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AI and Machine Learning-Driven Manufacturing: Pioneering Best Practices for Intelligent, Scalable, and Sustainable Industrial Operations
Author Name : Ankush Keskar
ABSTRACT AI and ML have recently become popular in manufacturing industries, where they add operational intelligence to manufacturing industries to make them smarter and more sustainable. There is a body of research that discusses the effects that advanced functions, including AI and ML technologies, have on manufacturing processes, paying special attention to the innovative Industry 4.0 principles that are used as the foundation for the intelligent decision-making mechanisms, as well as for scaling and making the entire manufacturing process more sustainable. They explore where and how AI and decision-making technologies for performance prediction, automation, and near-real-time optimization underpin increased productivity, sustainability, and reduced costs. This paper identifies important applications like Predictive Maintenance, Quality assurance, supply chain, and Energy management. It presents a deeper understanding of the contribution made by the respective applications to improve industrial performance. The research also discusses the issues faced while adopting AI & ML in manufacturing, including data handling, system interconnection, and organizational shifts. Therefore, the expected contribution of this work is to provide industries the ability to apply AI and ML solutions in light of modern industrial requirements for manufacturing flexibility, industry growth, and sustainability while avoiding pitfalls in choosing the proper solutions.