Abstract
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.
| Original language | Undefined/Unknown |
|---|---|
| Journal | International Journal of Scientific Research in Engineering and Management |
| Volume | 10 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 10 Feb 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
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