Intelligent Robotic Pick-and-Sort Systems for Dynamic Production

  • Authors

    • Dr. Nandhini Ravi Assistant Professor, VIT University, India. Author

    DOI:

    https://doi.org/10.67228/30715725/IJIARE-2021PII4S6X

    Published 10-04-2021

  • Intelligent Robotics, Pick-and-Sort System, Dynamic Production Lines, Industry 4.0, Artificial Intelligence, Machine Learning, Computer Vision, Deep Learning, Industrial Internet of Things (IIoT), Robotic Manipulators, Motion Planning, Smart Manufacturing, Automation

    Issue

    Vol. 4 No. 2 (2021)

    Section

    Articles

    How to Cite

    [1]
    N. Ravi, “Intelligent Robotic Pick-and-Sort Systems for Dynamic Production”, IJIARE, vol. 4, no. 2, pp. 01–15, Oct. 2021, doi: 10.67228/30715725/IJIARE-2021PII4S6X.

  • Abstract

    Industry 4.0 has transformed conventional manufacturing into intelligent, automated, and connected production environments. Intelligent robotic pick-and-sort systems improve productivity, flexibility, product quality, and operational efficiency by overcoming the limitations of traditional rule-based automation. This paper presents an AI-enabled framework integrating computer vision, deep learning, robotic manipulation, edge computing, and the Industrial Internet of Things (IIoT) for dynamic manufacturing applications. Convolutional Neural Networks (CNNs) provide accurate object detection and classification, while intelligent motion planning and reinforcement learning optimize robotic grasping and movement. Sensor fusion, edge computing, and IIoT connectivity enable real-time monitoring, low-latency decision-making, and predictive maintenance, improving system reliability and reducing downtime. Performance is evaluated using object detection accuracy, sorting accuracy, processing time, throughput, energy efficiency, and overall system reliability. Compared with conventional automation, the proposed framework offers greater adaptability, higher sorting accuracy, and improved operational performance in dynamic production environments. The study concludes that intelligent robotic pick-and-sort systems are a key technology for smart factories, supporting flexible manufacturing, mass customization, and sustainable industrial production, with future opportunities in digital twins, explainable AI, cloud-edge intelligence, and collaborative human-robot systems.

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