International Journal of Mechatronics and Manufacturing Technology ISSN: 3139-5058 (Online)

Authors: Rekha Dhanghi, Kavita Bansal

Abstract: Manufacturing industries are undergoing a significant transformation due to the integration of Artificial Intelligence (AI) technologies. Modern factories produce massive volumes of operational data through sensors, machines, enterprise systems, and supply chains. AI driven manufacturing optimization focuses on analyzing this data to improve productivity, quality, and operational efficiency. Machine learning algorithms, predictive analytics, and intelligent decision support systems allow manufacturers to detect patterns, forecast failures, and optimize production schedules in real time. The integration of AI also enables adaptive manufacturing processes where systems automatically adjust parameters to achieve desired outcomes. This paper reviews the role of AI in manufacturing optimization and decision support. It discusses core technologies such as machine learning, digital twins, predictive maintenance, and data driven scheduling. The study also highlights benefits including cost reduction, improved production planning, and enhanced product quality. However, challenges like data integration, computational complexity, and workforce adaptation remain significant. The paper concludes that AI driven optimization will play a central role in the development of smart manufacturing and Industry 4.0 systems.

Keywords: Artificial Intelligence, Smart Manufacturing, Predictive Maintenance, Decision Support Systems, Production Optimization, Industry 4.0