AI-Based Dynamic Reconfiguration in Modular Smart Manufacturing Cells

  • Authors

    • Dr. Mohammed Asif Khan Professor, Jamia Millia Islamia, India. Author
    • Dr. Shalini Gupta Associate Professor, Panjab University, India. Author

    DOI:

    https://doi.org/10.67228/3142788X/IJMLPA-2018PI4T7B

    Published 03-02-2018

  • Smart Manufacturing, Modular Manufacturing Cells, Dynamic Reconfiguration, Artificial Intelligence, Industry 4.0, Machine Learning, Cyber-Physical Systems, Real-Time Decision Making, Intelligent Automation, Reconfigurable Manufacturing Systems (RMS)

    Issue

    Vol. 1 No. 1 (2018)

    Section

    Articles

    How to Cite

    [1]
    M. Asif Khan and S. Gupta, “AI-Based Dynamic Reconfiguration in Modular Smart Manufacturing Cells”, IJMLPA, vol. 1, no. 1, pp. 01–12, Mar. 2018, doi: 10.67228/3142788X/IJMLPA-2018PI4T7B.

  • Abstract

    The evolution of Industry 4.0 has brought forth an increasing demand for flexibility, adaptability, and intelligence in manufacturing systems. Modular smart manufacturing cells, with their inherent reconfigurability, are becoming essential components in modern production environments. This paper presents an AI-based framework for dynamic reconfiguration of such cells, enabling rapid adaptation to changing production demands, equipment failures, and optimization goals. Leveraging machine learning and real-time data analytics, the proposed system autonomously identifies optimal reconfiguration strategies with minimal human intervention. A case study is presented to validate the framework, demonstrating significant improvements in operational efficiency and system responsiveness. The results highlight the transformative potential of AI in achieving truly autonomous and resilient manufacturing systems.

  • References

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