## 2 Relevant Literature
### Relevant Theory and Models  
There are a number of implementation frameworks in the existing literature, some of which are specific to implementing certain types of DTs, or DTs for specific purposes. For instance, [PERSON] et al. [22] and [PERSON] et al. [23] proposed frameworks to optimise factory layout designs. [PERSON] et al. [24] focused on developing a framework to improve the simulation functionality of a DT using machine learning and process mining techniques. [PERSON] et al. [25] (p. 12) developed a \"small-scale digital twin implementation framework\", in which they identified Resources (\"labour, capital and materials\"), Technology, and Digital Transformation (\"enabling digital processes such as simulation, diagnostics, prognostics\") as the \"high-level requirements\" for DT projects. [PERSON] et al. [26], in their case study of a DT in technical product development, suggest five key dimensions for DT projects, based on earlier work by [PERSON] et al. [27]. These are people, process, data, product, and tools. The International Organization for Standardization (ISO) detailed requirements for a DT framework [28] in which it partitions a DT into four layers defined by standards (Figure 2). The lowest layer describes the observable manufacturing  
Figure 1: Digital Twin technology components and application areas. elements--the items that need to be modeled in the DT. The second layer is the device communication entity which \"collates all the state changes of the observable manufacturing elements, and sends control programs to those elements when adjustments become necessary\" (para. 2). The third layer is the digital twin entity, which reads the data collated by the device communication entity and uses the information to update its models. The fourth layer contains user entities. These are applications that use the digital twins to enhance manufacturing efficiency. They are \"legacy applications such as ERP and PLM, and new applications that make processes work more quickly\" (para. 3). The ISO 23247 framework is based on the Internet of Things and also includes a \"cross system entity\", linking shop floor devices, the digital twin, and main applications in the fourth \"user entity\" layer. The three change dimensions of technology, process, and people have been used as a framework to analyse IT projects [29; 30] and develop IT strategy [31] in the digital era. This is somewhat similar to the approach adopted by [PERSON] et al. [25] (p. 12) and, in particular, the framework put forward by [PERSON] et al. [26] for implementing DT projects. Their framework includes process and people change dimensions, plus data and tools (which can be viewed as part of the technology dimension), and the product itself--the focus of the DT simulation. The significance of the people change dimension is emphasised by [PERSON] et al. [26] (p. 384), who note \"current barriers between departments have to be considered as the usage of a twin also changes the significance of certain tasks or even departments of the product development process\". In terms of process change, the authors note \"many of the processes in a company will change with the introduction of a twin, as for example some simulations will be conducted automatically instead of a simulation assignment being handed over from one department to the other\". They also note that \"the generation and usage of data, especially from the use phase of products, has to be altered in many places to enable the implementation of a Digital Twin\" (p. 385). More recently, [PERSON] et al. [32] put forward a \"business modelling approach\" for digital twin projects, which is a 10-step guide to implementing a DT and transitioning to new processes (Figure 3). In a similar vein, [PERSON] and [PERSON] [7], in their analysis of DT implementation, identify a number of key challenges, including terminology, standardization, organizational culture, technology maturity, and automation.