The Curious Case of Digital Twin : The Marvel of Industry4.0 Revolution and Beyond
Kaaustubh K.
Business & Digital Transformation | Open Banking | CBDC | Payments | RegTech | Fintech Enthusiast | Kay’s Principle of Transformation - ADAPC l Immediate Joiner and can relocate globally!
Introduction and Overview
Delivering a satisfying customer experience is one of the top priorities for every business. For this purpose, businesses carefully analyze customer journeys and market trends. In the digital era, customer journeys have become even more complex. Right from finding out about a new brand online or through friends and family to posting product reviews on social media, customer journeys can go through multiple stages. Additionally, changing market trends can influence customer experience drastically. Hence, business leaders have to develop complex strategies to enhance customer experience.
A digital twin is a virtual replica of a product, system, process, or customer that helps businesses visualize various aspects and collect crucial data. Digital twin can be compared to X-ray vision that allows businesses to monitor their products in real-time.
“Digital twins drive the business impact of the Internet of Things (IoT) by offering a powerful way to monitor and control assets and processes,” says Alfonso Velosa, research vice president at Gartner. “However, to truly drive value from digital twins, CIOs will need work with business leaders to develop economic and business models that consider the benefits in light of the development costs, as well as ongoing digital twin maintenance requirements.”
Digital twins refer to the digital representation of physical objects, and for more than 30 years, product and process engineering teams have used 3D renderings of computer-aided design (CAD) models, asset models and process simulations to ensure and validate manufacturability. NASA, for example, has run complex simulations of spacecraft for decades.
It spans the object's lifecycle and uses real-time data sent from sensors on the object to simulate the behavior and monitor operations. Digital twins can replicate many real-world items, from single pieces of equipment in a factory to full installations, such as wind turbines and even entire cities. Digital twin technology allows us to oversee the performance of an asset, identify potential faults, and make better-informed decisions about maintenance and lifecycle.
“A digital twin can be defined, fundamentally, as an evolving digital profile of the historical and current behavior of a physical object or process that helps optimize business performance.”
It is based on massive, cumulative, real-time, real-world data measurements across an array of dimensions. These measurements can create an evolving profile of the object or process in the digital world that may provide important insights on system performance, leading to actions in the physical world such as a change in product design or manufacturing process.
It differs from traditional computer-aided design (CAD), nor does it serve as merely another sensor-enabled Internet of Things (IoT) solution. It could be much more than either. CAD is completely encapsulated in a computer-simulated environment that has demonstrated moderate success in modeling complex environments; and more simple IoT systems measure things such as position and diagnostics for an entire component, but not interactions between components and the full life cycle processes.
Adopting a platform approach towards the creation of product digital twins allows for the breaking down of silos in the enterprise. The goal of that twin is to create an experience of the product in the digital world that is indistinguishable from the physical product experience.
The digital twin for a product or overall system provides a source of information that is unique, authoritative and consistent across the entire product life cycle. The digital twin can lubricate the collaboration between engineering and manufacturing by mirroring the designed process and the manufac. It’s a velocity driver allowing for the movement of innovations from the conceptual stage to the market place in a fraction of the time.
The economic value of digital twins will vary widely, depending on the monetization models that drive them. For complex, expensive industrial or business equipment, services or processes, improving utilization by reducing asset downtime and lowering overall maintenance costs will be extremely valuable, making internal software competencies critical to driving value with digital twins.
“The complexity of digital twins will vary based on the use case, the vertical industry and the business objective”
Developing and supporting digital twins in such environments will require continuous updating of data collection capabilities and curating, as well as adaptive analytics and algorithms. Consider the software updating that a car manufacturer provides to its automobiles. Going forward this will require even more component monitoring and software updating, to the point that OEMs, such as vehicle makers, must also become software vendors, and use these digital twin and software skills as part of their differentiation. Asset operators will have to add software skills to their operations teams as they add smarter assets, and address more complex digital twins in their operations. They must also add software and data terms to their contracts.
A digital twin is a virtual representation of a physical object or system across its entire lifecycle. It uses digital tools and real-time data to virtually create, test, build and monitor a product or process – closing the feedback loop between design and operations. It’s an ingenious approach that facilitates transformation without risking operations.
How Does Digital Twin Technology Work?
The life of a digital twin begins with experts in applied mathematics or data science researching the physics and operational data of a physical object or system in order to develop a mathematical model that simulates the original.
The developers who create digital twins ensure that the virtual computer model can receive feedback from sensors that gather data from the real world version. This lets the digital version mimic and simulate what is happening with the original version in real time, creating opportunities to gather insights into performance and any potential problems.
A digital twin can be as complex or as simple as we require, with differing amounts of data determining how precisely the model simulates the real world physical version.
The twin can be used with a prototype to offer feedback on the product as it is developed or can even act as a prototype in its own right to model what could occur with a physical version when built.
What Challenges has it Solved?
Since it can be used across a wide range of industries, from automotive to healthcare and power generation, it has already been used to solve a large number of challenges. These challenges include fatigue testing and corrosion resistance for offshore wind turbines and efficiency improvements in racing cars. Other applications have included the modelling of hospitals to determine work flows and staffing to find procedure improvements.
A digital twin allows users to investigate solutions for product lifecycle extension, manufacturing and process improvements, and product development and prototype testing. In such cases, a digital twin can virtually represent a problem so that a solution can be devised and tested in the program rather than in the real world.
Who Invented It?
The concept of digital twins was first put forward by David Gelernter’s 1991 book ‘Mirror Worlds,’ with Michael Grieves of the Florida Institute of Technology going on to apply the concept to manufacturing.
By 2002, Grieves had moved to the University of Michigan when he formally introduced the digital twin concept at a Society of Manufacturing Engineers conference in Troy, Michigan.
However, it was NASA who first embraced the digital twin concept and, in a 2010 Roadmap Report, John Vickers of NASA gave the concept its name.?The idea was used to create digital simulations of space capsules and craft for testing.
The digital twin concept spread further still in 2017, when Gartner named it as one of the top 10 strategic technology trends. Since then, the concept has been used in an ever-growing array of industrial applications and processes.
Digital twin can be broken down into three broad types, which show the different times when the process can be used:
Through the integration of technologies such as artificial intelligence, machine learning and software analytics with data, digital twin creates a simulation model that can update alongside or in lieu of a physical counterpart. This allows companies to assess an entirely computerized development cycle from design to deployment and even decommissioning.
By mimicking physical assets, frameworks and operations to produce continuous data, a digital twin allows industry to anticipate downtime, react to changing circumstances, test design improvements and much more.
Digital twin is key to the development of Industry 4.0 to provide automation, data exchange and joined-up manufacturing processes as well as de-risking product rollout. Industry employees are able to monitor operations in real time, providing prior alerts of possible failures and allowing for real time performance optimization and assessment with minimal loss of productivity.
Practical Applications for Digital Twins
Because it’s possible to make digital twins of individual components, complete assets, full systems and entire processes, the technology has broad application in a variety of areas.
1.?Testing New Systems Prior to Manufacture
Companies can use digital twins to create and test systems, equipment ideas and service models before investing in building or implementation. If a model proves effective, its digital twin could theoretically be linked to the physical creation for real-time monitoring.
2.?Improving Efficiency and Productivity
In a 2017 prediction regarding the benefits of digital twins, Forbes suggested using the technology could improve the speed of critical processes by 30 percent. According to Gartner, industrial companies could see a 10 percent improvement in effectiveness. The widespread availability of and diverse use cases for digital twins gives businesses in nearly all industries a better understanding of where processes can be streamlined and improved, thus helping to minimize downtime through the practice of predictive maintenance.
3.?Managing Assets in Real Time
Using digital twins to monitor daily operations and streamline manufacturing reduces unnecessary wear and tear on machinery and alerts business owners to potential money-saving changes, such as making adjustments in fuel use. Faster maintenance and repair allows companies to maintain a competitive edge by improving overall output.
4.?Understanding Data to Provide Better Service
Digital twins also have customer-facing applications, including remote troubleshooting. Using virtual models, technicians can conduct diagnostic testing from anywhere and walk consumers through the proper steps for repair instead of blindly relying on default protocols. Information gathered from these sessions provides valuable insights for future product planning and development.
Types of digital twins
There are various types of digital twins depending on the level of product magnification. The biggest difference between these twins is the area of application. It is common to have different types of digital twins co-exist within a system or process. Let’s go through the types of digital twins to learn the differences and how they are applied.
1.?Component twins/Parts twins
Component twins are the basic unit of digital twin, the smallest example of a functioning component. Parts twins are roughly the same thing, but pertain to components of slightly less importance.
2.?Asset twins
When two or more components work together, they form what is known as an asset. Asset twins let us study the interaction of those components, creating a wealth of performance data that can be processed and then turned into actionable insights.
3.?System or Unit twins
The next level of magnification involves system or unit twins, which enable us to see how different assets come together to form an entire functioning system. System twins provide visibility regarding the interaction of assets, and may suggest performance enhancements.
4.?Process twins
Process twins, the macro level of magnification, reveal how systems work together to create an entire production facility. Are those systems all synchronized to operate at peak efficiency, or will delays in one system affect others? Process twins can help determine the precise timing schemes that ultimately influence overall effectiveness.
Benefits
1: Conceptual Development
Very early experimentation with design concepts in a model that predicts dynamic behavior provides powerful insight. This allows engineers to make more informed decisions as they begin the design process. Long before the first build, engineers can predict the steady-state and transient loads of actuators during their duty cycles. To ensure the right performance, control engineers can test PLC hardware against the digital twin using common automation software. They can also test their code prior to hardware integration, resulting in accurately tuned controls across a system.
2: Data Collection
The combination of sensor technology and simulation is changing how we develop and integrate tools, giving rise to new innovations. Sensors collect massive amounts of data, allowing the digital version to act like the physical object. Running the digital twin in parallel with the real machine can provide insight into how each machine is functioning, when it will need repairs or how it could perform more efficiently. Since the dynamic response of the digital twin is built on rigorous physical laws, internal calculated properties can be used as inputs to the control system. As an example, this may allow an engineer to quickly fix, replace or eliminate the use of a faulty sensor. These scenarios may provide a reduction in costs and improved customer service as customers have the option to remotely configure products in online diagnostic systems.
3: Predictive Maintenance
There are many factors that determine the maintenance schedule for a machine. One factor is frequently overlooked because it is difficult to predict without a digital twin. This factor is the impact of dynamic loading on bearings, gears, and motors, caused by changes in the duty cycle. Putting a digital twin through a proposed duty cycle can help determine the loads on these components and the impact on the component life, reducing maintenance costs. A digital twin can also help predict where a problem might arise as the machine’s response drifts from the model. This also allows for maintenance and repairs to be scheduled, reducing unpredictable downtime and ultimately minimizing associated costs.
4: Product Enrichment
The above operations likely take place on real-time automation platforms or SCADA systems in the design office or operations room. However, manufacturers are moving this capability onto the machine itself, so these capabilities can be offered to the operator on the shop floor. These valuable features will allow manufacturers to provide greater innovations and differentiate themselves from their competition.
5: Sales Tool
Outside of the engineering department, sales teams can use digital twins to qualify customer specifications and provide accurate information to each customer. This can help validate the performance and operation of a machine given different payloads or operating conditions, without needing a consultation by the engineer.
Digital twins can help bring these benefits to our company, allowing for reduced manufacturing costs and faster time to market. To remain competitive in today’s market, embracing digital twin technology is essential. If we’re not already considering the benefits of digital twins, we may be making a costly decision that could set our company years behind.
Security Challenges
The faster a new type of technology spreads, the less attention tends to be paid to security at the outset. This forces companies to scramble to put out metaphorical fires when vulnerabilities are exploited, leading to the loss of time and profits.
The challenge remains converging existing data into a common, easily accessible template which incorporates IoT data, design (both 3D and 2D), process and quality control data to provide a full life view of a product in service. Realizing this makes it easier to deliver not only personalized products but also personalized experiences around those products to customers. Organizations must also transform themselves to enable delivery of products that meet the personalized requirement of customer bases across different markets.
Because digital twins are based in the cloud and don’t require physical infrastructure, the associated security risks are somewhat lower than with other types of systems. However, the massive amounts of data being collected and utilized is drawn from numerous endpoints, each of which represents a potential area of weakness. It’s estimated 75 percent of digital twins will be integrated with at least five endpoints by 2023, and a time is coming when visualizing complex systems may require the linking of multiple digital twins.
Every time a new connection is made and more data flows between devices and the cloud, the potential risk for compromise increases. Therefore, businesses considering digital twin technology must be careful not to rush into adoption without assessing and updating current security protocols. Areas of greatest importance include:
? Data encryption
? Access privileges, including clear definition of user roles
? Principle of least privilege
? Addressing known device vulnerabilities
? Routine security audits
While the insights digital twins provide can help businesses make improvements in processes and gain more control over operations, the introduction of any new system creates new vulnerabilities requiring the attention of IT security professionals. Businesses seeking to implement digital twin technology must consider the potential weaknesses and take appropriate measures to guard against malicious activity so that the full benefits may be realized with a minimal amount of risk.
Top digital twin applications and use cases
A.? Aerospace
Aerospace tasks are intrinsically complex. End products like aircraft and spacecraft are massively expensive to design and build, making it all the more imperative to get work done right the first time in order to avoid costly delays. From design and engineering all the way through to assembly and maintenance, digital twins improve decision-making by allowing teams to visualize and interact with computer-aided design (CAD) models and other datasets in real-time 3D.
For example, Boeing created an AR-powered aircraft inspection application using a digital twin of one of its planes. The twin enabled this aerospace industry leader to generate over 100,000 synthetic images to better train the machine learning algorithms of the AR application.
B.??Architecture
At the start of a project, architects produce design materials, including renderings and models, to allow clients to evaluate and approve the design. The problem is there’s no shared, collaborative environment with stakeholders to make decisions in real-time. Communicating design intent during traditional reviews is a difficult process. Static 2D and 3D models cause details to be lost in translation, renderings aren’t flexible enough, and not everyone is on the same page. Digital twins solve these problems so there’s no costlier mistakes.
For example, Award-winning architecture firm SHoP Architects and JDS Development Group, a real estate development, construction and acquisition firm, are utilizing real-time data with Unity to make decisions faster with every project stakeholder. See how a digital twin of The Brooklyn Tower, a 93-story, 1,073-foot skyscraper in New York City, saves time and money and reduces the project’s carbon footprint.
C.??Automotive
In the automotive industry, digital twins are used to simulate and test new design concepts before they are built, optimize production processes, and even predict how a vehicle will perform in different conditions. The top benefit of using digital twins for automotive OEMs is the ability to save time and money by identifying and addressing potential issues before they occur. As the industry continues to embrace this technology, it plays an increasingly important role across every workflow in the automotive lifecycle, from design and manufacturing to marketing and maintenance.
For example, Volvo Cars revolutionizes the vehicle production lifecycle using digital twin technology to improve design-engineering communication and collaboration, reduce reliance on physical prototype vehicles, and create more immersive and effective buying experiences
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D.??Construction
Faced with rampant supply chain delays, labor shortages, and inflated material costs, the stakes for builders are at an all-time high. Bad data and poor decision-making can lead to expensive delays and rework. Digital twin and AR technology allow the construction industry to optimize project data, streamline collaboration, and better visualize projects from design through to operations and maintenance. By using AR to bring valuable BIM data to the field, contractors are able to capture and communicate design errors in just a few clicks, allowing stakeholders to resolve issues quickly and avoid costly rework.
For example, DPR, an ENR Top 10 Contractor, is integrating AR and immersive tech into the project lifecycle to bring valuable BIM data to the field in real-time to improve team performance and reduce rework.
E.??Energy
Energy companies generate a wealth of data, especially as operations are increasingly outfitted with Internet of Things (IoT) sensors, high-definition cameras with artificial intelligence (AI) capabilities, and more. Digital technologies like real-time 3D can visualize this data to provide right-time insights, better-informing decisions around production, maintenance, safety and security, and optimization.
For example, Zutari, a South African engineering consultancy, is using Unity’s real-time 3D development platform to automate large-scale solar photovoltaics (PV) projects to reduce the time required to develop design-level insights and decrease costs.
F.? Infrastructure
Digital twin technology helps builders, planners, and operators across cities worldwide better understand and optimize these spaces for public use. By using advanced, interactive models and live IoT data, stakeholders are able to simulate traffic flow, mobility patterns, and even the effects of climate change and shifting landscapes surrounding key infrastructure like airports, roads, and transportation hubs. From individual facilities to smart cities, digital twins are helping owners, operators, and policy-makers manage large volumes of valuable data that will allow them to better equip our infrastructure for future demands.
According to ABI Research, more than 500 cities will deploy digital twins by 2025. Read more about how global industry leaders within the smart city movement are leveraging Unity to bring urban digital twins to life
G.?Government
The use of real-time 3D, extended reality (XR), and AI technologies are accelerating at a rapid pace in civilian, defense and intelligence applications. New technologies are being deployed rapidly and putting challenges on government agencies and contractors that need to stay at the forefront of cutting-edge development. Digital twins help reduce the risk, time and cost of designing, developing, deploying and supporting cutting-edge applications in simulation and training and beyond.
For example, the reconstruction of Tyndall Air Force Base in Florida after Hurricane Michael provides an opportunity to imagine what modern installations require and to rapidly undergo digital transformation. Learn how Tyndall’s digital twin is used to increase efficiency across planning, construction progress, operations, and maintenance.
H.?Luxury goods
Luxury interactive shopping is on the rise, complementing premium in-store experiences. Many luxury brands have been preparing for the future of retail for many years by creating 3D marketing experiences. Investing in this new way of selling can reduce costs and increase revenue.
For example, Globe-Trotter takes luxury shopping to new heights by using digital twin, delivered a more immersive experience to help their customers feel confident in purchasing high-priced custom luggage sight unseen.
I.?Manufacturing
As emerging trends such as the fourth industrial revolution (4IR) continue to gain traction, manufacturers are using digital twin technology to transform their product lifecycle. From faster time-to-market in product development to increased productivity among frontline workers, many manufacturers are already reaping the benefits. Over 80% of companies who implemented immersive technologies identified improvements in their ability to innovate and collaborate in their production, manufacturing, and operations work phases, according to a Forrester Consulting study commissioned by Unity.
For example, SAP shapes the future of work with Unity for AR, VR, and mixed reality (XR) as the next user experience frontier to reinvent field and factory operations.
J.?Retail
Spurred on by the pandemic, the need for retailers to leverage digital twins for design, planning, operations and more has increased exponentially. The importance of engaging customers online likewise increased overnight, and retailers looked to this technology to create immersive virtual experiences to continue connecting with shoppers. Savvy retailers are embracing digital twins to enhance processes, connect with their customers in new and profound ways, and deliver compelling digital and in-store user experiences.
eBay launches AI-enabled 3D display feature for sneaker sellers
Practical Applications for Digital Twins
1: Helsinki is Building a Digital Twin of the City
Kalasatama is a new seaside district being developed in Helsinki. A smart city project called Fiksu Kalasatama has been experimenting with smart services in collaboration with the residents, businesses, and other stakeholders in the area. Helsinki 3D+ and Forum Virium, an innovation unit of the city, joined forces to serve the needs of the experimenters through the development and use of digital twins.
The Kalasatama digital twin project got funding from KIRA-digi, the national digitalization program of the Finnish government. The project team worked full time for over a half year to complete five critical tasks, namely to:
Advance the use of digital twins in the city’s processes and services.
“We created two city models, for which we used the very latest technologies available. The first one is a triangular mesh that is more detailed than the comprehensive Helsinki model. The other is a CityGML model. We included several new themes, like planned buildings and bridges, “Airaksinen explains. “It is possible to expand the same processes to cover the whole city in the future.”
CityGML is a global standard established by OGC (Open Geospatial Consortium). It is a semantic, expandable information model that can describe objects - e.g., buildings and building parts - and their relationships in a hierarchical structure. CityGML makes the model “intelligent,” rather than just a three-dimensional representation of the reality.
One of the key results from the KIRA-digi project was the documentation of the model creation and utilization process. The project team have described the process and use cases in a comprehensive project report that is going to be made available online, both in Finnish and English.
“Our primary purpose was not to create virtual entertainment or pretty pictures. Our aim was to increase the understanding of various phenomena and issues; to simulate, anticipate, and optimize,” Suomisto proclaims.
Because the digital twin data is open for anyone to use, the city and businesses alike can create new services based on it. Helsinki’s Energy and Climate Atlas, for example, uses the million semantic surfaces of 80,000 buildings to calculate and visualize the city’s solar energy potential.
2: Etihad Rail Aiming for a Geo-Empowered “Digital Twin”
Etihad Rail has identified information technology as one of its key enablers towards becoming one of the most advanced rail systems in the world. In 2019, and as of the key initiatives of Etihad Rail Digital Transformation Program, the Company commissioned GPC-GIS as the consultant to help them design and develop a business-centric GIS Roadmap and implementation plan for an enterprise-wide GIS at Etihad Rail. GPC-GIS team of consultants has worked closely with the Company staff and other stakeholders to gain a clear understanding of the current and future needs and to align the GIS development with other key business functions and systems that are either existing or planned for the future. As envisioned, the GIS is to provide the foundation for a geo-empowered “digital twin” of the Etihad Rail network, facilities and operations that can be used to fully plan, design, construct and manage the full lifecycle of the enterprise into the future.
Geospatial information and technology will be utilized to both enhance existing and future business application systems and as a foundation for systems integration and interoperability. It is envisioned that the Etihad Rail geospatially-enabled digital twin environment will over time incorporate new and emerging trends of technology such as Internet of Things (IoT), artificial intelligence, big data, machine learning and other innovations in technology to support the continuous advancement and streamlining of Etihad Rail operations and increase safety and profitability, while providing premium reliability and safe services to its customers.
3: Western Sydney’s 4D digital twin revealed
CSIRO’s Data61 and NSW Spatial Services have launched a cutting-edge digital twin for Western Sydney.
The new 4D model, covering western Sydney’s built and natural environment was launched by Minister for Customer Service Victor Dominello on Monday.
The platform is built on Data61’s TerraJS platform and open source data catalogue system, MAGDA, and is web-accessible and secure.
Mats Henrikson, Geospatial Web Systems Group Leader at CSIRO’s Data61, said the technology will create efficiencies and has the potential to transform decision making for planners, policymakers and developers.
“Cities have never been so data rich as a result of connected sensors and many are growing vertically in addition to horizontally. This creates incredible opportunities to overlay 3D/4D data from satellite and drone technologies which is spatially accurate, to show the bigger picture of what’s happening above and below the ground over time,” he said.
“The digital twin represents a step change in how we visualise environments and processes taking place in them.”
The NSW Digital Twin combines data from across government departments, private and open sources, such as such as live transport data, infrastructure (above and below ground), building information models and property boundaries.
The model currently visualizes local government areas that comprise the Western Sydney City Deal and Greater Parramatta to the Olympic Peninsula, with more areas to be imaged and modelled in future.
4: Virtual Singapore
Virtual Singapore is a dynamic three-dimensional (3D) city model and collaborative data platform, including the 3D maps of Singapore. When completed, Virtual Singapore will be the authoritative 3D digital platform intended for use by the public, private, people and research sectors. It will enable users from different sectors to develop sophisticated tools and applications for test-bedding concepts and services, planning and decision-making, and research on technologies to solve emerging and complex challenges for Singapore.
This project is championed by the National Research Foundation (NRF), Prime Minister’s Office, Singapore, the Singapore Land Authority (SLA) and the Government Technology Agency of Singapore (GovTech). NRF will be leading the project development, whilst SLA will support with its 3D topographical mapping data and become the operator and owner when Virtual Singapore is completed. GovTech will provide expertise in information and communications technology and its management as required in the project. Other public agencies will participate in Virtual Singapore in various phases.
Virtual Singapore is an R&D programmer initiated by the NRF at a cost of $73 million for the development of the platform as well as research into latest technologies and advanced tools over a period of five years. The platform is targeted to be ready by 2018 and will be deployed progressively. There are ongoing collaborations with government agencies, universities and partners to leverage Virtual Singapore for their modelling and simulation needs.
Virtual Singapore includes semantic 3D modelling, which comprises detailed information such as texture, material representation of geometrical objects; terrain attributes, for example, water bodies, vegetation, transportation infrastructure, etc. Models of buildings encode the geometry as well as the components of a facility, such as walls, floors, and ceilings, down to its fine details, as in the composition of granite, sand and stone in a building material.
Virtual Singapore will be developed based on geometric and image data collected from various public agencies, and will integrate different data sources to describe the city with the necessary dynamic data ontology. The 2D data and information coordinated through existing geospatial and non-geospatial platforms such as One Map, People Hub, Business Hub etc. will enrich the 3D Singapore City Model. Advanced information and modelling technology will allow Virtual Singapore to be infused with different sources of static, dynamic and real-time city data and information e.g. demographics, movement, climate.
Virtual Singapore offers four major capabilities, namely:
Virtual Experimentation
Virtual Singapore can be used for virtual test-bedding or experimentation. For example, Virtual Singapore can be used to examine the coverage areas of 3G/4G networks, provide realistic visualization of poor coverage areas, and highlight areas that can be improved on in the 3D city model.
Virtual Test-Bedding
Virtual Singapore can be used as a test-bedding platform to validate the provision of services. For example, the 3D model of the new Sport hub with semantic information within the Virtual Singapore could be used to model and simulate crowd dispersion to establish evacuation procedures during an emergency.
Planning and Decision-Making
With a rich data environment, Virtual Singapore is a holistic and integrated platform to develop analytical applications (i.e. Apps). For instance, an app could be developed to analyse transport flows and pedestrian movement patterns. Such applications would be useful in non-contiguous urban networks such as our parks and park connectors in Punggol.?
Research and Development
The rich data environment of Virtual Singapore, when made available to the research community with the necessary access rights, can allow researchers to innovate and develop new technologies or capabilities. The 3D city model with semantic information provides ample opportunities for researchers to develop advanced 3D tools.
5: Air-services Australia
Air services eyes fully-fledged digital replica of Australian airspace
Air services Australia is planning to build out its digital twin of the country’s air traffic management network to improve network planning and reduce costly delays at airports.
The government-owned corporation has been investigating a “virtual copy” of Australian airspace since early 2019, joining with Deloitte and McLaren to complete proof-of-concepts.
The digital twin is expected to help the agency better navigate Australia’s air traffic network, which has a large proportion of flights connecting to a small number of major airports.
The route between Sydney and Melbourne, for instance, was the second busiest in the world prior to the pandemic.
Airservices expects the network will become only more complex over the next decade with the arrival of new data flows and more runways (in Melbourne and Perth) and airports (Sydney).
It also planning for new airspace users, with air traffic control information to be shared with drone operators through a planned flight information management system (FIMS).
In a request for information (RFI) issued this week, Airservices called for additional information from providers who can provide such a digital twin ahead of a future tender.
“The digital twin will be used to support decision making at a network level that is transparent to tactical decision making by air traffic controllers with a direct separation responsibility,” it said.
Documents show the digital twin will need to “simulate predicted future operations of the air traffic network” to support the decision making of air traffic controllers.
It will cover network structures, planes, air traffic movements and “include the use of stochastic variables, based on near real-time data from different sources”.
Airservices said the digital twin will be based on a “foundational platform” that will enable the delivery of a suite of applications designed to “better plan and manage the network”.
Initial application to be built will include delay management, task load management and dynamic sectorisation, though RFI documents indicate the number of applications will expand over time.
Any future provider would need to establish the framework for the simulation, which will “support Airservices in establishing the functionality of the applications”.
The digital twin will feed its “near real-time data” from internal and external sources, including the air traffic management and ground delay systems, weather systems and aeronautical database.
“More accurate data, based on more dynamic, integrated, and comprehensive inputs... to ensure a common operational picture, will enable better operational planning and decision-making, Airservices added.
Conclusion
Conceptually, the path would involve steps to automate critical processes when at all possible. The increased reliability associated with automation would help build a foundation for automated data acquisition necessary to represent the processes digitally. For critical processes that must still involve a manual component, implementing passive data collection through systems such as RFID tags would allow for the required data collection without human intervention.
Finally, the digitized data from all of these sources would need to be consolidated in an exact way to allow real-time management and future analysis. Success in implementation requires a deep understanding of both the difficulties and benefits of implementing a digital twin, even though this level of understanding is complicated, time-consuming and challenging to achieve
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