## 4 Discussion
Based on this, they defined a DT with three components: a digital master, a digital shadow, and a linking mechanism. In addition, the scope and type of a DT are divided into eight dimensions, with each dimension having three to four levels. The dimensions include integration breadth, connectivity mode, update frequency, CPS intelligence, simulation capabilities, digital model richness, human interaction, and product life cycle [14]. [PERSON] et al. analyzed 50 papers, eight patents, and six best practices of leading companies. This review is focused on industrial DT applications in general; thus, current developments of DT in the industry, as well as DT applications, are described. The literature was assigned to the application areas of design, production, PHM, and others, showing that PHM is the most popular application area for DT. The importance of DT modeling is highlighted, as well as the fact that no consensus can be found in how to build a DT model. The authors conclude that cyber-physical fusion is one of the major challenges of DT and a lack of universal frameworks is identified [12]. Researching a different application area, the literature review of [PERSON] et al. is focused on DT for warehouse processes, stating that the development of DT in this area is still at the initial stage and that DES models must be enhanced with real-time functionalities [35]. This paper complements the previous reviews on DTs by adding non-investigated aspects focusing on production logistic processes. First, the most used definitions of DTs in this application area are analyzed and discussed, highlighting similarities and differences between these definitions. As a result, the main components and important functionalities of a DT have been pointed out. In addition to mentioned concepts and reviews, 20 case studies are analyzed in more detail in a second step and evaluated based on the five dimensions of [PERSON] et al. Due to the integral role of the VM in a DT, the approaches and technologies used to create a VM are analyzed and discussed. Together with the analysis of the pursued optimization goals, this provides a starting point for new developments based on already existing approaches and an overview of the potential benefits in this area. The literature analyzed reveals some research gaps and future research directions. It has been shown that there are different approaches for the implementation of a DT for production logistics. Therefore, different requirements must be met as well. These requirements for a DT implementation have not been systematically surveyed and addressed so far. All the literature analyzed deals with discrete production systems, without addressing logistics challenges in the process industry. Despite the description of various information sources, no data models could be found that would allow the DT to be independently connected via APIs. As described, much of the analyzed literature deals with the creation of VMs. Thus, the real-time capabilities and the connection with the physical entity as well as the service system are often neglected. This should be considered in more detail in future research. Overall, only a few fully implemented DTs in industrial environments for production logistics processes could be found. To comprehensively determine the potential benefits in real-world applications in this area, further fully implemented DTs in industrial environments need to be investigated. Although the use of DTs within the design phase is discussed, virtual commissioning with DT technologies is not addressed at all. This is supported by a review by [PERSON] et al., focusing on virtual commissioning and showing no hits for application in logistics processes [53]. Due to the close relationship between DT and CPS concepts, in future literature reviews, this term should be included to extend the search.