A research about data-driven simulation approach for Rolls-Royce 150 seater engine supply chain
This dissertation is about a data-driven simulation applied on the supply chain improvement project for Rolls-Royce. Rolls-Royce is now planning design an engine for 150 seats Boeing 737. One of requirements of Boeing is less than 65 days lead time. Compared current 2 years lead time, it is a big ch...
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| Format: | Dissertation (University of Nottingham only) |
| Language: | English |
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2007
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| Online Access: | https://eprints.nottingham.ac.uk/21087/ |
| _version_ | 1848792183195303936 |
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| author | Shi, Shuaijie |
| author_facet | Shi, Shuaijie |
| author_sort | Shi, Shuaijie |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | This dissertation is about a data-driven simulation applied on the supply chain improvement project for Rolls-Royce. Rolls-Royce is now planning design an engine for 150 seats Boeing 737. One of requirements of Boeing is less than 65 days lead time. Compared current 2 years lead time, it is a big challenge for Rolls-Royce's supply chain. A data-driven simulation method is applied in this article to solve this problem. The model of 150 seater engine supply chain is built by data-driven simulation. Supply chain theories are used to analyze the model and provide solutions. Data-driven simulation experiment one of the solutions in supply chain model. At last, recommendation is given in last chapter. |
| first_indexed | 2025-11-14T18:40:21Z |
| format | Dissertation (University of Nottingham only) |
| id | nottingham-21087 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T18:40:21Z |
| publishDate | 2007 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-210872022-03-21T16:03:55Z https://eprints.nottingham.ac.uk/21087/ A research about data-driven simulation approach for Rolls-Royce 150 seater engine supply chain Shi, Shuaijie This dissertation is about a data-driven simulation applied on the supply chain improvement project for Rolls-Royce. Rolls-Royce is now planning design an engine for 150 seats Boeing 737. One of requirements of Boeing is less than 65 days lead time. Compared current 2 years lead time, it is a big challenge for Rolls-Royce's supply chain. A data-driven simulation method is applied in this article to solve this problem. The model of 150 seater engine supply chain is built by data-driven simulation. Supply chain theories are used to analyze the model and provide solutions. Data-driven simulation experiment one of the solutions in supply chain model. At last, recommendation is given in last chapter. 2007 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/21087/1/07Msclixss28.pdf Shi, Shuaijie (2007) A research about data-driven simulation approach for Rolls-Royce 150 seater engine supply chain. [Dissertation (University of Nottingham only)] (Unpublished) Data-Driven simulaiton Rolls-Royce 150 seats engine |
| spellingShingle | Data-Driven simulaiton Rolls-Royce 150 seats engine Shi, Shuaijie A research about data-driven simulation approach for Rolls-Royce 150 seater engine supply chain |
| title | A research about data-driven simulation approach for Rolls-Royce 150 seater engine supply chain |
| title_full | A research about data-driven simulation approach for Rolls-Royce 150 seater engine supply chain |
| title_fullStr | A research about data-driven simulation approach for Rolls-Royce 150 seater engine supply chain |
| title_full_unstemmed | A research about data-driven simulation approach for Rolls-Royce 150 seater engine supply chain |
| title_short | A research about data-driven simulation approach for Rolls-Royce 150 seater engine supply chain |
| title_sort | research about data-driven simulation approach for rolls-royce 150 seater engine supply chain |
| topic | Data-Driven simulaiton Rolls-Royce 150 seats engine |
| url | https://eprints.nottingham.ac.uk/21087/ |