In the light of increasing global competition, the establishment of smart factory of which smart production is an integral part is indispensable for manufacturing companies’ competitiveness and sustainability. The establishment of interoperability for factory resources and the improvement of manufacturing companies’ real-time capability are important requirements to fulfil the objectives of smart production. Manufacturing companies could achieve these by developing its virtual capability through the development of digital twin. As such, the focus of this thesis was to investigate the infrastructure requirements for developing digital twin (DT) to enable smart production. To address the research issues, a qualitative approach involving a systematic literature review (SLR) to collect theoretical data, case study to enable an in-depth investigation of the research issues, and interview, collection of documents, as well asobservation to obtain empirical data was adopted. Findings from the analysis of empirical and theoretical data reveals that the strength of DT in assisting the establishment of smart production lies on the fact that, digital twin is the exact replica of the real-world production resource, and that the virtual models are permanently tied to their real-world twins throughout their lifespan. Findings also reveals that, physical model (consisting of equipment, machines, operators, system, or entire process), data model (consisting of data for virtual modelling and data for smart production management), and virtual model (consisting of geometric, physics, behaviour, and rules models) are the three main infrastructures that constitute a DT. In addition to these, findings equally reveal that developing DT to enable smart production requires the integration of the three main infrastructures that constitute a DT. A model depicting the main infrastructures that makes a DT is presented by figure 4. At the same time a model that depicts the path to develop digital twin to enable smart production is presented by figure 5.