Streamlining industrial robot maintenance: an intelligent voice query approach for enhanced efficiency

Ren, Zecheng, Yu, Zengnan, Zhang, Wenyi and Lei, Qujiang (2024) Streamlining industrial robot maintenance: an intelligent voice query approach for enhanced efficiency. IEEE Access, 12. 121864 - 121881. ISSN 2169-3536

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Abstract

Industrial robots are indispensable in modern manufacturing across various sectors, including nuclear, chemical, and aerospace industries. They serve to replace humans in hazardous operations, ensuring worker safety, while also enhancing production efficiency and product quality, particularly in tasks such as welding and assembly. However, the maintenance and repair of these robots present significant challenges. When malfunctions occur, workers often face the daunting task of sifting through extensive industrial manuals to diagnose the root cause based on error codes, a process that is time-consuming and hampers productivity.To address this issue, this paper proposes an intelligent voice query method designed to facilitate access to industrial manual content. The goal is to empower workers to swiftly comprehend the causes of robot failures and retrieve corresponding solutions through interactive voice commands, thereby streamlining troubleshooting efforts. Leveraging voice recognition technology, workers can effortlessly issue queries without the need for manual search and interpretation. The effectiveness of this method was rigorously evaluated through experimental validation in real-world scenarios, demonstrating notable improvements in maintenance efficiency.

Item Type:	Article
Additional Information:	© 2024 The Authors
Divisions:	LSE
Subjects:	Q Science > Q Science (General)
Date Deposited:	23 Sep 2024 13:03
Last Modified:	25 Nov 2024 21:39
URI:	http://eprints.lse.ac.uk/id/eprint/125493

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