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https://hdl.handle.net/20.500.14365/5308
Title: | Using AI Tools to Enhance the Risk Management Process in the Automotive Industry | Authors: | Dragomir, D. Popișter, F. Kabak, K.E. |
Keywords: | artificial intelligence automotive industry risk management Data Analytics Knowledge representation Risk assessment Risk management Automotive companies Classical approach Comparative analyzes Identification procedure Mitigation measures Organizational levels Process levels Risk Identification Risk management process Risks management Automotive industry |
Publisher: | Springer Science and Business Media Deutschland GmbH | Abstract: | The paper presents an exploratory investigation concerning the usage of AI tools in automotive companies in order to streamline their risk management processes. A risk identification procedure is performed at organizational and process levels, and a comparative analysis is undertaken between the classical approach for developing proper mitigation measures and the AI-supported manner of doing the same. Some of the most popular tools in this field are employed and studied, such as large language models, data analytics and knowledge representation. The differences and changes are analyzed from the point of view of their effectiveness, efficiency and adaptability within the existing manufacturing frameworks in the automotive industry. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. | Description: | 8th International Scientific-Technical Conference Manufacturing, MANUFACTURING 2024 -- 14 May 2024 through 16 May 2024 -- 310369 | URI: | https://doi.org/10.1007/978-3-031-56444-4_15 https://hdl.handle.net/20.500.14365/5308 |
ISBN: | 9783031564468 | ISSN: | 2195-4356 |
Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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