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Supply networks are the means by which products are delivered to market. Organisations within supply networks exploit their capabilities to co-create value with customers. Perspectives are needed across multiple organisations in. the network if supply network performance is to be maximised. Measures of performance include responsiveness and reduced costs. This research explored means of visualizing one aspect of supplier capability, namely capacity, and its implications for supply network performance. An application of discrete event simulation was used to visualize suppliers' capacities in supply network contexts. A framework for the visualization of supply networks was established based upon requirements elicited from a review of literature. The framework was used to evaluate three broad approaches to the visualizat10n of supplier capability in supply networks. A common feature of these approaches was the static nature of the data being visualized. Given the nature of demand fluctuations, a dynamic visualization of capacity would allow risks to be made visible to decision makers. Three case studies were used. An initial case study, based on a civil aerospace supply network, highlighted the importance of employing supply network best practices. These include involving suppliers in the design and development of products and using continuous improvement approaches such as waste elimination to shorten manufacturing lead times. These two are key success factors for an organisation's long term supply network performance. Two further case studies were based. on a bicycle supply network. One was used to build understanding of the interplay between supply network and product structure. This led to a recognition that a product structure influences network structure. In turn, network structure influences supply network processes, and supply network performance is a measure of the performance of these processes. For changes in demand, the bill of materials can be used to predict capacity demands in the supply network. The second bicycle case study was used to explore the potential of discrete event simulation tools to visualise the consequences of surges in demand and allow alternative capacity strategies to be explored. |
