# Ship's Digital Twin--A Review of Modelling Challenges and Applications
## 1 Introduction  
Although the concept of a digital twin (DT) can be found described in the literature, e.g., as in [1], and although a digital twin as a term is being used increasingly in different fields of technical sciences, the concept remains unclear mostly in the way of differentiating a DT concept from an ordinary computer simulation model. Furthermore, the concept is sometimes related to a cyber-physical system (CPS) as described in [2; 3; 4; 5], a part of the CPS as described in [6], or as a digital model and digital shadow, which can be combined to form a DT as described in [7].  
What makes a digital twin of a ship (SDT) and how to create one in a systematic and reliable fashion were motives for this research. Therefore, this paper presents a review analysis of the SDTs developed so far, based on the available literature. It presents the concept, identifies the steps and methods used in the SDT formulation process, as well as communication protocols used in different stages of the process. The applications of the SDT are numerous, and some of them are presented in this paper.  
Furthermore, the paper proposes a four-step iterative procedure for the SDT development that is based on data acquisition, data processing, modelling, and model validation. Recalibration of the model using the new data is possible, thus making the process iterative, and it is performed once the new input data become available. In the same way, SDT outputs are used on a real object depending on the level of connectivity between the SDT and the ship. Thus, the connectivity and communication level between the ship and its DT is essential.  
The SDT concept relies on data it would expect for the advanced data modelling methods, such as artificial intelligence, used in [8; 9; 10; 11; 12], and data-driven modelling (DDM), used in [12; 13; 14], to take prime in this area. However, conventional mathematical models have often been used for the purposes of creating an SDT, as in [15; 16; 17; 18; 19; 20; 21; 22].  
SDT applications found in papers [8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27] were analysed according to the standards of the DT formulation process set in this paper. For every case study, methods used to form a DT, applications, and steps of the DT formulation process were analysed. Some of the common applications are maintenance and condition monitoring, as in [8], system identification for fault detection, as in [9], cost reduction, as in [17], remote control and monitoring, as in [24], and various applications, as in [21], whereas ships' systems can be modelled for the purpose of decision-making support, as described in [23].  
The simulation aspect of a DT concept was reviewed in [28], while ref. [29] discussed challenges in DT application for maintenance of marine equipment. Furthermore, ref. [30] analysed advantages and contrasted them with challenges, thus identifying benefits of DT implementation, while ref. [31] addressed the main research focus and future fields of interests regarding the DT concept. The literature review for DT concept applications for the purpose of maintenance was discussed in [32], while ref. [33] conducted a systematic literature review and analysed DT trends and strategies.  
Main areas that need to be researched in order to efficiently implement a DT both in the maritime industry and in general were identified in [34] and include: sensor technology, signal processing and filters, modelling methods such as machine learning (ML), DT architectures, and application programming interfaces (API).  
The review analysis presented in this paper gives some direction to the formulation process of an SDT and suggests further research that should be performed in that area.