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dc.contributor.supervisorSong, Dongping
dc.contributor.authorXU, Wei
dc.contributor.otherPlymouth Business Schoolen_US
dc.date.accessioned2013-12-03T16:07:04Z
dc.date.available2013-12-03T16:07:04Z
dc.date.issued2013
dc.identifier10246396en_US
dc.identifier.urihttp://hdl.handle.net/10026.1/2839
dc.description.abstract

Supply chain management has attracted much attention in the last decade. There has been a noticeable shift from a traditional individual organisation-based management to an integrated management across the supply chain network since the end of the last century. The shift contributes to better decision making in the supply chain context, as it is necessary for a company to cooperate with other supply chain members by utilising relevant information such as inventory, demand and resource capacity. In other words, information sharing and coordinated management are essential mechanisms to improve supply chain performance.

Supply chains may differ significantly in terms of industry sectors, geographic locations, and firm sizes. This study was based on case studies from small and medium sized manufacturing supply chains in People Republic of China. The study was motivated by the following facts. Firstly, small and medium enterprises have made a big contribution to China’s economic growth. Several studies revealed that most of the Chinese manufacturing enterprises became aware of the importance of supply chain management, but compared to western firms, the supply chain management level of Chinese firms had been lagging behind. Research on supply chain management and performance optimisation in Chinese small and medium sized enterprises (SMEs) was very scarce. Secondly, there had been plenty of studies in the literature that focused on two or three level supply chains whilst considering a number of uncertain factors (e.g. customer demand) or a single supply chain performance indicator (e.g. cost). However, the research on multiple stage supply chain systems with multiple uncertainties and multiple objectives based on real industrial cases had been spared and deserved more attention. One reason was due to the lack of reliable industrial data that required an enormous effort to collect the primary data and there was a serious concern about data confidentiality from the industry aspect.

This study employed two SME manufacturing companies as case studies. The first one was in the Aluminium industry and another was in the Chemical industry. The aim was to better understand the characteristics of the supply chains in Chinese SMEs through performing in-depth case studies, and built models and tools to evaluate different strategies for improving their supply chain performance.

The main contributions of this study included the following aspects. Firstly, this study generalised a supply chain model including a domestic supply chain part and an international supply chain part based on deep case studies with the emphasis on identifying key characteristics in the case supply chains, such as uncertainties, constraints and cost elements in association with flows and activities in the domestic supply chain and the international supply chain. Secondly, two important SCM issues, i.e. the integrated raw material procurement and finished goods production planning, and the international sales planning, were identified. Thirdly, mathematical models were formulated to represent the supply chain model taking into account multiple uncertainties. Fourthly, several operational strategies utilising the concepts of just-in-time, safety-stock/capacity, Kanban, and vendor managed inventory, were evaluated and compared with the case company's original strategy in various scenarios through simulation methods, which enabled quantification of the impact of information sharing on supply chain performance. Fifthly, a single objective genetic algorithm was developed to optimise the integrated raw material ordering and finished goods production decisions under (s, S) policy (a dynamic inventory control policy), which enabled the impact of coordinated management on supply chain performance to be quantified. Finally, a multiple objectives genetic algorithm considering both total supply chain cost and customer service level was developed to optimise the integrated raw material ordering and finished goods production with the international sales plan decisions under (s, S) policy in various scenarios. This also enabled the quantification of the impact of coordinated management on supply chain performances.

en_US
dc.language.isoenen_US
dc.publisherUniversity of Plymouthen_US
dc.subjectSupply Chain Managementen_US
dc.subjectInformation Sharingen_US
dc.subjectCoordinationen_US
dc.subjectSMEen_US
dc.subjectIntegrated raw material procurement and finished goods production strategyen_US
dc.subjectInternational sales planen_US
dc.subjectDecision Makingen_US
dc.subjectSimulationen_US
dc.subjectOptimisationen_US
dc.subjectGenetic Algorithmen_US
dc.titleOptimising Supply Chain Performance via Information Sharing and Coordinated Managementen_US
dc.typeThesis
plymouth.versionFull versionen_US
dc.identifier.doihttp://dx.doi.org/10.24382/1546
dc.identifier.doihttp://dx.doi.org/10.24382/1546


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