Browsing by Author "Van Schalkwyk, Willem Tobias"

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    A data and modelling framework for strategic supply chain decision-making in the petro-chemical industry.
    (Stellenbosch : Stellenbosch University, 2006-12) Van Schalkwyk, Willem Tobias; Bekker, James; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.
    ENGLISH ABSTRACT: The research was initiated by an opportunity within the petro-chemical company Sasol to explore, improve and integrate various analytical techniques used in the modelling, design and optimisation of supply chains. Although there is already a strong focus on the use of analytical applications in this environment, the lack of both modelling integration and analytical data availability has led to less than optimal results. This document presents an exploration into the supply chain planning landscape, and in particular strategic planning in the petro-chemical environment. Various modelling methodologies and techniques that support strategic supply chain decision-making are identified, followed by an in-depth analysis of the data requirements for effectively constructing each of these models. Perhaps the biggest hurdle in the continual use of modelling techniques that support strategic supply chain decision-making, remains the extent of the data gathering phase in any such project. Supply chain models are usually developed on an ad hoc project basis, each time requiring extensive data gathering and analysis from transactional data systems. The reason for this is twofold: 1) transactional data are not configured to meet the analytical data requirements of supply chain models, and 2) projects are often done in isolation, resulting in supply chain data that end up in spreadsheets and point solutions. This research proposes an integrated data and modelling framework, that aspires to the sustainable use of supply chain data, and continual use of modelling techniques to support strategic supply chain decision-making. The intent of the framework is twofold: 1) to enable the design of new supply chains, and 2) to ensure a structured approach for capturing historical supply chain activities for continued review and optimisation. At the heart of the framework is the supply chain analytical data repository (SCADR), a database that maintains supply chain structural and managerial information in a controlled data model. The motivation behind developing a database structure for storing supply chain data is that a standard encoding method encourages data sharing among different modelling applications and analysts. In the globalised environment of the 21•t century, companies can no longer ensure its market position solely by its own functional excellence ... in the new economy, whole business ecosystems compete against each other for global survival (Moore, 1996). This motivates the ever-increasing importance of supply chain management, which necessitates the use of advanced analytical tools to assist business leaders in making ever more complex supply chain decisions. It is believed that the integration of information requirements for multiple optimisation/ modelling initiatives in a structured framework (as presented in this research) will enable sustainability and improved strategic decision-making for the petro-chemical supply chain.