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A Review on Integrating AI and Machine Learning using Data-Driven Approaches for Smart and Sustainable Manufacturing

Author

Listed:
  • Varalakshmi Byadigere Doddathimmaiah

    (Acharya Institute of Technology, India)

  • Lingaraju Gowdru Malleshappa

    (Ashoka Polytechnic, India)

  • Geetha Venkatesh

    (Ramaiah Institute of Technology, India)

  • Ameya Mathew

    (Proeffective Cloud IT Services, India)

Abstract

This review paper systematically analyses advanced artificial intelligence (AI) and machine learning (ML) methodologies implemented in modern Industry 4.0 production lines. Manufacturing has evolved significantly due to data-intensive processes, with AI techniques such as deep learning, transformer-based large language models (LLMs), reinforcement learning, and generative AI becoming integral for interpreting extensive industrial data and optimizing real-time decisions. Specifically discussed are algorithmic scheduling, intelligent production planning, overall equipment effectiveness (OEE), and deep learning models, emphasizing recent breakthroughs including the application of LLMs for predictive analytics and decision-making in manufacturing scenarios.

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Handle: RePEc:epw:ejai00:v:4:y:2025:i:6:id:1083
DOI: 10.24018/ejai.2025.4.6.1083
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