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Title: An RFID-enabled knowledge-based customization system for supply chain network integration
Authors: Cheung, Chung-man
Degree: M.Phil.
Issue Date: 2008
Abstract: The traditional axioms of supply chain management, Vendor Managed Inventory (VMI), Collaborative Planning, Forecast and Replenishment (CPFR), and Just-in-time (JIT) focus on building a long-term relationship, information streamlining and process integration. However, these strategies increase the dependence of supply chain partners and decrease flexibility. Increasing demands from customers, the need for innovation, and globalization of markets, has multiplied the complexity of the supply chain network, and increased the need for even more sophisticated and responsive approaches to supply chain management. With the aim of enhancing the agility and visibility of the supply chain, a framework for supply chain network integration is proposed in this thesis which integrates three core concepts: visualization of topologies, network analysis, and knowledge-based customization. Although the concepts originated from distinct research domains, current studies demonstrate the integration of these concepts in a complementary and innovative manner. Wide adoption of Radiofrequency Identification (RFID) technology is foreseeable due to the technology advancement and lowering of the cost. The large amount of real-time quality data now available opens the opportunities to manage the supply chain using a more sophisticated approach than ever before. Supply chain visibility is identified as one of the critical factors which allow a company to adapt effectively to fluctuations in the market. It is now possible to have a holistic and macroscopic view of the interaction that takes place in the supply chain showing detailed information from one end of the supply chain to the others. Network analysis which originated from research on network theory provides numerous tools to understand the structure of networks and the relationship of the entities (nodes) within the networks and permits the study of the dynamics of the network. Customization of the supply chain network allows it to achieve agility and cope with dynamic fluctuation in demand. The knowledge of experienced workers is needed to balance a complex network of tradeoffs. The knowledge-based customization system not only helps to acknowledge supply chain performance measured by network analysis, but also acquires knowledge from the knowledge workers during the formulation of supply chain strategies. To realize supply chain network integration in this study, a Knowledge-based Customization System for Supply-chain Integration (KCSSI) is designed and built. The application of the system is demonstrated by a trial implementation in a selected reference case in Novetex Spinners Limited, which is the World's largest single site woolen spinner in the garment industry. The performance of the system is verified by evaluating the result of the trial implementation, and by using the controlled simulation approach. It is verified that the KCSSI improves supply chain visibility by recognizing the structure clustering and interconnection of the supply chain network, quantifying and exploiting holistic supply chain performance to provide measurable insights. Under the controlled simulation, different system settings of the reasoning methodologies are evaluated by automating the problem retrieval, solution formulation and performance evaluation. In addition, the growth of the system is also simulated and studied. The results from the controlled simulation provide a strong support for the design and selection of reasoning methodologies. With the successful implementation of the system, supply chain visibility and agility is enhanced which allows network opportunities to be exploited and supply chain complexity to be alleviated. This improvement will help the company to survive in the long term even under turbulent market conditions.
Subjects: Hong Kong Polytechnic University -- Dissertations.
Radio frequency identification systems.
Business logistics -- Data processing.
Business networks.
Pages: xii, 179, 20 leaves : ill. ; 30 cm.
Appears in Collections:Thesis

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