Revolutionizing Industrial Management: A Review of Artificial Intelligence Applications in Manufacturing Operations

Samir  ali; Salah; AbdulJaleel

doi:10.71229/njemcs.v1i2.3

Authors

Samir Ali Amin Department of Mechanical Power Techniques Engineering, College of Technical Engineering, University of Al-Farahidi,
Salah Sabeeh Abed Al Kareem Department of Mechanical Power Techniques Engineering, College of Technical Engineering, University of Al-Farahidi,
AbdulJaleel Hamad Majeed Department of Aeronautical Technical Engineering, College of Technical Engineering, University of Al-Farahidi,

DOI:

https://doi.org/10.71229/njemcs.v1i2.3

Keywords:

Artificial Intelligence, Industrial Management,, Manufacturing Automation,, Robotics in Manufacturing,, AI-Driven Decision Making, Flexible Manufacturing Systems.

Abstract

Artificial Intelligence paved the path for integration into industrial management, which shook up the operational frontier within manufacturing and supply chain. Combining these with machine learning, predictive analytics, robotics and computer vision, this thought provoking, comprehensive review considers the transformative potential of mixed use AI in driving enhanced industrial productivity, better decisions, and smarter processes. The study describes how theoretical constructs of AI became practical applications capable of predictive maintenance, real time monitoring, and demand forecasting and flexible manufacturing systems. Dynamic resource allocation, as supported by AI, allows us to improve the operation of quality inspection systems to control quality and management of supply chain through intelligent logistics and inventory management to improve supply chain resilience. Besides that, these technologies not only lower the operational cost and downtime in production, but also allow for further customization, agility and innovativeness towards vary market needs. In the same vein, AI can also analyze big data in real time and help industries make concrete strategic decisions driven by the data. However, the paper argues in spite of these advantages the paper critically discusses several key barriers to adoption, which include legacy system integration, data privacy concern, workforce readiness and organizational resistance. It highlights the significance of cultural transformation, ethical AI practices, and up skilling construct in ensuring the full deployment of AI in an industrial environment. AI is expected to cause additional emerging trends like digital twins, generative AI and Industry 5.0 to meaningfully stir AI, which will create socio-technological synergies to foster efficiency while maintaining sustainability and human centric values. It concludes that AI will actually reshape operational frameworks as it will become a fundamental part of the digital transformation of industrial enterprises.

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