An integrated sugarcane supply chain model : development and demonstration.
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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.