In recent years, the rapid growth of new technologies, especially artificial intelligence, has created new opportunities in various fields, particularly in the manufacturing industry. This research aims to provide a systematic analysis of how to integrate and embed artificial intelligence into manufacturing processes, focusing on assessing the role of this technology in transforming the industry and enhancing factory performance.

Artificial intelligence has unique capabilities in analyzing big data, predicting malfunctions, optimizing resource management, increasing quality control accuracy, designing new products, and improving productivity. Integrating AI with various manufacturing subsystems through advanced software and hardware tools can lead to information coherence, reduced errors, improved response times, and enhanced intelligent decision-making in complex environments.

However, this path faces challenges such as the need for technological infrastructure, coordination between incompatible systems, high initial costs, the need for training specialized human resources, and security and cultural considerations. In this research, in addition to outlining the main advantages of AI integration in manufacturing, solutions are proposed to overcome challenges, such as utilizing open standards, adopting lightweight models and SaaS, and gradually developing AI models on cloud platforms.

The results indicate that integrating artificial intelligence is not only a significant step towards digital transformation but also an essential necessity for competitiveness, innovation, and sustainable development in the manufacturing industry.
The results indicate that integrating artificial
The results indicate that integrating artificial intelligence is not only a significant step towards digital transformation but also an essential necessity for competitiveness, innovation, and sustainable development in the manufacturing industry.