Digital twin

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A digital twin is a digital model of an intended or actual real-world physical product, system, or process (a physical twin) that serves as a digital counterpart of it for purposes such as simulation, integration, testing, monitoring, and maintenance. [1] [2] [3]

Contents

A digital twin is set of adaptive models that emulate the behaviour of a physical system in a virtual system getting real time data to update itself along its life cycle. The digital twin replicates the physical system to predict failures and opportunities for changing, to prescribe real time actions for optimizing and/or mitigating unexpected events observing and evaluating the operating profile system. [2] Though the concept originated earlier (as a natural aspect of computer simulation generally), the first practical definition of a digital twin originated from NASA in an attempt to improve the physical-model simulation of spacecraft in 2010. [4] Digital twins are the result of continual improvement in modeling and engineering.

In the 2010s and 2020s, manufacturing industries began moving beyond digital product definition to extending the digital twin concept to the entire manufacturing process. Doing so allows the benefits of virtualization to be extended to domains such as inventory management including lean manufacturing, machinery crash avoidance, tooling design, troubleshooting, and preventive maintenance. Digital twinning therefore allows extended reality and spatial computing to be applied not just to the product itself but also to all of the business processes that contribute toward its production.

History

The first digital twin, although not labeled as such, came about at NASA during the 1960s as a means of modelling the Apollo missions. NASA used simulators to evaluate the failure of Apollo 13's oxygen tanks. [5] The broader idea that became the digital twin concept was anticipated by David Gelernter's 1991 book Mirror Worlds. [6] [7] The digital twin concept, which has been known by different names (e.g., virtual twin), was first called "digital twin" by Hernández and Hernández in 1997. [8] [9]

An early digital twin concept by Grieves and Vickers Digital Twin Concept of Grieves and Vickers.png
An early digital twin concept by Grieves and Vickers

The digital twin concept consists of three distinct parts: the physical object or process and its physical environment, the digital representation of the object or process, and the communication channel between the physical and virtual representations. The connections between the physical version and the digital version include information flows and data that includes physical sensor flows between the physical and virtual objects and environments. The communication connection is referred to as the digital thread.

The International Council of Systems Engineers (INCOSE) maintains in its Systems Engineering Book of Knowledge (SEBoK) that: "A digital twin is a related yet distinct concept to digital engineering. The digital twin is a high-fidelity model of the system which can be used to emulate the actual system." [10] The evolving US DoD Digital Engineering Strategy initiative, first formulated in 2018, defines a digital twin as "an integrated multiphysics, multiscale, probabilistic simulation of an as-built system, enabled by a Digital Thread, that uses the best available models, sensor information, and input data to mirror and predict activities/performance over the life of its corresponding physical twin." [11]

Types

Digital twins are commonly divided into subtypes that sometimes include: digital twin prototype (DTP), digital twin instance (DTI), and digital twin aggregate (DTA). [12] The DTP consists of the designs, analyses, and processes that realize a physical product. The DTP exists before there is a physical product. The DTI is the digital twin of each individual instance of the product once it is manufactured. The DTI is linked with its physical counterpart for the remainder of the physical counterpart's life. The DTA is the aggregation of DTIs whose data and information can be used for interrogation about the physical product, prognostics, and learning. The specific information contained in the digital twins is driven by use cases. The digital twin is a logical construct, meaning that the actual data and information may be contained in other applications.

Examples

Manufacturing industry

The physical manufacturing objects are virtualized and represented as digital twin models (avatars) seamlessly and closely integrated in both the physical and cyber spaces. [13] Physical objects and twin models interact in a mutually beneficial manner.

The digital twin is disrupting the entire product lifecycle management (PLM), from design, to manufacturing, to service and operations. [14] Nowadays[ when? ], PLM is very time-consuming in terms of efficiency, manufacturing, intelligence, service phases and sustainability in product design. A digital twin can merge the product physical and virtual space. [15] The digital twin enables companies to have a digital footprint of all of their products, from design to development and throughout the entire product life cycle. [16] [17] Broadly speaking, industries with manufacturing business are highly disrupted by digital twins. In the manufacturing process, the digital twin is like a virtual replica of the near-time occurrences in the factory. Thousands of sensors are being placed throughout the physical manufacturing process, all collecting data from different dimensions, such as environmental conditions, behavioural characteristics of the machine and work that is being performed. All this data is continuously communicating and collected by the digital twin. [16]

Advanced ways of product and asset maintenance and management come within reach as there is a digital twin of the real 'thing' with real-time capabilities. [18]

Digital twins offer a great amount of business potential by predicting the future instead of analyzing the past of the manufacturing process. [19] The representation of reality created by digital twins allows manufacturers to evolve towards ex-ante business practices. [14] Furthermore, autonomy enables the production system to respond to unexpected events in an efficient and intelligent way. Lastly, connectivity like the internet of things, makes the closing of the digitalization loop possible, by then allowing the following cycle of product design and promotion to be optimized for higher performance. [20] This may lead to increase in customer satisfaction and loyalty when products can determine a problem before actually breaking down. [14] Furthermore, as storage and computing costs are becoming less expensive, the ways in which digital twins are used are expanding. [16] Implementation challenges such as data integration, organizational or compliance challenges can hinder the implementation of digital twins and its benefits. [21]

Urban planning and construction industry

Digital twins are transforming construction by creating dynamic digital replicas of physical assets. They support health monitoring, ergonomic risk assessment, and predictive maintenance of structures like bridges and historical buildings. Applications also optimize building energy and carbon performance. Case studies, such as Weihai Port, highlight their practical success. Digital twins rely on robust system architectures and tailored, requirements-driven designs. Advanced models like LSTM enable predictive capabilities, though challenges in integration and scaling remain. [22]

Geographic digital twins have been popularised in urban planning practice, given the increasing appetite for digital technology in the Smart Cities movement. These digital twins are often proposed in the form of interactive platforms to capture and display real-time 3D and 4D spatial data in order to model urban environments (cities) and the data feeds within them. [23]

Visualization technologies such as augmented reality (AR) systems are being used as both collaborative tools for design and planning in the built environment integrating data feeds from embedded sensors in cities [24] and API services to form digital twins. For example, AR can be used to create augmented reality maps, buildings, and data feeds projected onto tabletops for collaborative viewing by built environment professionals. [25]

In the built environment, partly through the adoption of building information modeling (BIM) processes, planning, design, construction, and operation and maintenance activities are increasingly being digitised, and digital twins of built assets are seen as a logical extension - at an individual asset level and at a national level. In the United Kingdom in November 2018, for example, the Centre for Digital Built Britain published The Gemini Principles, [26] outlining principles to guide development of a "national digital twin". [27]

One of the earliest examples of a working 'digital twin' was achieved in 1996 during construction of the Heathrow Express facilities at Heathrow Airport's Terminal 1. Consultant Mott MacDonald and BIM pioneer Jonathan Ingram connected movement sensors in the cofferdam and boreholes to the digital object-model to display movements in the model. A digital grouting object was made to monitor the effects of pumping grout into the earth to stabilise ground movements. [28]

Digital twins have also been proposed as a method to reduce the need for visual inspections of buildings and infrastructure after earthquakes by using unmanned vehicles to gather data to be added to a virtual model of the affected area. [29]

Healthcare industry

Healthcare is recognized as an industry being disrupted by the digital twin technology. [30] [15] The concept of digital twin in the healthcare industry was originally proposed and first used in product or equipment prognostics. [15] With a digital twin, lives can be improved in terms of medical health, sports and education by taking a more data-driven approach to healthcare. The availability of technologies makes it possible to build personalized models for patients, continuously adjustable based on tracked health and lifestyle parameters. This can ultimately lead to a virtual patient, with detailed description of the healthy state of an individual patient and not only on previous records. Furthermore, the digital twin enables individual's records to be compared to the population in order to easier find patterns with great detail. [30] The biggest benefit of the digital twin on the healthcare industry is the fact that healthcare can be tailored to anticipate on the responses of individual patients. Digital twins will not only lead to better resolutions when defining the health of an individual patient but also change the expected image of a healthy patient. Previously, 'healthy' was seen as the absence of disease indications. Now, 'healthy' patients can be compared to the rest of the population in order to really define healthy. [30] However, the emergence of the digital twin in healthcare also brings some downsides. The digital twin may lead to inequality, as the technology might not be accessible for everyone by widening the gap between the rich and poor. Furthermore, the digital twin will identify patterns in a population which may lead to discrimination. [30] [31]

Automotive industry

The automobile industry has been improved by digital twin technology. Digital twins in the automobile industry are implemented by using existing data in order to facilitate processes and reduce marginal costs. Currently, automobile designers expand the existing physical materiality by incorporating software-based digital abilities. [32] A specific example of digital twin technology in the automotive industry is where automotive engineers use digital twin technology in combination with the firm's analytical tool in order to analyze how a specific car is driven. In doing so, they can suggest incorporating new features in the car that can reduce car accidents on the road, which was previously not possible in such a short time frame. [33] Digital twins can be built for not just individual vehicles but also the whole mobility system, where humans (e.g., drivers, passengers, pedestrians), vehicles (e.g., connected vehicles, connected and automated vehicles), and traffics (e.g., traffic networks, traffic infrastructures) can seek guidance from their digital twins deployed on edge/cloud servers to actuate real-time decisions. [34]

Related Research Articles

<span class="mw-page-title-main">Computer-aided design</span> Constructing a product by means of computer

Computer-aided design (CAD) is the use of computers to aid in the creation, modification, analysis, or optimization of a design. This software is used to increase the productivity of the designer, improve the quality of design, improve communications through documentation, and to create a database for manufacturing. Designs made through CAD software help protect products and inventions when used in patent applications. CAD output is often in the form of electronic files for print, machining, or other manufacturing operations. The terms computer-aided drafting (CAD) and computer-aided design and drafting (CADD) are also used.

<span class="mw-page-title-main">Simulation</span> Imitation of the operation of a real-world process or system over time

A simulation is an imitative representation of a process or system that could exist in the real world. In this broad sense, simulation can often be used interchangeably with model. Sometimes a clear distinction between the two terms is made, in which simulations require the use of models; the model represents the key characteristics or behaviors of the selected system or process, whereas the simulation represents the evolution of the model over time. Another way to distinguish between the terms is to define simulation as experimentation with the help of a model. This definition includes time-independent simulations. Often, computers are used to execute the simulation.

<span class="mw-page-title-main">Mixed reality</span> Merging of real and virtual worlds to produce new environments

Mixed reality (MR) is a term used to describe the merging of a real-world environment and a computer-generated one. Physical and virtual objects may co-exist in mixed reality environments and interact in real time.

DELMIA, a brand within Dassault Systèmes, is a software platform designed for use in manufacturing and supply chain professionals. It offers various tools encompassing digital manufacturing, operations, and supply-chain management, including simulation, planning, scheduling, modeling, execution, and real-time operations management.

Digital Prototyping gives conceptual design, engineering, manufacturing, and sales and marketing departments the ability to virtually explore a complete product before it's built. Industrial designers, manufacturers, and engineers use Digital Prototyping to design, iterate, optimize, validate, and visualize their products digitally throughout the product development process. Innovative digital prototypes can be created via CAutoD through intelligent and near-optimal iterations, meeting multiple design objectives, identifying multiple figures of merit, and reducing development gearing and time-to-market. Marketers also use Digital Prototyping to create photorealistic renderings and animations of products prior to manufacturing. Companies often adopt Digital Prototyping with the goal of improving communication between product development stakeholders, getting products to market faster, and facilitating product innovation.

A smart object is an object that enhances the interaction with not only people but also with other smart objects. Also known as smart connected products or smart connected things (SCoT), they are products, assets and other things embedded with processors, sensors, software and connectivity that allow data to be exchanged between the product and its environment, manufacturer, operator/user, and other products and systems. Connectivity also enables some capabilities of the product to exist outside the physical device, in what is known as the product cloud. The data collected from these products can be then analyzed to inform decision-making, enable operational efficiencies and continuously improve the performance of the product.

Cyber-Physical Systems (CPS) are mechanisms controlled and monitored by computer algorithms, tightly integrated with the internet and its users. In cyber-physical systems, physical and software components are deeply intertwined, able to operate on different spatial and temporal scales, exhibit multiple and distinct behavioral modalities, and interact with each other in ways that change with context. CPS involves transdisciplinary approaches, merging theory of cybernetics, mechatronics, design and process science. The process control is often referred to as embedded systems. In embedded systems, the emphasis tends to be more on the computational elements, and less on an intense link between the computational and physical elements. CPS is also similar to the Internet of Things (IoT), sharing the same basic architecture; nevertheless, CPS presents a higher combination and coordination between physical and computational elements.

Virtual prototyping is a method in the process of product development. It involves using computer-aided design (CAD), computer-automated design (CAutoD) and computer-aided engineering (CAE) software to validate a design before committing to making a physical prototype. This is done by creating computer generated geometrical shapes (parts) and either combining them into an "assembly" and testing different mechanical motions, fit and function. The assembly or individual parts can be opened in CAE software as digital twins to simulate the behavior of the product in the real world.

FlexSim is a discrete-event simulation software package developed by FlexSim Software Products, Inc. The FlexSim product family currently includes the general purpose FlexSim product and healthcare systems modeling environment.

<span class="mw-page-title-main">Simcad Pro</span> Simulation software by CreateASoft Inc.

Simcad Pro simulation software is a product of CreateASoft Inc. used for simulating process-based environments including manufacturing, warehousing, supply lines, logistics, and healthcare. It is a tool used for planning, organizing, optimizing, and engineering real process-based systems. Simcad Pro allows the creation of a virtual computer model, which can be manipulated by the user and represents a real environment. Using the model, it is possible to test for efficiency as well as locate points of improvement among the process flow. Simcad Pro's dynamic computer model also allows for changes to occur while the model is running for a fully realistic simulation. It can also be integrated with live and historical data.

<span class="mw-page-title-main">3D modeling</span> Form of computer-aided engineering

In 3D computer graphics, 3D modeling is the process of developing a mathematical coordinate-based representation of a surface of an object in three dimensions via specialized software by manipulating edges, vertices, and polygons in a simulated 3D space.

Cloud manufacturing (CMfg) is a new manufacturing paradigm developed from existing advanced manufacturing models and enterprise information technologies under the support of cloud computing, Internet of Things (IoT), virtualization and service-oriented technologies, and advanced computing technologies. It transforms manufacturing resources and manufacturing capabilities into manufacturing services, which can be managed and operated in an intelligent and unified way to enable the full sharing and circulating of manufacturing resources and manufacturing capabilities. CMfg can provide safe and reliable, high quality, cheap and on-demand manufacturing services for the whole lifecycle of manufacturing. The concept of manufacturing here refers to big manufacturing that includes the whole lifecycle of a product.

Digital health is a discipline that includes digital care programs, technologies with health, healthcare, living, and society to enhance the efficiency of healthcare delivery and to make medicine more personalized and precise. It uses information and communication technologies to facilitate understanding of health problems and challenges faced by people receiving medical treatment and social prescribing in more personalised and precise ways. The definitions of digital health and its remits overlap in many ways with those of health and medical informatics.

<span class="mw-page-title-main">Fourth Industrial Revolution</span> Current trend of manufacturing technology

"Fourth Industrial Revolution", "4IR", or "Industry 4.0", is a neologism describing rapid technological advancement in the 21st century. It follows the Third Industrial Revolution. The term was popularised in 2016 by Klaus Schwab, the World Economic Forum founder and executive chairman, who asserts that these developments represent a significant shift in industrial capitalism.

<span class="mw-page-title-main">Smart manufacturing</span> Broad category of manufacturing

Smart manufacturing is a broad category of manufacturing that employs computer-integrated manufacturing, high levels of adaptability and rapid design changes, digital information technology, and more flexible technical workforce training. Other goals sometimes include fast changes in production levels based on demand, optimization of the supply chain, efficient production and recyclability. In this concept, as smart factory has interoperable systems, multi-scale dynamic modelling and simulation, intelligent automation, strong cyber security, and networked sensors.

Predictive engineering analytics (PEA) is a development approach for the manufacturing industry that helps with the design of complex products. It concerns the introduction of new software tools, the integration between those, and a refinement of simulation and testing processes to improve collaboration between analysis teams that handle different applications. This is combined with intelligent reporting and data analytics. The objective is to let simulation drive the design, to predict product behavior rather than to react on issues which may arise, and to install a process that lets design continue after product delivery.

<span class="mw-page-title-main">Virtual reality applications</span> Overview of the various applications that make use of virtual reality

There are many applications of virtual reality (VR). Applications have been developed in a variety of domains, such as architectural and urban design, industrial designs, restorative nature experiences, healthcare and clinical therapies, digital marketing and activism, education and training, engineering and robotics, entertainment, virtual communities, fine arts, heritage and archaeology, occupational safety, as well as social science and psychology.

Digital thread, also known as digital chain, is defined as “the use of digital tools and representations for design, evaluation, and life cycle management.”. It is a data-driven architecture that links data gathered during a Product lifecycle from all involved and distributed manufacturing systems. This data can come from any part of product's lifecycle, its transportation, or its supply chain. Digital thread "enables the collection, transmission, and sharing of data and information between systems across the product lifecycle" to enable real-time decision making, gather data, and iterate on the product.

A digital project twin is a virtual equivalent of intangible assets and processes by using digits, particularly binary digits, around a temporary undertaking.

The Digital twin integration level refers to the different degrees of data and information flow that may occur between the physical part and the digital copy of a digital twin. According to the different levels of integration, the digital twin can be divided into three subcategories: Digital Model (DM), Digital Shadow (DS) and Digital Twin (DT).

References

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