Issues pertaining to cane supply reliability and stockpiling at the Umfolozi sugar mill - model development and application.
The co-owned Umfolozi Mill area has developed as an integrated supply chain. Cane supply reliability was identified as a potential area for productivity improvement at Umfolozi. It is important that the cane supply to a sugar mill arrives at a steady and reliable rate. A reliable cane supply ensures that the mill can operate at an optimum efficiency. Sugarcane supply reliability depends on how the mill area adapts to unforeseeable changes in the supply chain. An important aspect to this is the weather and how it affects the harvesting regimes. The sugarcane supply chain at Umfolozi is divided into two branches, road transport and tram transport. The trams account for 70 % of the cane delivered to the mill and the can is sourced from a climatically homogenous region. In the occurrence of a rainfall event of above 5 mm, infield harvesting cannot take place on the Umfolozi Flats; hence 70 % of the mill‟s supply is halted for one or more days. To address the problem, a stochastic model was created to simulate the effectiveness of an enlarged cane stockpile if it were maintained on the current tram sidings outside the mill and were crushed when wet weather prevented further harvesting. The stockpile was simulated on a first-in first-out principle and was able to supply the mill with enough cane to continue running for 24 hours. The model was then used to conduct a series of Monte Carlo simulations on which sensitivity analyses and economic feasibility assessments were carried out. Results show that the stockpile was effective in reducing the length of milling season and the number of no-cane stops. However, on further analysis into the implications of creating a stockpile it was found that 1% recoverable value (RV) was lost during the 24-hours that the cane is stored outside the mill. The loss in revenue as a result of the RV reduction had a negative impact on any savings created with the implementation of the stockpile. This result made apparent the negative impact of deterioration to the whole supply chain. Further research is required to determine more accurately the rate of deterioration, and therefore, quantify more accurately the losses that occur in the supply chain. A significant outcome of the study was the development of a mechanistic tool which drove decision making at Umfolozi Sugar Mill. It lead to the development of the modelling framework LOMZI, a simulations based framework which places more emphasis on environmental factors and risks.