• Login
    View Item 
    •   ResearchSpace Home
    • College of Agriculture, Engineering and Science
    • School of Engineering
    • Agricultural Engineering
    • Masters Degrees (Agricultural Engineering)
    • View Item
    •   ResearchSpace Home
    • College of Agriculture, Engineering and Science
    • School of Engineering
    • Agricultural Engineering
    • Masters Degrees (Agricultural Engineering)
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Modelling sugarcane quality in the context of mill scale supply chain logistics.

    Thumbnail
    View/Open
    Thesis. (1.475Mb)
    Date
    2014
    Author
    Jenkins, Edwin Peter Garland.
    Metadata
    Show full item record
    Abstract
    The length of milling season (LOMS) refers to the length and timing of sugarcane crushing operations at a sugar mill. LOMS is central to the competitiveness and profitability of any sugar mill supply area (MSA). Conflicting interests between supply chain stakeholders can make adjusting the LOMS difficult. The LOMS should take into account weather conditions, cane quality, milling capacity, supply chain capabilities and other interrelated issues, such as agronomics. Previous LOMS models in South Africa were developed over a decade ago and there was scope to improve the calculation of risks by using a stochastic modelling approach. Recently, a stochastic model named LOMZI was developed to evaluate stockpiling options at Umfolozi. In this study, LOMZI was adapted and expanded to allow the LOMS for any MSA in South Africa to be investigated. However, mill area specific applications of the updated model fell outside the scope of this study. As it currently stands, LOMZI simulates a sugarcane supply chain from the point where sugarcane is cut, up to delivery at the mill. During the process of adapting LOMZI, the simulation of sugarcane quality was identified as an important area for improvement in the model and this became the focus of the study. A predictive MSA scale cane quality model was developed, based on recent weather conditions and a mechanistic understanding of sugarcane quality. The quality model was developed to simulate the daily average brix %, pol % and fibre % of sugarcane delivered to the mill. The preceding 11 weeks’ rainfall and temperature values were used to predict cane quality. A total of 98 mill-specific coefficients were calibrated from historic milling data and, for model demonstration purposes, the quality model was applied at two mills, namely Sezela and Umfolozi. Independent verifications yielded R2 values between 0.56 and 0.74. A useful method to estimate the average burn/cut to crush delay for a MSA was also identified. The quality model has been successfully integrated with LOMZI. Future work is envisaged to expand LOMZI and to model the operations of sugar mills and the RV cane payment system.
    URI
    http://hdl.handle.net/10413/12542
    Collections
    • Masters Degrees (Agricultural Engineering) [30]

    Related items

    Showing items related by title, author, creator and subject.

    • The development and evaluation of a community-based programme offering psychosocial support to vulnerable children affected by HIV/AIDS, poverty and violence. 

      Killian, Beverley Janet. (2004)
      This research programme endeavours to develop, implement and evaluate an effective method of offering psychosocial support to vulnerable children. Vulnerability is defined by trained community members as including children ...
    • The state of spatial information for land reform in South Africa : a case study of the Amantungwa Land Reform project. 

      Kubheka, Sipho. (2006)
      Many authors and practitioners involved in rural or local development agree that co-operation and the integration of efforts by the delivery agents is crucial for sustainable development programmes. The delivery of Land ...
    • Loan products to manage liquidity stress when broad-based black economic empowerment (BEE) enterprises invest in productive assets. 

      Finnemore, Gareth Robert Lionel. (2005)
      Investments in productive assets by broad-based black economic empowerment (BEE) enterprises in South Africa (SA) during the 1990s have been constrained, in part, by a lack of access to capital. Even if capital can be ...

    DSpace software copyright © 2002-2013  Duraspace
    Contact Us | Send Feedback
    Theme by 
    @mire NV
     

     

    Browse

    All of ResearchSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsAdvisorsTypeThis CollectionBy Issue DateAuthorsTitlesSubjectsAdvisorsType

    My Account

    LoginRegister

    DSpace software copyright © 2002-2013  Duraspace
    Contact Us | Send Feedback
    Theme by 
    @mire NV