Proceedings of the International Conference on Advancements in Materials, Design and Manufacturing for Sustainable Development, ICAMDMS 2024, 23-24 February 2024, Coimbatore, Tamil Nadu, India

Research Article

Industry 4.0 Approaches for Sustainable Real-Time Monitoring and Predictive Maintenance of Conveyor Systems

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  • @INPROCEEDINGS{10.4108/eai.23-2-2024.2347031,
        author={Somasundara Vinoth  K and Haresh  R and Dharanesh  D and Sri Athrukshna  B and Srinithi  K P},
        title={Industry 4.0 Approaches for Sustainable Real-Time Monitoring and Predictive Maintenance of Conveyor Systems},
        proceedings={Proceedings of the International Conference on Advancements in Materials, Design and Manufacturing for Sustainable Development, ICAMDMS 2024, 23-24 February 2024, Coimbatore, Tamil Nadu, India},
        publisher={EAI},
        proceedings_a={ICAMDMS},
        year={2024},
        month={6},
        keywords={sustainability conveyor belts industry 40 real time monitoring predictive maintenance},
        doi={10.4108/eai.23-2-2024.2347031}
    }
    
  • Somasundara Vinoth K
    Haresh R
    Dharanesh D
    Sri Athrukshna B
    Srinithi K P
    Year: 2024
    Industry 4.0 Approaches for Sustainable Real-Time Monitoring and Predictive Maintenance of Conveyor Systems
    ICAMDMS
    EAI
    DOI: 10.4108/eai.23-2-2024.2347031
Somasundara Vinoth K1,*, Haresh R1, Dharanesh D1, Sri Athrukshna B1, Srinithi K P1
  • 1: PSG College of Technology
*Contact email: ksv.prod@psgtech.ac.in

Abstract

Industry 4.0 techniques play a pivotal role in revolutionizing real-time monitoring and predictive maintenance of conveyor systems, which are critical assets in modern industries to achieve sustainability. By synthesizing insights from various studies, the article provides a comprehensive perspective on the challenges, emerging trends, and opportunities within this dynamic field. The convergence of sensor technology, machine vision, data analytics, and IoT empowers conveyor systems to proactively address maintenance needs, minimize disruptions, and optimize performance while also promoting sustainability and minimizing environmental impact. Additionally, the multifaceted challenges associated with implementing predictive maintenance, such as data heterogeneity and model maintenance, are discussed, along with the introduction of advanced methodologies for specific issues like belt tear detection and foreign object identification. This highlights the transformative potential of Industry 4.0 techniques in enhancing conveyor systems' operational efficiency and reliability within the context of sustainability, contributing to a greener and more responsible industrial landscape.