Analysis of demand planning in supply chain using simulation modeling
This research focuses on demand planning in the supply chain. Systems thinking and system dynamics are introduced for the thinking and analysis of the supply chain, and proved to be the effective and vital approaches. With these approaches, the methodology of simulation modeling is employed to model...
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sg-ntu-dr.10356-135102023-03-11T17:17:16Z Analysis of demand planning in supply chain using simulation modeling Wong, Yew Peng. De Souza, Robert School of Mechanical and Production Engineering Spedding, Trevor Allan DRNTU::Engineering::Industrial engineering::Supply chain This research focuses on demand planning in the supply chain. Systems thinking and system dynamics are introduced for the thinking and analysis of the supply chain, and proved to be the effective and vital approaches. With these approaches, the methodology of simulation modeling is employed to model the supply chain and demand planning in the supply chain. The simulation model successfully demonstrates the causes and impacts of the "bullwhip effect" and the importance of stability and predictability in the supply chain. Moreover, it also demonstrates the importance of information technology and the benefits of reducing lead times in the supply chain. Most importantly, the simulation model demonstrates that demand planning in the supply chain is more than the forecast of the product demands. This work also presents the suggested ordering strategies and the important factors to be considered in the ordering strategies for demand planning in the supply chain. This dissertation also discusses how the simulation model can be developed from a tool for analyzing the supply chain into a software that is capable of supporting the planning and decision making in the supply chain. Master of Engineering (MPE) 2008-10-20T08:21:57Z 2008-10-20T08:21:57Z 1999 1999 Thesis http://hdl.handle.net/10356/13510 en 105 p. application/pdf |
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DRNTU::Engineering::Industrial engineering::Supply chain Wong, Yew Peng. Analysis of demand planning in supply chain using simulation modeling |
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This research focuses on demand planning in the supply chain. Systems thinking and system dynamics are introduced for the thinking and analysis of the supply chain, and proved to be the effective and vital approaches. With these approaches, the methodology of simulation modeling is employed to model the supply chain and demand planning in the supply chain. The simulation model successfully demonstrates the causes and impacts of the "bullwhip effect" and the importance of stability and predictability in the supply chain. Moreover, it also demonstrates the importance of information technology and the benefits of reducing lead times in the supply chain. Most importantly, the simulation model demonstrates that demand planning in the supply chain is more than the forecast of the product demands. This work also presents the suggested ordering strategies and the important factors to be considered in the ordering strategies for demand planning in the supply chain. This dissertation also discusses how the simulation model can be developed from a tool for analyzing the supply chain into a software that is capable of supporting the planning and decision making in the supply chain. |
author2 |
De Souza, Robert |
author_facet |
De Souza, Robert Wong, Yew Peng. |
format |
Theses and Dissertations |
author |
Wong, Yew Peng. |
author_sort |
Wong, Yew Peng. |
title |
Analysis of demand planning in supply chain using simulation modeling |
title_short |
Analysis of demand planning in supply chain using simulation modeling |
title_full |
Analysis of demand planning in supply chain using simulation modeling |
title_fullStr |
Analysis of demand planning in supply chain using simulation modeling |
title_full_unstemmed |
Analysis of demand planning in supply chain using simulation modeling |
title_sort |
analysis of demand planning in supply chain using simulation modeling |
publishDate |
2008 |
url |
http://hdl.handle.net/10356/13510 |
_version_ |
1761781522241683456 |