I never heard of “Digital Twins” until a friend of mine mentioned it to me and told me it might be an interesting topic for one of my blog posts. Because I had no idea what this buzzword was all about I thought it would be fun to invest some time in getting a basic understanding of the concept of “Digital Twins”.
This post will give you a basic overview of “Digital Twins”: what it is, its history, how this technology is currently being utilized, and its potential for the (near) future.
How mirrored systems (simulations) saved the day during the Apollo 13 accident
Simulations are imitations of the operation of real-world processes or systems over time and have been applied by many companies. NASA has always been working with simulations: they had to because they had (and still have) to cope with a lot of unknown factors in their ventures of space exploration. When you are developing applications that are utilized during space exploration you don’t have the luxury of monitoring these applications physically once they are in space. This is the reason why NASA started to set up mirrored systems on earth.
This approach saved the lives of the astronauts during the Apollo 13 accident. Apollo 13 launched on April 11th, 1970 at 13:13 local time. Two days after launch, an oxygen tank exploded on April 13, effectively shipwrecking the crew in space. This accident triggered Jim Lovell’s historic words: “Okay, Houston, I believe we’ve had a problem”.
By system mirroring, the people on earth managed to find a solution. In order to do this, three possible solutions were simulated on earth:
- Only using the command/service module (CSM) engine and fuel to return directly to Earth (the speed was already much less than immediately after the trans-lunar injection). Then the lunar lander (Lunar module, LM) would have to be discarded to reduce its mass, thereby saving fuel. This option expired because of the damage to the CSM facilities, components from the lunar lander were required for the return trip.
- Returning directly to Earth, by using the lunar lander’s engine and fuel. For this, the damaged service module would have to be discarded after the fuel had been used up, which was also subject to objections.
- This option was chosen: Apollo 13 was instructed to continue to the Moon and once there it used the Moon’s gravity to return (the so-called free-return trajectory). Finally, the lunar lander’s descent motor was used to slow down the speed. Course corrections were made with the steering rockets of the lunar lander.
Digital Twins and Simulations
As previously discussed, simulations can help organizations to imitate real-world processes or systems. In the past, this was done physically (like what NASA did during the time of the Apollo 13). Nowadays, this can be done by a Digital Twin. A Digital Twin represents itself as a digital counterpart of a physical object or process. The concept originates from 2002 (introduced by Michael Grieves, then of the University of Michigan) but was first applied in practice by NASA in 2010, in an attempt to improve physical model simulations of spacecraft (hence improving their approach of system mirroring).
If you invest engineering activities in the development of a virtual model of a product, service, or process, this virtual model is a Digital Twin: a pairing of the virtual and the physical world (the actual product, service, or process).
By doing simulations with a Digital Twin, you can run all kinds of tests without actually developing the product, service, or process in real-time. This means that it allows analyses of data and monitoring of systems to prevent problems before they happen in real-time. It also prevents downtime, can help you in developing new opportunities, and can support you in planning for the future by using simulations. And most importantly: this is done in a virtual environment which means that mistakes can be made with limited costs.
How does it work?
The people who build a Digital Twin are most of the time experts in data science or applied mathematics. First, they start to research the physics behind the physical object or system that is being imitated. This is done by developing smart components that use sensors to gather data about real-time status, working conditions, and positions. Those components are then integrated with a physical item after which the process of data extraction starts.
It is also possible to design the Digital Twin based on a prototype of its physical counterpart. In this case, the Digital Twin can provide feedback as the prototype is refined. It is even possible for a Digital Twin to serve as a prototype itself before a physical version is created.
After the data that has been obtained from the real-world original, it is developed into a mathematical model that simulates the real-world original in a virtual environment: a cloud-based system that receives and processes all the data that the sensors monitor.
You can learn very interesting lessons and create/uncover opportunities, within a virtual environment that can be copied into the physical world. This is done by analyzing two types of available data, obtained from the virtual environment: business data and/or contextual data.
Business data and contextual data
Business data is all the information that is related to your company. For example, sales data, customer contact information, and web traffic statistics. Business data is a very broad concept. It includes everything: from simple analytic details to in-depth reviews of the performance of your organization.
Contextual data provides perspective into an event, a person, or an object. It gives you a broader understanding by showing unequal pieces that in their turn, relate to each other. This way you “paint” a larger picture based on all these pieces of small data.
Contextual data is all around us every day. If you want to buy a telephone and walk into a store, the salesperson will immediately start asking you a number of questions to determine the context of your purchase. What color phone do you want? Do you want to play heavy games on the phone? Do you want it to be compatible with 5G or not? All your answers to these questions give the salesperson data points that put your visit to the store into context. Your answers help the store to provide you with better service.
How the Internet of Things contributed to the success of Digital Twins
More and more hardware is equipped with sensors and connected to the Internet of Things (IoT). You can think of lights, refrigerators, furnaces, microwaves, toys, cars, etc. Because IoT devices are refined, Digital Twin scenarios can also include smaller and less complex objects. Obtaining this data can give additional benefits to companies.
Digital Twins can also be used to predict different outcomes based on variable data. This is comparable to a “run-the-simulation” scenario. In this, a possible scenario is proven within a digital environment. With additional software and data analytics, Digital Twins can try to optimize an IoT deployment for maximum efficiency based on this kind of scenario. It can also help designers to figure out where things should go or how they have to operate before they are physically deployed.
Digital Twin applications
Digital Twin business applications are mainly applied in the below sectors:
- Manufacturing: in this area, the rollouts of Digital Twins are probably the most common. A lot of factories already use Digital Twins to simulate their processes.
- Automotive: because cars are fitted with telemetry sensors nowadays, Digital Twins are more and more common. Looking to the near future when autonomous vehicles are going to hit the road, the concept of Digital Twins will become even more important.
- Healthcare: a good example of this is band-aid-sized sensors. These sensors send health information back to a Digital Twin that uses this data to monitor and predict the well-being of a patient.
How Digital Twins can compliment a Master Mind Group
In addition to the more regular business applications, there are also out-of-the-box opportunities that are less straightforward. One of these examples is the integration of a Digital Twin into a Master Mind Group.
A Master Mind Group is a group of peers who regularly meet in order to give each other guidance, advice, and support. A Master Mind Group is essential in operating a successful business, growing a business, and achieving business goals. The ultimate goal of a Master Mind Group is to navigate its participants through difficult business challenges and issues, using the collective experiences and insights of the other members of the Master Mind Group.
Digital Twins can be a very interesting addition to the pool of masterminds that a company has at its disposal. In addition to the collective experiences of the group, the concept of Digital Twins can provide the group with a virtual simulation of possible solutions to complex business problems. You can see a Digital Twin as your most talented product technician with the most advanced monitoring, analytical and predictive capabilities at his/her fingertips: a very welcome addition to any Master Mind Group!
Digital Twins 2.0: Process Digital Twins
With the current technological advancements, Digital Twins are evolving into Process Digital Twins. This is also a must because organizations are more demanding in relation to the quality of output of Digital Twins. Traditional manufacturers are operating in both physical and virtual models of their environments. The problem is that you can’t be in both spaces at the same time. This means that this declines the quality of your end-to-end visibility. Additionally, machine-to-machine-to-people (M2M2P) is remaining tricky. Manufacturers need a way to collaborate across their physical and virtual ecosystems. This has to be done in real-time, modeling all the changes to complex systems involving software, hardware, and digital representations of multiple machines.
In order to bridge this gap, there is a new wave of digital transformation visible: Process Digital Twins. This advanced form of Digital Twins mixes High-Performance Computing (HPC), the Internet of Things (IoT), Artificial Intelligence (AI), and real technologies together in order to optimize not only equipment but entire manufacturing processes. By using Process Digital Twins, a manufacturer can take advantage of advanced and immersive visualizations. This includes holographic representations (HoloLens) that bring virtual processes and entire production lines into the real world.
Additional HPC solutions enhance Process Digital Twins, even more, enabling an engineer to interact with these in-process models in virtual and physical space simultaneously. Potential changes can be simulated before they are executed or an engineer can train with new equipment. It almost feels like standing on a Holodeck in Star Trek! The technology of enhanced Process Digital Twins surpasses the dimension of simply projecting an object into a physical space. It provides an entirely new functionality instead, eliminating technology limitations in order to provide real-time collaboration across the value chain.
Final thoughts
The concept of Digital Twins gives an organization more flexibility to experiment and innovate with a lower barrier for employees to come up with creative ideas. I think that, in the end, this will make an organization more agile and improve the anti-fragility of the organization. It can give a business a serious competitive edge if executed properly. In other words: significant resources need to be dedicated to this and it should not be a one-time project. It should be a mature process/discipline within an organization and should be a branch of your R&D department.
In addition to that, technological advancement also enhances the possibilities of Digital Twins. It is already possible to project virtual objects into the real world with the support of, for instance, the HoloLens. Within time people will be able to fully step into a virtual environment (the Metaverse) or the real world. I think within time, the border between the real world and the virtual world will be dissolved by the use of even more advanced tools.
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