Modelling complexity in the automotive industry supply chainTools Turner, Kevin and Williams, Geoff (2005) Modelling complexity in the automotive industry supply chain Journal of manufacturing technology management, 16 (4). pp. 447-458. ISSN 1741-038X Full text not available from this repository. Official URL: http://dx.doi.org/10.1108/17410380510594525 AbstractAbstract: Purpose – In most countries the distribution system for new cars has remained unchanged for many years, with the main emphasis on supplying customers from stock held at dealers. Despite high stocks, the performance of the supply chain has failed to meet customer expectations in terms of delivering the exact specification desired within an acceptable timescale. This paper investigates changes to the design of the supply chain which potentially offer significant improvements in performance. Design/methodology/approach – A simulation of the supply of new cars, from ordering through the assembly plant and finished vehicle stocking to customer delivery, has been used to develop further understanding of the dynamic performance of the supply chain. The application of the simulation model is demonstrated through scenarios drawn from research into the UK car market. Findings – The findings demonstrate the benefits of central stocking (storing new cars in distribution centres, rather than at dealers) for both manufactures and customers, supported by recent industry data. Research limitations/implications – The results presented are based on a representative vehicle model manufactured and sold in the UK; a range of alternative scenarios and changes to the supply chain design can be investigated using the simulation model. Practical implications – For the automotive industry, the research supports the introduction of central stocking, and demonstrates a methodology for assessing future changes to the supply chain. Originality/value – The research extends the range of applications of simulation to investigating supply chain design, and demonstrates the feasibility of this approach in modelling complex supply chains.
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