Digital Twins (DTs) are becoming popular in Additive Manufacturing (AM) due to their ability to create virtual replicas of physical components of AM machines, which helps in real-time production monitoring. Advanced techniques such as Machine Learning (ML), Augmented Reality (AR), and simulation-based models play key roles in developing intelligent and adaptable DTs in manufacturing processes. However, questions remain regarding scalability, the integration of high-quality data, and the computational power required for real-time applications in developing DTs. Understanding the current state of DTs in AM is essential to address these challenges and fully utilize their potential in advancing AM processes. Considering this opportunity, this work aims to provide a comprehensive overview of DTs in AM by addressing the following four research questions: (1) What are the key types of DTs used in AM and their specific applications? (2) What are the recent developments and implementations of DTs? (3) How are DTs employed in process improvement and hybrid manufacturing? (4) How are DTs integrated with Industry 4.0 technologies? By discussing current applications and techniques, we aim to offer a better understanding and potential future research directions for researchers and practitioners in AM and DTs.

翻译：数字孪生（DTs）因其能够创建增材制造（AM）设备物理组件的虚拟副本，从而有助于实现实时生产监控，正日益在增材制造领域受到欢迎。机器学习（ML）、增强现实（AR）以及基于仿真的模型等先进技术，在开发制造过程中智能且适应性强的数字孪生方面发挥着关键作用。然而，在开发数字孪生时，其可扩展性、高质量数据的集成以及实时应用所需的计算能力等方面仍存在问题。理解数字孪生在增材制造中的现状，对于应对这些挑战并充分发挥其在推进增材制造工艺方面的潜力至关重要。鉴于此机遇，本研究旨在通过探讨以下四个研究问题，对增材制造中的数字孪生提供一个全面的概述：（1）增材制造中使用的主要数字孪生类型及其具体应用是什么？（2）数字孪生的最新进展与实施情况如何？（3）数字孪生如何应用于工艺改进与混合制造？（4）数字孪生如何与工业4.0技术集成？通过讨论当前的应用与技术，我们旨在为增材制造和数字孪生领域的研究人员与实践者提供更深入的理解以及潜在的未来研究方向。