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dc.contributor.advisorHuy, Nguyen Hoang
dc.contributor.authorNhu, Le Hoang
dc.date.accessioned2021-09-03T03:47:37Z
dc.date.available2021-09-03T03:47:37Z
dc.date.issued2020
dc.identifier.other022005780
dc.identifier.urihttp://keep.hcmiu.edu.vn:8080/handle/123456789/4071
dc.description.abstractNowadays in Vietnam, steel industry is experiencing numerous promising potentialities for further development in not only domestic but international markets as well. To remain competitive with other steel manufacturers, Bien Hoa Steel Joint Stock Company (VICASA), one of the companies operating in this sector, has to continually improve its performance. One of the important considerations is enhancing the control of its inventories. Despite having operated for many years, currently, the company is facing some difficulties in inventory management which has resulted in a substantial increase in total inventory costs up to 8 billion VND over the last year. Through the observations at the warehouse and data analysis, the research has identified two main issues in inventory management of the company including inaccurate demand forecast and high inventory level. In order to solve the problems, a new mathematical model is carried out in this thesis with the goal of reducing total costs to at least 10 - 15% as well as inventory amount at least 10%. Moreover, certain techniques for forecasting will be addressed in order to propose an appropriate one instead of using moving average, which has which has proven inefficient in predicting the company's demand. In terms of data collection, a 12-month dataset with 3 item types is applied in mathematical modeling and demand forecasting methods that provide the feasible solution. Keywords: inventory management, inventory level, intermittent demand, forecasting techniques, steel production.en_US
dc.language.isoen_USen_US
dc.publisherInternational University - HCMCen_US
dc.subjectInventory managementen_US
dc.titleInventory management in supply chain: A Bien Hoa steel joint stock company (VICASA) case studyen_US
dc.typeThesisen_US


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