Digital Twin (DT) technology has been the driving force in the industry 4.0 and future industrial landscapes by providing real-time coordination between physical assets and virtual twins. In smart manufacturing, DTs provide never-seen-before simulation, prediction, and optimization in the product lifecycle. This review delivers an in-depth evaluation of the latest trends in integrating Digital Twins in the manufacturing system. The paper starts by tracing the conceptual development and architecture of the DTs, followed by the in-depth exploration of the enabling technologies like IoT, artificial intelligence, edge computing, and cyber-physical systems. Industrial applications in key areas like predictive maintenance, process optimization, and human–machine collaboration have been assessed in the automotive, aerospace, and additive manufacturing sectors. The paper also covers the essential challenges in the areas of standardization, security in the sphere of data, real-time processing, and interoperability. The latest developments in the areas of cognitive twins, sustainability-oriented DTs, and integrating them into upcoming paradigms like Industry 5.0 have been considered. The paper concludes by the exploration of present-day research gaps and contributing future directions for the deployment of scalable, secure, and intelligent DTs in the field of manufacturing. The paper aims to act as the foundation for the researcher and practitioner community by bringing academic understanding and industrial relevance in close proximity to the application areas of the Digital Twins, ensuring the latter's position as the strategic facilitator for the future-day excellence in the field of manufacturing.
Kadam et al. (Mon,) studied this question.