## 2 Relevant Literature
### Technology and Data Aspects  
A DT can take several forms and usually utilises a combination of existing technologies, which differ from project to project. These include the following:  
Corporate Information Systems: DTs will often use corporate data, particularly that relating to manufacturing products, and this is usually located in some of the core business information systems. Typically, these may be an Enterprise Resource Planning (ERP) system such as Oracle or SAP, and other software packages with product-related data--PLM and Manufacturing Execution System (MES) applications, for example. Digital Thread: The digital thread is particularly relevant to shop floor product development and manufacturing DTs. It provides the linkage and connectivity between systems and technologies that provide the data required by the DT. [PERSON] [15] (para. 14) notes that the digital thread \"provides a communication framework to help facilitate an integrated and connected data flow of the product's data throughout its lifecycle. Digital thread enables accessing, transforming, integrating, and analyzing data from various different systems in the entirety of the product life cycle\". Internet of Things: [PERSON] [13] (para. 9) says of DT: \"its implementation is intertwined with another relatively new technology--IoT\", which is now widely deployed across many aspects of business operations [16]. A DT will use IoT generated data via a range of devices, monitors, and controllers for data collection within the physical and virtual environments. Edge processing: This refers to the processing of data near its point of collection (on the \"edge\") via IoT devices. This avoids delays and overheads that may be incurred by moving data to the cloud or elsewhere for onward processing. This also reduces possible network bottlenecks that have limited the viability of DT projects hitherto. Data Analytics/Artificial Intelligence: Many DT projects rely on data analytics to analyse and organise data to support DT operation and output. Advanced business intelligence tools like Power BI are often used for DT reporting and analysis purposes, and artificial intelligence (AI) applications may be developed to enhance system and product prediction, simulation, and visualization functions. Workflow/3-D Modelling: Many DTs use 2D or 3D computer-aided design images, although this is not always the case. Three-dimensional modelling technologies create virtual world images, products, and other objects. Workflow products are often linked with, and/or contain, 3D modelling capabilities. Extended Reality: Extended reality headsets and glasses provide users with virtual reality parallels of the physical world. virtual reality (VR), augmented reality (VR), and mixed reality (MR) technologies can be used individually or in combination with DTs. Most DT projects will involve implementing a combination of these technologies to construct the DT (Figure 1). Interoperability issues between technologies in the production environment are commonplace, and here a number of solutions are being developed, notably the asset administration shell (AAS). The AAS model for digital twins is promoted within Industry 4.0 and \"encompasses the interpretation of the digital representation of any production-related asset\", so that \"materials and products, devices and machines but also software and digital services have a respective digital version\" [17] (p. 160). It \"describes the technological features of an asset\" and \"was created to present data and information in a structured and semantically defined format, allowing for interoperability\" [18] (p. 2533). Some data from corporate information systems will usually be required to provide the basis for developing the simulation, and AAS can be used to support data exchange between manufacturing software applications [19]. Effective data management underpins DT applications, so data management technologies are of particular relevance.