Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/147771
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dc.titleOPTIMISING AN INTEGRATED PLANT NETWORK FOR STEEL RECYCLING
dc.contributor.authorGUO SI
dc.date.accessioned2018-09-26T08:57:08Z
dc.date.available2018-09-26T08:57:08Z
dc.date.issued2014
dc.identifier.citationGUO SI (2014). OPTIMISING AN INTEGRATED PLANT NETWORK FOR STEEL RECYCLING. ScholarBank@NUS Repository.
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/147771
dc.description.abstractThis paper uses a quantitative model to optimize the integrated plant network for steel production and recycling. The model was based on the Generic Recovery Network Model developed by Fleischmann et. al. The objective of the model is set to optimize the overall profit and its solutions involve whether to open a production/recycling plant at any customer location. Using the case study of NatSteel, the model yield a noticeably different network compared to NatSteel’s existing network. This could be largely due to the expansion strategies taken by NatSteel in entering new markets. More importantly, the model was used to gain further insights into the plant network competencies, namely, recycling ratio, miniscaling and localization. The model revealed that unit profit increases with investment in these competencies. The model also validated the complementarities among these competencies, which suggests that investment in a combination of competencies can generate additional increase in unit profit. Through analyzing the optimal networks, it is found that there is a tendency for production plants and recycling plants to be collocated due to savings in transportation cost. In addition, investing in the three competencies leads to more decentralized plant networks. The mechanisms towards decentralization are different, as increasing recycling ratio shows favour for more recycling plants while increasing localization shows favour for more production plants. Their interaction with colocation bonus leads to an overall more decentralized plant network. We hope that this paper could provide some insights for improvement on firms’ existing plant network and potential expansion, to work towards a more sustainable growth.
dc.typeThesis
dc.contributor.departmentNUS Business School
dc.contributor.supervisorQI MEI
dc.description.degreeBachelor's
dc.description.degreeconferredBACHELOR OF BUSINESS ADMINISTRATION WITH HONOURS
Appears in Collections:Bachelor's Theses

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