Using Ai Tools To Enhance the Risk Management Process in the Automotive Industry
Loading...

Date
2024
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Science and Business Media Deutschland GmbH
Open Access Color
Green Open Access
No
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
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
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
Fields of Science
Citation
WoS Q
N/A
Scopus Q
Q4

OpenCitations Citation Count
N/A
Source
Lecture Notes in Mechanical Engineering
Volume
Issue
Start Page
189
End Page
198
PlumX Metrics
Citations
Scopus : 0
Captures
Mendeley Readers : 7
Google Scholar™


