Nowadays, global competition in the manufacturing sector is increasingly fierce. Thus, global manufacturing companies must have a manufacturing system that ensures the production of reasonably priced, high-quality products, while meeting the needs of various customers. To address this issue, smart manufacturing should be implemented by adopting various information and communication technologies and convergence with existing manufacturing industries. One of the key technologies required for the implementation of smart manufacturing is a cyber-physical system (CPS). One of the major factors for the successful construction of a CPS is digital twin (DT). In this paper, we propose a standards-based information model for building a DT application, which is a key technology of a CPS-based integrated platform, by overcoming the heterogeneous device environment of global manufacturers and using data collected from various manufacturing sites. Furthermore, we propose a concept of modeling and simulation-based DT application. The DT application proposed in this study facilitates monitoring, diagnosis, and prediction at manufacturing sites using real-time data collected from various environments by ensuring interoperability. Moreover, its validity is verified by applying the technology to a global manufacturing company of automotive parts.