Fault Diagnosis and Prognosis using IoT in Industry 5.0
Abstract
This research delves into the pivotal role of the Internet of Things (IoT) in fault diagnosis and prognosis within the context of Industry 5.0. As manufacturing environments evolve towards greater connectivity and intelligence, Industry 5.0 emphasizes the seamless integration of human expertise with advanced technologies. In this transformative landscape, IoT emerges as a critical enabler for real-time monitoring, data acquisition, and predictive analytics. The abstract explores the application of IoT in fault diagnosis, detailing how sensor-rich environments facilitate the detection of anomalies and deviations from normal operations. Furthermore, the chapter investigates the prognostic capabilities of IoT, where predictive analytics and machine learning algorithms anticipate potential faults and prescribe proactive maintenance strategies. The synthesis of human expertise with IoT-driven insights in Industry 5.0 paves the way for enhanced operational efficiency, reduced downtime, and optimized resource utilization. This chapter contributes to the discourse on the convergence of IoT and Industry 5.0, providing insights into the transformative potential of proactive fault diagnosis and prognosis in modern industrial settings.
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References
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