International Journal of Scientific Research and Engineering Development

The Internet of Things (IoT) has transformed the industrial sector by enabling seamless integration of diverse systems, devices, and technologies within manufacturing environments. IoT has significantly contributed to various aspects of manufacturing, including remote monitoring and control of industrial operations, improved energy efficiency, optimized resource utilization, and reduced operational costs, thereby supporting the evolution of smart manufacturing under the industry 4.0 paradigm. This review presents a comprehensive and up-to-date examination of IoT technologies and machine learning (ML) techniques employed in smart manufacturing. It focuses on four key application domains: industrial security, predictive maintenance, process control, and additive manufacturing. The study also provides a detailed overview and comparison of the ML algorithms most adopted in smart manufacturing environments. Furthermore, it critically evaluates recent IoT-based solutions reported in the literature, examining their architectural frameworks, sensing technologies, data analytics approaches, communication protocols, performance metrics, and other distinguishing characteristics. By comparing these solutions, the review identifies their respective strengths and limitations. Finally, the paper discusses emerging trends and highlights the essential features and capabilities expected in future IoT-driven systems for advanced smart manufacturing applications.

Vennila P, Maniraj V, "Machine Learning and IoT-Driven Solutions for Smart Manufacturing in Industrial Applications" International Journal of Scientific Research and Engineering Development, V9(4): Page(1045-1052) July-August 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.