In the present world, simulation has become an integral part of system development for every engineering discipline. Starting from solving design problems using numerical algorithms in the 1960s, simulation has taken us to the digital era where simulation is integrated into the life cycle of the particular product including design, testing, manufacturing, commissioning, operating, and decommissioning[6]. This process of evolution has opened the pathway to DT which is more versatile and dynamic than the physical twin concept. Ever since, the concept of Digital Twin (DT) T has become a reality expanding its outreach to various disciplines around the world including the maritime domain. The novel concept of the DT was first proposed in the year 2002 by Dr Michael Grieves, a leading scientist in the field of advanced manufacturing at the Florida Institute of Technology at a manufacturing engineers conference in Troy, Michigan. His idea was based on constructing digital information on the physical model on his own. This digital information is a replica of the data embedded in the physical system which will be connected with the physical system in the complete life cycle of a particular system/ component.
Technological development of the world is ever incrementing, and mankind is searching for innovative pathways to perform the tasks demanded by industries or services with improved efficiency and effectiveness. Digitalization of the world is boomed with the evolution of Cloud computing, Internet of Things (IoT) [1, [1][2]2], Big Data analytics, Virtual Reality (VR), Augmented Reality (AR), Artificial Intelligence (AI) [3] with Machine Learning, Deep Learning and Neural Networks, etc. The same has led the pathway to the development of the Cyber-Physical System (CPS) which is hailed as the epitome of the manufacturing and consumer service sector [4]. It is an automated system with a connection of physical reality featured with computing structures with smart networking tools. 5G and Tactile Internet [5] with the provision of ultra-reliable ultra-low-delay have enhanced communication and feedback between entities beyond oceans. To create the fusion between cyberspace and physical space, Digital Twin (DT) was introduced as a rational solution in associating the two extents. The concept of DT has become a real application within a limited time and some disciplines are surpassing the expectations and predictions made during the early conceptual inception of DT.
The initial conception of having a “Twin” was first implemented by NASA in their ‘Apollo’ program which used two identically built satellites in their missions [6]. One would go on the actual voyage in outer space while the other physical twin will remain in the laboratory in a controlled space, thus providing the mission scientists to analyze the conditions of the launched vehicle by comparing the conditions with the ground twin. The same helped them in parameter monitoring and fault analysis with a minimum data transfer between the two vehicles. A similar concept was utilized in the “Iron Bird” ground-based aircraft system testing platform by Airbus Industries, where a hardware simulator twin was used in system evaluation, design and testing while a simulated cockpit was utilized by the test pilots [7].
The combined usage of the two terms of ‘Digital + Twin’ first came up in a white paper related to the design for 3-D arterial phantoms in coronary arteries published in ‘Radiology’ Journal of RSNA (Radiological Society of North America) [8][8]. Authors have developed a realistic model of arteries using stereolithography using a computer-based model and they have referred to the computer-based design as a “digital twin”.
The novel concept of the DT was first proposed in the year 2002 by Dr Michael Grieves, a leading scientist in the field of advanced manufacturing at the Florida Institute of Technology at a manufacturing engineers conference in Troy, Michigan. His idea was based on constructing digital information on the physical model on his own. (Figure 1) This digital information is a replica of the data embedded in the physical system which will be connected with the physical system in the complete life cycle of a particular system/ component [9].
Figure 1. Reflection of the Original Conceptual Idea of DT by Dr M. Grieves in 2002.
The concept of DT was also brought up by NASA under their ‘Modeling, Simulation, Information Technology & Processing Roadmap at Technology Area 11’, a DT is introduced as a multiscale simulation of a vehicle or system with its own incorporated physics by optimally utilizing its physical data, sensor data and historical data, etc., in the effort of obtaining a real-time image related to the life of its corresponding physical twin at outer space. Since the concept of DT is practical and more realistic in nature, application for a single vehicle or even for interdependent multiple assets can be performed robustly. The anomalies that occurred during the manufacturing stage which could imperil the space missions can also be foreseen during its manipulation. DT can act as the backbone of any high-fidelity physical model, supporting the integrated vehicle health management system in evaluating historical data. With the input dataset, DT will enhance the mission success credibility of the craft with continuous monitoring and evaluation of the operational condition and the remaining running hours ahead. A robust DT model will assist damage mitigation or degradation by real-time data analysis/forecasting and suggest required changes in an ongoing space mission to enhance the life span leading to mission success [10]. Later, USAF came up with the concept of Digital Thread, where each USAF aircraft enters the fleet with its own DT. The DT will help in Structural Health Monitoring (SHM), and maintenance thus allowing calibration of the craft in its operation state by comparing the sensor readings of flight and DT. It also acts as a digital surrogate to plan the design, production, and acquisition phases of the project [11]. Though it was a clear definition for DT to be made considering the representation fidelity, model simulation capabilities, synchronization techniques, data collection and exchange attributes etc. It is also stated as a virtual representation of the real-world asset with an exchange of information in a predetermined frequency [12][12]. It is a digital representation of the active product service system which comprises preset characteristics, conditions, behaviours and properties [13].
Along with this concept, the Internet of Vehicles (IoVs) also has developed with the integration of Vehicular Ad-hoc Networks (VANETs) and the Internet of Things (IoTs) [16][17][16, 17]. These were more focused on land-based locomotives, but the notion is widely accepted by many industrial sectors. IoT has supported the real-time data handshake component of DT which has been the basement of existing topology. These also incorporate the diagnostics and prognostics embedded within the system architecture along with optimization of the process [16][16]. Risk Analysis and accident prevention with DT support is another frontier which is already been adopted by the aviation industry. The system verification of the Boeing 737 Max after initial failures is a great example [17][17]. It ultimately promotes the concept of Smart Products (SP) in various phases of the product life cycle which benefits the stakeholders in the user groups of the product or asset [18].
In the industry, DT is used under different names such as Cyber objects or digital avatars etc. The data flow between the DT and the physical unit will depend upon the purpose of the DT in the industry which uses Cyber Objects or Digital Avatars. Accordingly, the nomenclature of DT has been proposed based on the two-directional data link between the DT and the actual unit. Kritzinger W. et al., have categorized the digital counterparts of a physical object based on the data flow into three types; Digital Model, Digital Shadow, and DT [19] (Figure 2).
Figure 2. Difference of data topologies among Digital Model, Digital Shadow, and DT.
Induction of DT in marine vessels is already underway and FigureFigure 3 3 explains the summarized trail of actions for its induction. The seafaring sector has been developing its technologies targeting improvements in efficiency, emission controls, and ergonomic operating systems. Traditionally, most marine vessels, specifically surface vessels are built with two separate power systems. One is dedicated to the propulsion system and the second is used to cater for the electricity demands. In this context, most of the vessels were built using diesel engine-driven propulsion systems due to the ergonomic simple robust architecture and ease of maintenance. However, traditional systems are highly polluting the marine environment, which has been regulated by the IMO regulations. Shipbuilders are finding ways to suffice these new regulations in their designs. Electrification of the vessels has been an ideal solution to gratify the emission control guidelines [20][20].
Figure 3. Pathway of Digital Twin Technology within the Shipping Industry.
3.1. Ship Electrification
The first electrical propulsion system was introduced by Russian scholar Boris Jacobi which was a paddle boat driven by an electric motor. Due to the low battery capacity and efficiency, the maximum speed achieved was 1.5knots which discouraged the development of a system for a long time ahead [21].[21] In 1903 Swedish shipyard ASEA built the river tanker ‘Vandal’ as the first vessel to carry a diesel-electric propulsion system.[22] [22].At the end of WWII, more emphasis was received on the development of electrical propellers and ships like the Ice Tanker ‘Uikku’ and Passenger Ferry Queen Mary 2. Uikku was the first ship to be installed with an Azipod propulsion system where the main electric motor was installed in a separate gondola which could direct the thrust with a 360o control. RMS Queen Mary 2 is a luxury cruise liner propelled by hybrid diesel turbo-electric propulsion with four 18MW Azipods driven by two gas turbine generators and four diesel engine-driven generators. This propulsion topology has provided navigation flexibility along with economical gains in varying speed demands and different passage legs while complying with emission control protocols [23].[23]
Integrated Full Electrical Propulsion (IFEP) is reducing fuel consumption heavily by avoiding the low load portion of fuel consumption curves in sharing the load of propulsion along with ships service loads including the weapon systems [24][24]. It is far superior to the standard propulsion systems like Combined Diesel Electric and Gas (CODLAG) system or Combined Diesel Electric or Gas (CODLOG) [25][25]. The latest US Navy stealth Destroyer USS Zumwalt was commissioned in the year 2016 as the first full-electric warship equipped with an integrated power system [26][26]. Further, with the initial project of MS Medstraum Norway has implemented the world’s first battery-powered ferries to transfer vehicles and people with greener environmental insights [27][27].
With the development of IFEP, ship designers further developed the concept of All-Electric Ships (AES) [28]. AES concept has provided high redundancy and mission capability even at a slight initial cost. At present, most of the high-end naval ship projects have opted for this technology due to the advantages posed by the electrical-based high-power navigation, communication, and weapon systems. Royal Navy Type 45 Destroyers and the aircraft carrier HMS Queen Elizabeth[29] [29] are a few examples of AES-based power topology. Hybrid powering topology is also developed and implemented to achieve the redundancy and advantages of both mechanical and electrical drives.
Benefits of the Electrification in Marine Vessels: [30]: [30]
3.2. Ship Digitalization
Along with the electrification process, digitalization also has become a key innovative trend in every operation in the maritime sector due to its efficiency, effectiveness, superlative performance, etc. New tools in designing, performance evaluation, simulation, and information safety are being introduced and the same is getting improved day by day which further assists in producing more robust models. As per the digitalization service development framework proposed by Erikstad S., the process of digitalization of the maritime sector can be achieved through two different approaches [31].
The marine industry will be able to gain the full merits of digitalization through the service-driven approach starting from the design phase of the vessel. However, existing platforms can be improved through the second approach to par with the present smart functions. Digitalization is further considered an effective, innovative, and optimized method enabling products and services as per Industry 4.0 [32][32]. Asset-intensive industries such as shipping, oil, gas, and energy etc. are looking for innovations that increase efficiency and reduce the cost while effectively managing operational risks and security. Main configurations such as the navigation system, power system and automation/control system are getting fully digitalized leaving the old analogue systems obsolete. Integrated Platform Management Systems (IPMS) available in present ships can link all the above system architectures into a centralized topology, thus providing more ergonomic operation and increased domain awareness for all stakeholders.
With the availability of satellite communication, the onboard modules are easily linked with onshore supporting facilities, rather than opening the standalone data infrastructures onboard holistically to shore operators (Figure 4). As per the Guidance Notes of the American Bureau of Shipping on Smart Function Implementation, they have highlighted the importance of having a DT to support the data infrastructure in onshore processing during Big Data Transfer [33][33]. It will allow operators to continuously collect, transmit, manage, and analyse the data for real-time monitoring, increase awareness and decision making both human-initiated decisions and autonomous command & control. It further enhances the ships' situational awareness, navigational safety, and reduction of crew fatigue and human error-related accidents.
Figure 4. Realtime Satellite Data Link of Smart Ships.
The main requirement of a smart ship can be defined as the ability to perform the intended functions autonomously. The transformation from a traditional human-based system to full autonomy is achieved with the digitalized platforms in the electrified vessels. Smart ships highly depend upon the digitalized marine eco-system which is focussed on autonomous operation.
This evolution has opened the doorway for DT technology to enter the shipping industry by bringing all experts into a centralized topology, providing powerful analysis, understanding, and diagnostics that are crucial for decision-makers in every stage of the ship's life. This iteration has made the pathway for Ship DT (SDT) which incorporates the basic topology of the DT concept to develop and implement for various applications within the maritime domain. Limits are endless in this effort, but this DT primarily can be based on three main virtues namely, Asset Representation, Operational Behaviour Model, and Parameter Measurement/Monitoring. The application of the technology can further be divided into the design phase, manufacturing phase, service phase and retire phase [34][34]. This encompasses every action that the ship must undergo during her life cycle. It will support the actions from preliminary conceptual design and optimization to the final validation of the model. The developed DT model will then assist the supply and production measures during her building at the shipyard till final performance trials and commissioning. During the entire service period, DT will be the key tool to performing intended functions during her operational phase. Routine upkeeping of the vessel to Planned Preventive Maintenance (PPM) to Conditioned Based Predictive Maintenance (CBPM) will be functioning through the DT model with all historical data accumulated in condition monitoring, prognostics, and diagnostics and even the simulated testing of the systems/ components.
The virtues of the existing functionality of any surface vessel require a clear understanding of the planned design specifications along with the precise functionality of the various components, systems, and departments of the vessel. Developers of the DT are focused mainly on three user groups for the system, Company, Operators and Researchers. DT will continuously communicate with the physical ship to update its data as per the real world to support the above-mentioned stakeholders with different demands during the complete product life cycle. Starting from the marketing phase of the vessel, DT will be functioning till the decommissioning stage of the ship. Designing as per the end user requirement and validation of the design with a 3D representation of the entire ship layout can be used extensively before the building phase.
DT of a fully autonomous ship will act as a complete controller of the vessel while regular manned vessels will be acted as a Digital Model or Digital Shadow to maintain the required data structure. DT solution should be capable of performing the following actions to provide service to the three main stakeholders: onboard crew (if present), shore operator and researcher/engineer. (Figure 5)
Figure 5. Direct Stakeholders of a Ship DT System.
A ship DT should be able to replicate all the Smart Functions[33] [33] of a digitalized surface ship including the following mandatory requirements;
Apart from the above functions, a robust communication link is to be established between the ship and the shore operator to obtain real-time situational awareness with complete control during the voyage. Digital Images can act as a model, shadow or twin depending on the data handshake method. DT can be utilized to monitor and maintain the autonomous control of the vessel including self-navigation and collision avoidance. The formidable internal verification system generated due to the DT architecture will enhance the existing conceptual design optimization using virtual testing and intelligent process monitoring till the finalized model is developed [35][35].
Since the data handled in a fully integrated DT Process Model (DTPM) will be large and complex, therefore, the model must be composed of Design Data (DD), Process Data (PD), Process Perception Data (PPD), Historical Running Data (HRD) and Simulation Data (SD) targeting the whole product life cycle [36][36]. Separate component schema for serialization of various components can be implemented covering the asset data, Analysis and measured data of different segments of ships and can be shared among various stakeholders [37] (Figure 6).
Figure 6. Overall Task Distribution of a DT-based Framework.
The physical and control architecture of the future ships is also evolving each day with new concepts in improving the efficacy and efficiency of the vessels targeting economic and emission goals. Designing, testing, validating, and implementing a robust Digital Twin (DT) model for a surface ship will provide seamless support for the functioning of the ship/craft to its intended operation despite being an unmanned craft or a conventional crewed vessel.
References