Digitalization & Sustainability Review

Peer Reviewed Article

Vol. 2 No. 1 (2022)

AI-Powered Predictive Maintenance for Industrial IoT Systems

Submitted
3 January 2022
Published
13-02-2022

Abstract

AI and IoT systems have enabled AI-powered predictive maintenance, a proactive approach to industrial maintenance that predicts and prevents equipment breakdowns. This study examines AI-powered predictive maintenance in Industrial IoT systems to improve predictive accuracy, maintenance schedules, and operational efficiency. The paper covers AI and IoT integration, significant machine learning algorithms in maintenance, data integration, cybersecurity issues, and workforce training implications using secondary data. According to the findings, AI-powered predictive maintenance improves predictive accuracy, real-time monitoring, cost savings, safety, and scalability. Data integration issues and cybersecurity dangers increase the need for robust policy frameworks. Policy should promote interoperability standards, cybersecurity protocols, and workforce training to solve these issues and promote AI-powered predictive maintenance. This study concludes that AI-powered predictive maintenance can transform industrial processes and ensure digital sustainability and competitiveness.

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