Zero-Defect Manufacturing through AI-Enhanced IIoT Sensor Fusion

  • Authors

    • Marco Bianchi Operations Manager, Ferrari, Italy. Author

    DOI:

    https://doi.org/10.67228/3142788X/IJMLPA-2022PII2V9R

    Published 11-05-2022

  • Zero-Defect Manufacturing (ZDM), Industrial Internet of Things (IIoT), Sensor Fusion, Artificial Intelligence (AI), Defect Detection, Predictive Maintenance, Real-Time Anomaly Detection, Smart Manufacturing, Data Integration, Manufacturing Quality Control

    Issue

    Vol. 5 No. 2 (2022)

    Section

    Articles

    How to Cite

    [1]
    M. Bianchi, “Zero-Defect Manufacturing through AI-Enhanced IIoT Sensor Fusion”, IJMLPA, vol. 5, no. 2, pp. 01–11, Nov. 2022, doi: 10.67228/3142788X/IJMLPA-2022PII2V9R.

  • Abstract

    Zero-Defect Manufacturing (ZDM) represents a critical objective in modern industrial processes, aiming to eliminate product defects and enhance production quality. This paper explores the integration of Artificial Intelligence (AI) with Industrial Internet of Things (IIoT) sensor fusion as a transformative approach to achieving ZDM. By leveraging heterogeneous sensor data—such as visual, acoustic, vibration, and thermal inputs—and applying advanced AI algorithms for real-time sensor fusion and anomaly detection, the proposed framework enables proactive identification and prevention of defects in manufacturing workflows. We discuss the architecture of an AI-enhanced IIoT sensor fusion system, its implementation challenges, and demonstrate its effectiveness in reducing defect rates through a case study. The results indicate significant improvements over traditional quality control methods, paving the way for smarter, more adaptive, and autonomous manufacturing environments.

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