Digital Twin

 

What is a Digital Twin (DT)?

            In simple terms, a basic definition of DT is "an executable virtual model of a physical thing or system" (Thomas, 2020).   An example may be a replica DT of a car while 3-D computer-aided drawing (CAD) models have been in use for years and used in participatory product development, now an executable virtual model of a physical thing or system.  

Introduction:

            With the forward into the 4th industrial revolution (4IR), Industry 4.0 increases the automation of everything, including industrial systems, the Internet of things (IoT), cyber-physical systems (CPS), smart-everything, and the operations and the networking linking the components together.  One result of this 4IR revolution was the birth of a new digital twin (Borchardt) abstraction that seeks to make the clarity between the digital and physical spheres evident. Relevant and overlapping terminology includes an avatar, product agent, virtual object, virtual twin, and digital counterparts.  A DT represents a digital mirror image of the tangible likeness, inhabits the virtual realm, and embodies all object features.  In real-time, the replicated object changes to facilitate treating, testing, and monitoring the real-world entity (Pokhrel et al., 2020).    Cybersecurity teams face increasingly complex systems and structures that arise from the IoT and cyber-physical systems/embedded systems such as smart cities, smart grids, autonomous cars, industry 4.0 manufacturing, and other examples, to name a few.  DT represents the future in simulations to model cyber-attacks in the industry 4.0 systems, with the aim of predicting attack vectors and preventing breaches.

Example in DT Solutions:

The DT is unlocking the key to meet today's industry challenges of the 'Three P's' of Profit (Costs), People, and Planet challenges.  For example, the Dassault Systèmes DT product called the '3DEXPERIENCE' Platform aims to reduce the space difference between virtual (V) and real (R ) with V&R simulations, models, experiences, and learning visualizations.  Digital continuity (DC) embodies the full digital realization from end to end. The DC benefits include:

1.      Benefits: predictive, immersive, collaborative, imaginative,

2.      People: know-how, knowledge, value networks, and

3.      Technologies: Model-based systems engineering (MBSE).

Some of the use cases described are the DT simulations and visualizations in Figure 1.  Safety benefits include recognizing safety and bottlenecks in the simulation to prevent safety issues and jams in a real-life scenario. According to Figure 1., the top three widely implemented DT use cases found, in discrete manufacturing, were used to (1) Improve product quality at 34%, (2) Reduce manufacturing costs 30%, and (3) Reduce unplanned downtime 28%.  DT enables stakeholders to view simulations and enable collaborative process improvements through analysis of various realistic simulation scenarios.  In complex systems analysis the DT enables noteworthy improvements over the predecessor 3-D CAD modeling such as data communications where virtual twins can capture all operational functions consisting of performance data, failures, support and maintenance needs, etc. the simulation enables simulation of what was produced rather than what was designed. 

                                  Figure 1. Digital twin use cases:

    Source: Forging the Digital Twin in Discrete Manufacturing LNS Research, 2018

The maturity model progression for the DT implementation often starts in a siloed execution environment, progresses to synchronized operations, and finally to the target state of integrated functions.  Table 1 displays the identified success factors for the DT and DC comprise (Thomas, 2020).

Table 1.  Success factors for digital twin (DT) and digital continuity (DC).

Identified success factors for the DT and DC
Value Advantage	Approaching opportunities from a business value vantage point rather than a technology point of view.
Sustainable Operations	Develop an industrial operations technology stack with flexibility, scalability, and global sustainability.
Top-Down	Driving transformation from the top while sharing and communicating successes.
Holistic Approach	Take a holistic approach with an unobstructed vision to accomplish the DC Workplan stages.
Collaboration	Collaborate with cross-discipline teams, including IT and OT engineering professionals and associates.
Get Lean First	Get a head-start by getting the organization lean before embarking on the DT/DC journey to foster a culture capable of sustaining the process.
Start Small	Start small with some initiatives and don't wait or risk falling behind the competitive set.
Source: (Thomas, 2020)

 

What Types of Companies and Industries use Digital Twins?

DT, like Velcro, and other inventions popularized by NASA eventually became ubiquitous as they spread through various use cases, industries, and our daily life. Initially, Michael Grieves conceptualized the DT at the University of Michigan on technology in 2002.  Companies such as NASA, Kaeser, Amazon, Chevron, China Central Television, General Electric (GE), T-Mobile, Volvo, SANY, Bellsystem24, De'Longhi, Obayashi Corporation, and Elekta have used virtual twins (DataMesh, 2020; DigitalNewsAsia, 2016; Marr, 2021; Miskinis, 2021; PTC, 2021).  Challenge.org expects the use of DT technology to most manufacturing companies, aerospace, automotive, defense, energy, healthcare, technology, and continue to gain a presence in most industries, including customer service, news and entertainment, smart cities and countries, healthcare, and other organizations engaging in digitalization.  Companies using DT have witnessed revolutionary improvements by incorporating artificial intelligence (AI).  DT with AI allows for thoroughly testing simulations in a safe space to avoid hazardous and costly mishaps in production environments.   The DT simulations prevent disruptions in service or safety incidents in the real word worst-case scenarios (Andersen, 2021).  Driverless cars, petrochemical plants, and medical devices exemplify prime examples of where you need to thoroughly test in a simulated environment before going live to avoid safety incidents. 

Compelling Imperative for Digital Twin:

Some quotes from industry leaders using DT highlight the essential need for companies to keep the pace going into the 4IR (Marr, 2021). 

·         "For every physical asset in the world, we have a virtual copy running in the cloud that gets richer with every second of operational data," per Ganesh Bell, chief digital officer and general manager of Software & Analytics at GE Power & Water.

·         Thomas Kaiser, SAP Senior Vice President of IoT, put it this way: "Digital twins are becoming a business imperative, covering the entire lifecycle of an asset or process and forming the foundation for connected products and services. Companies that fail to respond will be left behind."

DT usage is getting driven by the increase in IoT-designated sensors, the companion that goes hand-in-hand with DT.  Concerning what countries lead in implementing DT, you might call out Singapore because the Country of Singapore has its own DT called 'Virtual Singapore' (Government of Singapore, 2021; Valzania, 2018).  In this example Dassault Systèmes and the National Foundation of Singapore worked to originate a comprehensive virtual twin replica of the city employing Dassault’s 3DEXPERIENCECity® solution.  The implementation enabled Singapore to combine environmental, topographical, and geographic data to run simulations on traffic patterns, climate events, and to develop improved solutions and understanding of city planning challenges.  To run the analysis on various simulated scenarios the city planners applied different data sets representing each scenario to understand the impact on the results communicated by the simulation results data.    

Challenges for Digital Twin:

Cyber digital twin needs multiple technologies to run in parallel and faces many challenges due to this requirement.  Table 2 lists some of the issues and challenges of DT identified (Juneja et al., 2021).

Table 2. Challenges for digital twin include the lack of various factors.

Challenges for Digital Twin Include the Lack of:
Compatible Parallel Collaborations	The inadequacy of compatible, clearly defined infrastructures among cyber twin, AI, IoT that are required to run together in parallel collaboration.
High Quality Uninterrupted Data	High-quality, uninterrupted data is needed. Poor data quality or deteriorated data communications could prevent the seamless functioning of the cyber twin infrastructure.
Data Privacy and Security	Data privacy and security challenges to sensitive data obtained from many connected IoT devices require authentication and security measures to be applied to the individual IoT devices to prevent unauthorized access.
Standardization	Lack of standardization of cyber twin prevents realizing its full potential and inhibits information flows.
Skilled and Equipped Resources	Lack of skilled and equipped resources is required to maintain digital twin due to lack of available resources.
Source: (Juneja et al., 2021)

 

Summary and the Future of Digital Twin:

                Cyber twin networks have demonstrated superior performance to peer-to-peer networks in all aspects (Juneja et al., 2021).   Table 3 lists future DT advancements to create improved innovations, security, and scalable architecture include:

Table 3. Future advancements for DT identified including innovations, security, and growth.

Future Advancements for Innovation, Security, and Anticipated Growth
New Business Models	Incorporating DT into new business models to achieve successful results needs exploration and defining the usage mission and goals.
Authentication Architecture	Properly designed authentication architecture of the DT demands evolving to enable tracing the behavior on the network.
AI Among Multiple DTs	Implementation of artificial intelligence (AI)  among multiple DTs to leverage efficiencies and increase the quality of services.
Cloud Resource Management	The critical nature of cloud resource management can't get overstated and could get effectively managed via blockchain technology to allocate resources among many devices efficiently.
Source: (Juneja et al., 2021)

 

References:

Andersen, J. (2021). Where Do Digital Twins Fit In? https://www.industryweek.com/technology-and-iiot/article/22026918/where-do-digital-twins-fit-in

DataMesh. (2020). DataMesh Digital Twin - Product Twin. https://datamesh.com/product-twin/

DigitalNewsAsia. (2016). Healthcare innovation could lead to your digital twin. https://www.digitalnewsasia.com/digital-economy/healthcare-innovation-could-lead-your-digital-twin

Government of Singapore. (2021). Virtual Singapore. National Research Foundation - Prime Minister's Office Singapore. Retrieved 11/11/2021 from https://www.nrf.gov.sg/programmes/virtual-singapore

Juneja, S., Gahlan, M., Dhiman, G., & Kautish, S. (2021). Futuristic Cyber-Twin Architecture for 6G Technology to Support Internet of Everything. Scientific Programming, 2021, 9101782. https://doi.org/10.1155/2021/9101782

Marr, B. (2021). 7 Amazing Examples of Digital Twin Technology In Practice. @BernardMarr. Retrieved 11/11/2021 from https://bernardmarr.com/7-amazing-examples-of-digital-twin-technology-in-practice/

Miskinis, C. (2021). Most Promising Companies Who Are Using Digital Twin Technology. @Challengenews. https://www.challenge.org/insights/digital-twin-technology-companies/

PTC. (2021). PTC Digital Twin Insights. https://www.ptc.com/en/industry-insights/digital-twin

Thomas, F. L. (2020). Webinar: Realizing your Manufacturing Digital Twin | DELMIA https://youtu.be/jPLdy_6S2e0

Valzania, G. (2018). Digital Twin Cities Deployment, and Worldwide Adoption. https://www.wrld3d.com/blog/digital-twin-cities-deployment-and-worldwide-adoption/