addressing this problem. The aim of this project was to develop and demonstrate, in concept, an integrated supply chain model for the sugar industry. Such a model could be used to address various integrated planning and management problems throughout the supply chain. A review of existing integrated agri-supply chain models was conducted followed by the development of CAPCONN, an integrated sugar supply chain model framework, that incorporate all steps from field to mill back end. CAPCONN estimates sugarcane quality, mill recovery, capacity utilisation and production costs. Bottlenecks are highlighted and the model could contribute towards capacity manipulation for efficiency improvements under different harvesting scenarios. CAPCONN was demonstrated by analysing a number of scenarios in a mechanisation case study at Komati Mill where sugarcane is currently burned and manually cut. A total of twelve scenarios were compared, including variations in cropping system and time of year. The model framework predicted that a decrease in sugarcane quality and sugar recovery would occur under mechanical harvesting scenarios. Estimated production costs were also higher, even though the transport fleet was significantly reduced. A manually cut green (unburned) harvesting scenario showed a further decrease in sugarcane quality and sugar recovery. Mechanical harvesting during wet weather caused a substantial reduction in supply chain capacity and an increase in production costs. CAPCONN output trends compared favourably with measured and observed data, though the magnitude of the trends should be viewed with caution, since the CAPCONN framework is only a prototype. This shows that it may be a suitable diagnostic framework for analysing and investigating the sugarcane supply chain as a single entity. With further development to a model, the CAPCONN model framework could be used as a strategic planning tool although, one drawback is that a relatively large number of technical inputs are required to run the model. / Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2006.

The South African sugar industry ranks eleventh in size out of 200 sugar-producing countries; and continuous advancement is essential to ensure that this industry remains competitive. The transfer system from field to mill, includes sugarcane being moved, loaded, transloaded and off-loaded and amounts to more than 25 % of the total production cost of sugarcane, hence small adjustments can have significant economic benefits. Payload variability is a current problem making the loading operation a leverage point for improvement. As a consequence of poor management and the under-utilisation of equipment, loading has been identified as an inefficient and costly operation. Studies have shown that technology and management can contribute to improved loading accuracy. This study aimed to evaluate loading characteristics in an attempt to develop guidelines for loading. Whole-stick loose sugarcane, which is loaded with grabloaders, is common practice in South Africa and this study aims to improve this loading system. This was achieved by reviewing transfer systems worldwide and synthesising the sugarcane characteristics that drive the designs and the management of equipment and systems within the transfer system. The sugarcane characteristics include the sugarcane bulk density, the length, the diameter and other variety characteristics e.g. the degree of lodging. Other factors, such as the preparation method for loading, the harvesting method and the topography, also have a marked influence on the efficiency of the transfer system. An assessment of typical South African loading practices was undertaken to establish beneficial practices and current operating rules. These factors included the way in which the sugarcane was presented prior to loading, as well as the techniques adopted for loading. The results were used to generate practical recommendations for the improvement of the loading component in order to make the transfer system more efficient. An efficient system comprises a balance of high quality operations with respect to safety, accurate loading, reduced cycle time, optimal fuel usage, reduced roadside losses, reduced sugarcane damage and increased off-loading efficiencies. An investigation into consignment characteristics was also carried out to identify the factors that need to be considered during the loading operation. These factors included the sugarcane bulk density, the degree of sugarcane alignment and the design characteristics of various vehicles. A set of practical guidelines were created from this study. / Thesis (M.Sc.)-University of KwaZulu-Natal, Durban, 2011.

Network theory has been widely and successfully used to model, analyse and visualise complex systems. This study aimed to develop approaches to analyse complex integrated sugarcane supply and processing systems. A literature review includes network theory, complex systems, the Theory of constraints, indicator analysis and root cause analysis. The cause-and-effect networks of four sugarcane milling areas in South Africa; viz. Eston, Felixton, Komati and Umfolozi were developed, where the factors that negatively affected the performance of the milling areas were represented by vertices, the relationships among the factors by arcs and the strength of these relationships by weights. Three network theory based analytical tools namely; (a) primary influence vertex analysis, (b) indicator vertex analysis and (c) root cause vertex analysis were developed to analyse the networks. The results from the analyses indicate variations in the numbers and strengths of primary influence factors, problem indicator factors and root causes of problems between the four milling areas. Rainfall, drought and high soil content in sugarcane were identified as the strongest primary influences in the respective milling areas. High crush rate variability, low cutter productivity, running behind allocation and increases in operating costs were identified as the strongest indicators of poor performance in the respective milling areas. Rainfall was found to be the most dominating root cause of poor performance in all the milling areas. Since the South African integrated sugarcane production and processing system is complex, it is likely that the unique approaches developed in this study can be used successfully to also analyse other relatively complex systems. It is recommended that these approaches be tested within other systems. The main contribution of this study is in the form of a relatively easy-to-use network theory based comprehensive systems analyses tool. This analytical approach has, to the author's knowledge, not been used in any agri-industrial application previously. / Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2013.

Due to the significant cost of transport in the sugar industry, a model, named FastTrack, was developed to investigate infrastructure planning opportunities. The model mathematically incorporates road construction and maintenance costs, terrain and land-use maps, vehicle performance specifications and annual sugarcane volumes to determine the most cost effective route, per vehicle type, from a production region to a mill. Route planning using geographical information systems (GIS) is a standard approach for determining the optimum alignment for pipelines, roads and canals. Theory of this approach was reviewed to create a foundation for the development of FastTrack. A small portion of the Noodsberg sugar mill region in the KwaZulu-Natal midlands was selected as a case study area to test the capabilities of FastTrack. A start location was identified as a natural flow point for 70 000 tons of sugarcane hauled from an area south of the mill. Currently this volume is transported along a 9.3 km stretch of national road from the start location to the sugar mill, while the Euclidean distance is approximately 7 km. Three vehicle types, differing in payload, fuel consumption and road speed were assessed. Two common and currently utilised vehicles, the tractor hilo and interlink combinations, were aligned by FastTrack along existing national roads. A financial penalty for driving on national roads was assumed for the third vehicle type considered, land trains, as these are currently not permitted to operate on national roads in South Africa. This high bulk vehicle was selected to test the capabilities of FastTrack and to identify if cost savings could be realised through increased consignment capacity as has been achieved in Australia, Malawi and Brazil. Utilising the model a new and more direct theoretical route was generated for the land train with a length of 7.4 km. Existing farm roads which would require upgrading made up 34 % of this proposed route. An economic analysis was conducted and showed that under current conditions, the private route generated by FastTrack for land train use, would be the most cost effective, with a system cost of R 57.50 t" . The tractor hilo and interlink had system costs of R 59.58 t" and R 60.98 t"1 respectively. Repeating the economic analysis with projected fuel prices indentified that the cost saving advantage of the land train system over the other two vehicle configurations increases with increasing fuel costs. A rigorous validation process, including a sensitivity analysis of results from FastTrack, revealed that the model performs predictably under a wide range of input conditions and could be a valuable tool for decision making in the sugar industry. However, further research is required to combine more economic and logistical aspects into FastTrack and to increase its usability. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2008.