Susan Smith has worked as an editor and writer in the technology industry for over 16 years. As an editor she has been responsible for the launch of a number of technology trade publications, both in print and online. Currently, Susan is the Editor of GISCafe and AECCafe, as well as those sites’ newsletters and blogs. She writes on a number of topics, including but not limited to geospatial, architecture, engineering and construction. As many technologies evolve and occasionally merge, Susan finds herself uniquely situated to be able to cover diverse topics with facility. « Less
Susan Smith has worked as an editor and writer in the technology industry for over 16 years. As an editor she has been responsible for the launch of a number of technology trade publications, both in print and online. Currently, Susan is the Editor of GISCafe and AECCafe, as well as those sites’ … More »
GISCafe Special Report: Digital Twin Technology Offers a Mirror Image for Productivity of the Future
Digital Twins – are they taking the technology world by storm? IDC recently noted that by 2020, 30% of global 2000 companies will be using data from Digital Twins to improve organizational productivity by as much as 25%. While it is not quite there, Gartner predicts the Digital Twin will reach the “Plateau of Productivity” within 5 to 10 years.
A good description of a digital twin is as follows: “A digital twin is a digital representation of a physical object or system. The technology behind digital twins has expanded to include large items such as buildings, factories and even cities, and some have said people and processes can have digital twins, expanding the concept even further. The idea first arose at NASA: full-scale mockups of early space capsules, used on the ground to mirror and diagnose problems in orbit, eventually gave way to fully digital simulations.” – Network World
In our GISCafe Voice Industry Predictions 2019, digital twins were cited as one of the trends to watch in 2019.
In the UK, the National Infrastructure Commission is exploring creating a digital copy of the country’s entire infrastructure. This would involve linking smaller digital twins of the country’s cities and towns and infrastructure networks. It is hoped that the UK digital twin would help in the preparation for and response to extreme weather events. This would be a collaborative effort involving both private and public sectors in all corners of the country.
Hear what industry experts have to say about Digital Twins:
What part of the digital twin process is your organization involved in developing or interested in for the future?
Cindy Elliott, head of Commercial Industry marketing team at Esri, spoke about the company’s role in digital twin technology.
“Current efforts within my organization at Esri are focused around the global supply chain network and operations. The normal supply chain organization is inherently made up of complex physical assets, some stationary and many others mobile (ie: people, trucks, ships, pallets, products, etc). Supply chains operate 7 days a week, 24 hours a day. Through digitizing this complex network of assets, organizations are better prepared to visualize what’s happening physically, including emerging threats from weather, traffic and incident feeds, to accelerate the decision-making processes to mitigate and eliminate supply chain disruptions. By creating a digital twin of the working supply chain, companies can not only have a real-time view into the supply chain operations but can also capture a chronological history of activities and related conditions that can be referenced for future investigations and/or simulations.”
COL [R] Steven D. Fleming, PhD, Professor of the Practice of Spatial Sciences, Spatial Sciences Institute USC Dana and David Dornsife, College of Letters, Arts and Sciences, University of Southern California says they are doing some work on “digital twins” — but not extensively.
“We are doing GeoDesign work in which we model cityscapes for future development. Some of this work uses robust modeling techniques from both the Spatial Science and Architecture communities,” says Dr. Fleming.
Bentley Systems, Inc. develops technology and services to create, visualize, and analyze infrastructure digital twins.
Cityworks currently takes the historical workflows within municipal (state and local government) organizations based in work management, permitting and asset management and brings those from their legacy paper process to digital applications using HTML5 apps, hosted solutions and mobile technology, according to Becky Tamashasky, vice president of Vision & Product Engineering for Cityworks.
What is the role of sensors in digital twin technology?
Says Dr. Fleming, “The new suite of sensors (space, aerial, terrestrial, in situ, and “non-traditional, VGI” from individuals) are where the much of the power is in creating the “as built” from which the twin can be created.”
“Sensors play a significant role in the data gathering process in the manner that they simplify the process and time necessary,” Tamashasky says. “With the use of automated sensors to collect the data, perform quality assurance and deliver to the connected business systems it’s possible for organizations to reduce the time required for the same process in a non-digital format. This enables organizations to allocate their constrained resources to other initiatives.”
Bentley Systems’ Adam Klatzkin, senior director, Infrastructure Digital Twins, points out that digital twins can leverage external information coming from sensors and cameras to reflect the current state of the physical asset. “By combining data from continuous surveys, photogrammetry, LiDAR and sensors, and assigning detected changes to a timeline, digital twins can allow you to roll the history of the infrastructure asset—and related real-world conditions—forward or backward in time.”
Sensors play a key role in gathering data for the digital twin, whether those sensors are IoT-enabled hardware, mobile devices, or GPS-enabled equipment, says Elliott. “When coupled with geo-enabled asset and infrastructure information (buildings, roads, ports, etc), sensor data can provide insight to where assets are located / moving (including staff), environmental conditions from internal and external feeds, and status of asset performance or risks. This combined data set can alert parties ahead of a disruption, monitor real-time performance in relation to service level agreements, and provide digital transparency for organizational stakeholders.”
Marcel Broekmaat, Director Product Management, Connect Applications at Trimble Inc., notes that sensors are embedded in devices to allow for communication and interaction over the internet to provide production, as-built and operational data. “This allows assets to be remotely monitored and controlled, and, for the purposes of digital twins, enables real-time updates to corresponding digital models. For example, sensors are often used for job site access control systems to automatically determine if a person is authorized to enter a specific area of a job site based on certain criteria. Other applications include scanners that can be seen as sensors used to capture as-built situations and equipment tracking which allows for analysis of the use of tools and accomplished productivity.
How do you see digital twins assisting in geospatial processes?
“In relation to the global supply chain, the digital twin can advise the geospatial process of where disruptions and incidents occur over time to identify patterns and root cause analysis, including when and where anomalies occur in the operation and why,” says Elliott. “In an advanced setting, organizations can leverage the big data of the digital twin to set and test hypothesis about patterns observed, as well as model the data for new process simulation and/or predictive exercises to further optimize and innovate the supply chain practices.”
Digital twins will help drive the development of application inherent in geospatial software modeling/simulation, noted Fleming. From this, sensor gaps will likely be identified to complement current-to-future development and production glide paths.
Cityworks’ Becky Tamashasky says: “Digital twins assist in the geospatial process by providing and enforcing business rules based on location. Rather than organizations manually confirming that a service request is delivered to the correct jurisdiction, logic within the GIS can provide this answer automatically. As well, when staff enter a “geo-fence” assignments can be delivered to their device to make it easier for them to sort through a list of assignments. These are just two examples, but overall the use of digital twins in the geospatial context can improve the quality of numerous interactions from assignments based on geographic service areas to identifying events based on geography and triggering actions.”
How are digital twins being used in the conceptual part of design for digital cities and countries around the world?
“Cities want to improve urban planning with greater levels of detail and optimize the performance of existing assets,” says Bentley’s Klatzkin. “The combination of reality modeling with geospatial-to-BIM integration makes city-scale digital twins possible. With a city-scale digital twin, you can see a visual representation of how your city is performing for operational review. Many aspects of the design process can be enhanced, such as optimizing designs for passenger flows, visualizing emergency evacuations, and demonstrating resilience against flooding, sea level changes, and/or extreme weather conditions.”
Assuming that the data is robust and that the algorithms used accurately model space/time relationships of human activity, digital twins clearly help us to understand and predict the possible use(s) of future urban landscapes, says Dr. Fleming.
Is there a way to enter the data from a real-world counterpart into a digital twin that is standard, or would that vary with the type of technology used?
“Yes, sensors in the field collect data on the status of physical assets and update the digital simulation automatically,” says Broekmaat of Trimble. “This allows digital twins to update on the fly as real-world conditions change. The goals defined for the digital twin should determine how data needs to be contributed to it, not the technology used. This will require definition of data schemas for the digital twin, that can then be used to check if contributed content matches the expected input.”
“In regard to digitizing the supply chain, aka the digital supply network, there are extensive resources needed to build a complete replica of the network,” Elliott says. “However, starting with basic enterprise information from ERP or TMS for example, sets the groundwork for the creating the twin. Because supply chains are so complex and made up of so many variants, it is essential that an open environment is created so that as many relevant points of data can be combined – such as global roadways and sea lanes, railways, real-time weather, live incident feeds, locations of moving assets – where are they now, and are they where they are supposed to be, sites of suppliers, plants, warehouses, retailers, customers, and the list continues. Geographic information systems (GIS) provide a natural platform for integrating and making sense of the complex, location-rich data.”
“Today, it would vary with the many unique types of sensor (from different vendors) that are used, Fleming says. “However, we are rapidly moving toward more common data formats that will assist in standardizing data sets so that more data can be better ingested into modeling/simulation/predictive decision tools.”
Bentley Systems has developed a technology called iModelHub to make it easy to incorporate information generated across the lifecycle of an infrastructure asset. iModelHub aligns disparate data and synchronizes changes with an extensive change ledger. Bentley has created and shared an open-source library of tools (iModel.js) that can be used to integrate infrastructure digital twins—based on iModelHub—into digital workflows.
“Digital twins should be built upon a technology framework that is both open and flexible, so that they can be easily used and integrated with other systems,” Klatzkin points out. “The technology should reduce input impedance with a developer’s codebase and help preserve flexibility over time. An open-source approach will likely be the best form factor to address the vast possibilities of digital twins and to foster innovation and novel uses of the technology.”
What are the rules, if any, for developing digital twins?
“Great and complex question,” says Dr. Fleming. “Generally speaking, two that come to mind are: (1) Use accurate and precise data of current, as-built urban populations via dynamic updating protocols; and (2) Develop predictive models of future human behavior (which may be different than current behavior as based on today’s technology and service expectations of the same).”
Klatzkin says: “Digital twins should be built upon a technology framework that is both open and flexible, so that they can be easily used and integrated with other systems. The technology should reduce input impedance with a developer’s codebase and help preserve flexibility over time. An open-source approach will likely be the best form factor to address the vast possibilities of digital twins and to foster innovation and novel uses of the technology.”
“At a minimum, I would say the rule would be to understand the workflow or the business case and needed outcome and not necessarily to design the digital twin to be identical to the non-digital process, but rather identify how digital technology can be used to improve the existing process,” Tamashasky of Cityworks offers. “As well, it’s also important to not worsen a process for the sake of developing a digital alternative.”
How does the digital twin aid in predictive analysis?
“Speaking specifically to the global supply chain, through the aggregation and analysis of data over time, applying AI and ML in particular, the digital twin of the supply chain provides insights to previously unseen patterns in disruptions, supply risks, and performance levels allowing supply chain operations to predict future threats, evaluate their impact, and mitigate downtime or disruptions,” Elliott of Esri explains. “Which improves network throughput to improve customer service levels and reduce costs.”
“This is an area where we’ve already been experimenting given the depth of historical data captured by our clients,” says Tamashasky. “One example of where a predictive twin can be leveraged is with water main breaks though there are numerous applications. Using the main break example, organizations could identify the frequency of main breaks based on time of year, soil type, pipe type, pressure zone and reactive and preventive maintenance records. This would be another example of the geospatial element within the digital twin experience, but using the wealth of this data organizations would be able to identify patters of breaks and identify those mains where similarities indicate a likelihood of short term failure. This knowledge would allow organizations to potentially modify both operational maintenance and capital replacements to minimize impacts to the distribution system and service area as well as costs for the organization.”
Another aspect of digital twin experience is the predictive twin, which could model the future of infrastructure, based upon the behavior of past designs of a similar nature. How do you feel the predictive twin would play into the digital twin experience?
“It is likely iterative,” notes Dr. Fleming. “What we recognize about a predictive, future urban landscape (in development) likely will impact how we may consider re-designing/fixing a current urban landscape. This is especially relevant when the opportunity to “re-build” or “correct” is offered. Unfortunately, these opportunities are the result of increasingly frequent natural disasters (e.g., hurricanes, floods, wildfires) where a mandate to re-build immediately becomes necessary.”
Moreover, Klatzkin says that with the increasing maturation of digital twins, the industry will be able to leverage real-time feedback and predictive insights—such as cost, safety, and performance—which will influence the design, execution, and operation of future projects.
“Digital twins should be built upon a technology framework that is both open and flexible, so that they can be easily used and integrated with other systems,” remarked Klatzkin. “The technology should reduce input impedance with a developer’s codebase and help preserve flexibility over time. An open-source approach will likely be the best form factor to address the vast possibilities of digital twins and to foster innovation and novel uses of the technology.”
Are there situations where digital twins would not be the best approach?
“There should always be a consideration of cost versus benefits. Smaller projects, assets with a limited lifespan or well-known, standard components may not be the best targets for extensive data collection and/or monitoring,” says Broekmaat of Trimble.
A digital twin would take many years to complete, depending upon its proportions. In the meantime, how do you perceive being able to use the digital twin and its data to the best advantage?
Dr. Fleming has an interesting analogy to make about the digital twins: “The key here is continuously updating the twin and use the twin based on a predictive growth path. The best way to view this is from the lens of ‘human twins’. Twins continually grow. Male twins and female twins are different. Twins today (male and female) will be different than twins in 5 years. There will be many things that remain in common… but the shirt and shoe sizes (assuming we are talking about the childhood years) will likely be different. Recognizing that change is a natural part of the process, will insure that data sets and ‘attitudes’ of the twins are kept current and meaningful.”
“Although a complete digital replica of the global supply network may take many years, any starting point can add immediate value to better visualize and address the day to day operations,” says Elliott from Esri. “It’s been my experience that organizations start with creating a digital map of all of their locations, including suppliers, factories, distribution facilities and customers. From there, based on the availability of live data feeds, additional supplier, partner and customer information available, transportation data (trucking, rail, sea, air) and IoT/sensor data as well as other unique data that pertains to the supply chain planning and operations, organizations build up their digital twin over time, strengthening its connections and value back to the company. So essentially, by leveraging GIS technology, organizations can quickly digitize enterprise assets such as major buildings, supplier and partner locations, distribution centers, and add in live data from weather, traffic, security incidents beginning to build that foundation of the digital twin. Next start connecting trucks, pallets, and other equipment to start collecting performance information for real-time operations information and for future big data analysis.
With the increasing maturation of digital twins, the industry will be able to leverage real-time feedback and predictive insights—such as cost, safety, and performance—which will influence the design, execution, and operation of future projects.”
In conclusion, Tamashasky of Cityworks says, “part of the beauty of the digital twin process is the ability to incorporate digital transformations incrementally. Identify where the digital process improves and enhances the current operations and brings benefit, and where this can be done independently without causing repercussions to other areas. This allows organizations to gradually adopt new digital processes in a manner that also allows their employees to develop the comfort and knowledge as the digital transformation expands within their organization.”
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