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Productivity Enhancement in the Indian Auto Component Manufacturing Supply Chain Through IoT, Digital Twins with Generative AI, and Stacked Encoder-Enhanced Neural Networks

Author

Listed:
  • Tushar D. Bhoite

    (MES’s Wadia College of Engineering, Wadia College Campus)

  • Rajesh B. Buktar

    (BVB’s Sardar Patel College of Engineering, Andheri (W))

  • Parikshit N. Mahalle

    (Vishwakarma Institute of Technology)

  • Mohan P. Khond

    (COEP Technological University, A Unitary Public University of Government of Maharashtra (Formerly College of Engineering Pune))

  • Ganesh S. Pise

    (Vishwakarma Institute of Technology)

  • Yogeshrao Y. More

    (PES’s Modern College of Engineering)

Abstract

The Indian auto component manufacturing sector has long struggled with inefficient decision-making and limited real-time data use. This research investigates how Industry 4.0 technologies, specifically the Internet of Things (IoT), digital twins, generative artificial intelligence, and advanced neural networks can revolutionize this sector. IoT-enabled smart sensors support real-time monitoring and predictive maintenance. Digital twins replicate physical assets virtually, aiding scenario simulation and process improvement. Generative AI facilitates defect detection, process optimization, and intelligent decision-making. A novel Bayesian Network-Stacked Encoder-Puma Optimizer (BN-SE-PO) model further improves anomaly detection, pattern recognition, and automation. Empirical results show that IoT-based systems achieve 85% efficiency, 30% downtime, 40% cost savings, and 90% quality significantly outperforming conventional approaches. This study provides a robust framework for implementing AI-driven technologies to transform productivity, reliability, and supply chain efficiency in the Indian auto component industry.

Suggested Citation

  • Tushar D. Bhoite & Rajesh B. Buktar & Parikshit N. Mahalle & Mohan P. Khond & Ganesh S. Pise & Yogeshrao Y. More, 2025. "Productivity Enhancement in the Indian Auto Component Manufacturing Supply Chain Through IoT, Digital Twins with Generative AI, and Stacked Encoder-Enhanced Neural Networks," SN Operations Research Forum, Springer, vol. 6(4), pages 1-27, December.
    • Handle: RePEc:spr:snopef:v:6:y:2025:i:4:d:10.1007_s43069-025-00522-0
    DOI: 10.1007/s43069-025-00522-0
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