Artificial Intelligence (FUZZY Logic) for local safety stock forecasting in multinational companies
As global economy takes off, we have a universalization of Manufacture and transfer of goods being made in other places. However, this practice results in some operational issues formultinational companies which are not able to transfer their know- how and supply chain practices for their overseas o...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Universidade Estadual Paulista
2019-09-01
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| Series: | GEPROS: Gestão da Produção, Operações e Sistemas |
| Subjects: | |
| Online Access: | https://revista.feb.unesp.br/index.php/gepros/article/view/2661 |
| _version_ | 1819070649149161472 |
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| author | Yuri Vasconcelos de Almeida Sá Tung Chiun Wen |
| author_facet | Yuri Vasconcelos de Almeida Sá Tung Chiun Wen |
| author_sort | Yuri Vasconcelos de Almeida Sá |
| collection | DOAJ |
| description | As global economy takes off, we have a universalization of Manufacture and transfer of goods being made in other places. However, this practice results in some operational issues formultinational companies which are not able to transfer their know- how and supply chain practices for their overseas offices, due either to local legislation, lack of customized software to local rules and even transfer delays of the product. One of the most critical issues that emerges is the contractual obligations for keeping sla?? and state mandatory deadlines, which may result in penalties. The go-to solution for that issue is to organize and keep a local safety stock, although that is problematic in itself, due to short shelf life, maintenance cost and demand fluctuations. In addition, many man hours were used for planning the local safety stock. In a case study, an AI technique was used, called fuzzy logic, to deal with these issues. The technique described in this article for the real system was able to mimic the discretionary behavior of the operator responsible for the safety stock, performing ideal planning for acquisitions. |
| first_indexed | 2024-12-21T17:09:17Z |
| format | Article |
| id | doaj.art-ce30eecfa01f4a60831d142d1b57d17f |
| institution | Directory Open Access Journal |
| issn | 1984-2430 |
| language | English |
| last_indexed | 2024-12-21T17:09:17Z |
| publishDate | 2019-09-01 |
| publisher | Universidade Estadual Paulista |
| record_format | Article |
| series | GEPROS: Gestão da Produção, Operações e Sistemas |
| spelling | doaj.art-ce30eecfa01f4a60831d142d1b57d17f2022-12-21T18:56:27ZengUniversidade Estadual PaulistaGEPROS: Gestão da Produção, Operações e Sistemas1984-24302019-09-01144011010.15675/gepros.v14i4.2661Artificial Intelligence (FUZZY Logic) for local safety stock forecasting in multinational companiesYuri Vasconcelos de Almeida Sá0Tung Chiun Wen1Faculdade de TecnologiaUniversidade PaulistaAs global economy takes off, we have a universalization of Manufacture and transfer of goods being made in other places. However, this practice results in some operational issues formultinational companies which are not able to transfer their know- how and supply chain practices for their overseas offices, due either to local legislation, lack of customized software to local rules and even transfer delays of the product. One of the most critical issues that emerges is the contractual obligations for keeping sla?? and state mandatory deadlines, which may result in penalties. The go-to solution for that issue is to organize and keep a local safety stock, although that is problematic in itself, due to short shelf life, maintenance cost and demand fluctuations. In addition, many man hours were used for planning the local safety stock. In a case study, an AI technique was used, called fuzzy logic, to deal with these issues. The technique described in this article for the real system was able to mimic the discretionary behavior of the operator responsible for the safety stock, performing ideal planning for acquisitions.https://revista.feb.unesp.br/index.php/gepros/article/view/2661Fuzzy logicArtificial intelligenceStock managementInventorySupply chain |
| spellingShingle | Yuri Vasconcelos de Almeida Sá Tung Chiun Wen Artificial Intelligence (FUZZY Logic) for local safety stock forecasting in multinational companies GEPROS: Gestão da Produção, Operações e Sistemas Fuzzy logic Artificial intelligence Stock management Inventory Supply chain |
| title | Artificial Intelligence (FUZZY Logic) for local safety stock forecasting in multinational companies |
| title_full | Artificial Intelligence (FUZZY Logic) for local safety stock forecasting in multinational companies |
| title_fullStr | Artificial Intelligence (FUZZY Logic) for local safety stock forecasting in multinational companies |
| title_full_unstemmed | Artificial Intelligence (FUZZY Logic) for local safety stock forecasting in multinational companies |
| title_short | Artificial Intelligence (FUZZY Logic) for local safety stock forecasting in multinational companies |
| title_sort | artificial intelligence fuzzy logic for local safety stock forecasting in multinational companies |
| topic | Fuzzy logic Artificial intelligence Stock management Inventory Supply chain |
| url | https://revista.feb.unesp.br/index.php/gepros/article/view/2661 |
| work_keys_str_mv | AT yurivasconcelosdealmeidasa artificialintelligencefuzzylogicforlocalsafetystockforecastinginmultinationalcompanies AT tungchiunwen artificialintelligencefuzzylogicforlocalsafetystockforecastinginmultinationalcompanies |