DIGITAL TWIN TECHNOLOGY for PREDICTIVE MAINTENANCE in INDUSTRY 4.0: A SYSTEMATIC REVIEW

Abstract

The development of Digital Twin (DTT) technology has revolutionized predictive maintenance (PdM) practices in the context of Industry 4.0. However, existing literature is still limited in comprehensively mapping the applications and strategic benefits of DTT. This research aims to fill this gap by exploring the application of DTT in PdM and its impact on operational efficiency. This study aims to identify and analyze the main applications and benefits of DTT in supporting PdM strategies in various industrial sectors. This research uses a Systematic Literature Review (SLR) approach by collecting and analyzing 22 scientific articles from leading databases, using the PRISMA protocol to ensure validity and reliability. Research findings show that DTT is able to increase operational efficiency through real-time monitoring, failure prediction, and reduced maintenance costs. In addition, DTT also contributes to extending asset life and improving operational safety. This research makes a significant contribution to the development of theory and practice in industrial asset management, by emphasizing the importance of DTT adoption to increase the effectiveness of PdM in the digital era.