Enhancing Knowledge Sharing Workshops with Natural Language Processing in Maintenance Work

被引:0
作者
Ogawa, Riku [1 ]
Inoue, Moritaro [1 ]
Uchihira, Naoshi [1 ]
机构
[1] Japan Adv Inst Sci & Technol, 1-1 Asahidai, Nomi, Ishikawa 9231292, Japan
来源
2024 INTERNATIONAL TECHNICAL CONFERENCE ON CIRCUITS/SYSTEMS, COMPUTERS, AND COMMUNICATIONS, ITC-CSCC 2024 | 2024年
关键词
Natural Language Processing; Smart Voice Messaging System; Knowledge Management System; MANAGEMENT;
D O I
10.1109/ITC-CSCC62988.2024.10628182
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In maintenance and inspection work, sharing and leveraging latent and tacit knowledge possessed by field inspectors are crucial for efficient maintenance and skill enhancement. We have developed the smart voice messaging system, which was designed to accumulate and utilize this latent and tacit knowledge, known as "Gen-Ba knowledge," which is difficult to describe as explicit knowledge (e.g. manuals). An effective approach for knowledge sharing is conducting workshops by inspectors using voice messages containing "Gen-Ba knowledge" recorded in the field by smart voice messaging system. Here, it is important that workshops are conducted efficiently and effectively. This study proposes a method to enhance workshop activation using natural language processing technologies. We applied the proposed method to electrical maintenance work and evaluated its effectiveness. A technical contribution elucidates how various large language models can enhance knowledge sharing workshops.
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页数:6
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