Utilization AI for Predictive Maintenance in IoT-Enabled Industrial Systems

Abstrak

Integrating Artificial Intelligence (AI) with Internet of Things (IoT) technologies has emerged as a transformative approach to predictive maintenance in industrial systems. This article aims to explore the use of AI for predictive maintenance in IoT-based industrial systems, aiming to improve operational efficiency and asset reliability. The research method uses a systematic literature review (SLR) through empirical studies and real-world case scenario analysis; this research highlights the potential benefits of AI-based predictive maintenance, including proactive equipment failure detection, maintenance schedule optimization, and reduced downtime. However, implementation challenges such as data quality, interoperability, and cybersecurity must be addressed to realize the benefits of AI-based predictive maintenance fully. The research results identify emerging trends and future directions in AI-powered predictive maintenance, emphasizing the importance of continuous innovation and exploration of advanced technologies to drive sustainable growth in the industrial environment. So, integrating AI algorithms with IoT sensors enables proactive identification of equipment failures, optimization of maintenance schedules, and, ultimately, enhancement of operational efficiency and asset reliability.