Abstract
Supply chain design is a task that has to both be economically efficient and provide viable design results. Therefore, the demand placed on supply chain design is for modelling methods that rapidly and efficiently provide key performance indicators for the networks assessed to a desired level of granularity and to a sufficient degree of realism. Several such modelling methods exist that each divergently fulfils these requirements. Of special interest in automotive supply chain design are static scenario comparison and dynamic simulation. The former, because it is easy to comprehend and straightforward to apply; the latter, because it is so powerful and its results are so desirable. Integrating both methods leads to significant advantages when modelling during supply chain design. The combined approach taken provides quick and efficient evaluation of a large number of scenarios at a suitable level of granularity and provides a higher degree of realism than just applying a static scenario comparison. Static modelling provides an adequate initial assessment of supply chain design and reduces the number of scenarios to a set of viable networks. These are automatically transferred to a dynamic simulation where assessment at a detailed level of granularity and lower level of abstraction takes place. Thus, all possible network alternatives are assessed quickly. The user gains efficiency and speed, whilst having the best data and key performance indicators possible for decision-making.
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Seidel, T. (2008). Rapid Supply Chain Design by Integrating Modelling Methods. In: Parry, G., Graves, A. (eds) Build To Order. Springer, London. https://doi.org/10.1007/978-1-84800-225-8_16
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DOI: https://doi.org/10.1007/978-1-84800-225-8_16
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