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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM56478
Volume:
10 |
2 |
Feb 2026
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The rapid expansion of digital technologies and the growing demands of industrial standards are elevating the manufacturing sector to a more advanced level. This study proposes the integration of AI agents, specifically AI callbots, into the manufacturing environment and examines performance factors, downtime, meaningful insights, and decision-making. The study further investigates the use of AI callbots in optimizing performance, reducing downtime, and promoting prompt decision-making. The challenges of conventional systems are thoroughly examined, including troubleshooting latency, inconsistent data management, and a lack of real-time monitoring. The proposed solution considers the employment of AI agents combined with machine learning algorithms and natural language processing, facilitating human-machine integration, predictive maintenance, and timely scheduling. The methodology encompasses the optimal use of a unified namespace, enhancements in digital twin technology, and the application of augmented reality and virtual reality with real-time feedback adaptation. The results indicate a substantial increase in efficiency, client satisfaction, and compliance with industrial standards. The article concludes stating AI Agent as an effective AI-driven tool offering a sustainable approach in achieving manufacturing excellence.
KEYWORDS
Publication Date
10/1/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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