Real-Time Verification and Updates of End-of-Life (EOL) Data: Enhancing Database Maintenance through ChatGPT Integration
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International Journal of Recent Engineering Science (IJRES) |  |
| © 2024 by IJRES Journal | ||
| Volume-11 Issue-3 |
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| Year of Publication : 2024 | ||
| Authors : Gauri Borle, Juee Gore, Riya Dangra, Amitkumar Manekar |
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| DOI : 10.14445/23497157/IJRES-V11I3P118 |
How to Cite?
Gauri Borle, Juee Gore, Riya Dangra, Amitkumar Manekar, "Real-Time Verification and Updates of End-of-Life (EOL) Data: Enhancing Database Maintenance through ChatGPT Integration," International Journal of Recent Engineering Science, vol. 11, no. 3, pp. 143-150, 2024. Crossref, https://doi.org/10.14445/23497157/IJRES-V11I3P118
Abstract
Incorporating ChatGPT technology into industrial product lifecycle management seeks to address the challenges of verifying and updating End-of-Life (EOL) dates in databases, which are often laborious and error-prone tasks. By utilizing OpenAI's GPT-3 model through Python and the OpenAI API, the goal is to automate the validation processes, minimize manual work, and improve data accuracy. Through iterative refinement of the AI model using specific prompts and real-time feedback, the system can efficiently handle changes in EOL dates, address broken URLs, and ensure secure authentication. By harnessing ChatGPT's natural language processing capabilities, this integration provides a comprehensive solution for effective decisionmaking and asset management within the product lifecycle management framework. Ultimately, this approach aims to revolutionize EOL database management practices by optimizing precision, productivity, and dependability while reducing the need for manual intervention. The research gap includes limited application scope beyond EOL date verification, lack of integration with existing systems, scalability and performance concerns, user acceptance and training challenges, security and compliance issues, and absence of a cost-benefit analysis. Addressing these gaps can enhance the practical implementation of ChatGPT in industrial PLM.
Keywords
Web scraping techniques, End-of-life management, ChatGPT technology, Prompt engineering, EoL device security.
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