<![CDATA[Engineering systems have been profoundly altered by the quick development of digital technologies, especially with the use of Digital Twin technology. The purpose of this project is to investigate how digital twins facilitate predictive maintenance and real-time monitoring within engineering systems using a literature review approach. The method involves systematically analyzing and synthesizing findings from recent scholarly articles, conference proceedings, and technical reports related to Digital Twin applications. The results indicate that The development of virtual copies of real systems is made easier by digital twin technology, enabling continuous data integration, performance simulation, and anomaly detection. Through real-time monitoring, engineering systems can achieve improved operational transparency and faster decision-making. Furthermore, the implementation of predictive maintenance supported by Digital Twin reduces downtime, optimizes maintenance scheduling, and minimizes operational costs by predicting potential failures before they occur. However, challenges such as data integration complexity, high implementation costs, and cybersecurity risks remain significant barriers. This study highlights that despite these challenges, Digital Twin technology presents substantial opportunities for enhancing efficiency, reliability, and sustainability in modern engineering systems. Future research is recommended to focus on scalable frameworks and secure data architectures to maximize its implementation.]]>
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