AI-Powered Industrial Robots in Smart Factories: A Survey of Applications Challenges and Future Trends
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Abstract
The integration of Artificial Intelligence (AI) with industrial robotics is driving the evolution of smart factories, creating environments that are intelligent, adaptive, and highly efficient. By combining machine learning, computer vision, and real-time decision-making with advanced robotics, industries are achieving greater flexibility, precision, and productivity. Smart factories leverage enabling technologies such as Industrial Internet of Things (IIoT), cloud/edge computing, and collaborative robots to enhance workflow optimization, predictive maintenance, and quality assurance. This survey explores the applications of AI-powered industrial robots, including autonomous material handling, adaptive manufacturing, defect detection, and micro-manufacturing, which contribute significantly to cost efficiency and operational reliability. It further highlights the challenges hindering adoption, such as high implementation costs, integration with legacy systems, safety concerns, and the requirement for skilled expertise. The paper also reviews existing literature to provide insights into technological advances, industrial impact, and global adoption trends. Findings emphasize that AI-powered robotics not only enhances productivity and sustainability but also paves the way for Industry 4.0 transformation. Future directions focus on interdisciplinary collaboration, ethical AI deployment, and advanced cognitive robotic systems for sustainable and resilient manufacturing ecosystems.
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This work is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) License. Authors retain the copyright of their work and grant the Journal of Global Research in Multidisciplinary Studies (JGRMS) the right of first publication. This license permits unrestricted use, distribution, adaptation, and reproduction in any medium or format, provided the original author(s), source, and publication are properly credited. Users may copy, redistribute, remix, transform, and build upon the published material for any purpose, including commercial use, in accordance with the terms of the CC BY 4.0 License.