Gosh, where do you start on thinking through “digital twins”. The manufacturing industry is exploding with their digital twins to mimic their physical operations,

We have companies like Dassault who have been focusing on digital for many years taking a  specific focus on the human being and commercially releasing their “Living Heart”.

This “living heart” digital twin is the first realistic model of a human organ that actually accounts for electricity, mechanics and blood flow in the heart into a personalized full-dimensional model of the heart. Then users can practice and manipulate it, to place pacemakers, reverse chambers, cut out cross sections and run all sorts of hypothetical scenarios before the physical heart needs to be touched.

Then we have the digital twin that will learn all about you and what you do, think and work upon to provide you a closer replica of your daily life to help you. No, the digital twin is alongside us in multiple ways, it is not just a shadow in a mirror, mimicking all we do, in life and real time but it is working on finding better solutions to improve the actions being undertaken. It helps to predict, suggest and improve on our current activities.

Now stop and absorb that, please. The digital twin takes intelligence to a new level to mimic and then also predicts performance, based on the real-world performance you are feeding back into it.

A real-time performance that builds the digital thread that gives this connectivity and context to the decisions you want to make, or will allow you to investigate alternatives in the digital world, so that these can then be a precursor to doing them in the physical.

In a post or two, I want to take a little deeper look into digital twins and threads and what this all means. My main focus will be more the manufacturing world as it has been the grounding for what is emerging but I can’t promise this when I put on my future thinking hat, it might go differently.

Lets firstly in this post, look at some history and definitions

I have been researching, collecting and slowly try to absorb as much as this tiny brain can. I already need a powerful twin that can collect, predict and suggest where I keep investigating to speed up the process and make it more efficient. In time something out there will do this. Que Google or Amazon who are getting there, as are others.

Origins of the Digital Twin

The term “Digital Twin” was defined by Dr. Michael Grieves at the University of Michigan around 2001-2002. He originally defined this in the context of Product Lifecycle Management. In his paper, he introduced the concept of a “Digital Twin” as a virtual representation of what has been manufactured. He promoted the idea of comparing a Digital Twin to its engineering design to better understand what was produced versus what was designed, tightening the loop between design and execution.

The initial concept was to create a digital model of a physical system before building it. This way, tests, and simulations could be performed beforehand but not in real time but in predictive modeling. These designs were prototypes and commonly referred too as blueprints.

Jump forward to today. How do we presently define digital twins?

Looking through various papers I like some of these definitions of the digital twin.

Srivathsan Govindarajan, Vice President, SAP Digital Twin, summarized it best:

“A Digital Twin is a dynamic digital representation of a live physical object and needs to represent specific aspects of physical objects like shape, working state and structural behavior. Digital Twins will dynamically change in near real-time as the state of the physical object changes.”

Within the same article I was reading one summary was made: “A Digital Twin is simply a virtual representation of all the information users need to supplement their work—no more, no less. It’s a question of scope. Sure, an organization can gather more data than that one user might need. But that would simply mean there are more Digital Twins for each asset, user or relationship or one Digital Twin that filters data accessible by a user’s role”

One useful insight has been: “Different people interacting with the Digital Twin might want different lenses of it” Hold that thought, it extends out digital into a very different era of future relationships.

One other suggested definition I read was by Tom Maurer, with Siemens PLM software and he/they define the Digital Twin as “a digital model that accurately represents a product, production process or the performance of a product or production system in operation.” Now that definition fits more tightly into where a manufacturer might go in their definition.

I know definitions are evolving, for instance, I have been reading how Siemens has been evolving their Digital Twin, linking it into a Digital Thread and working this ultimately into a complete “Digital Factory” concept. Actually, Siemens has a dedicated “Digital Factory” division focusing on all things “digital”. It makes sense. It has been set up to offer a comprehensive portfolio of seamlessly integrated hardware, software and technology-based services to support the manufacturing world. It extends the Enterprise out beyond even a “digital enterprise in different solutions that connect the internal and external worlds”.

The digital twin has evolved from its PLM roots. For instance, much of Siemen’s current digital business comes from the legacy of a strong PLM focus over many years. CAD and CAE tools have been working and aiding in designing and simulating the performance of hardware for years. The difference today with the digital twin lies in its more dynamic form. The digital representation captures the mechanical, electrical, software and system aspects. It simulates any physical performance by the use of sensors and controllers ‘fixed’ on or embedded in the asset or specific moving parts, to provide ‘real-time data’ back to the digital twin, so as to allow an accurate ‘mirror’ of performance. So the digital twin is as closely representing the physical entity that it is ‘connected up too’. This virtual representation can also build two-way interactions, so remote parties can control the physical machine to change some of its parameters to optimize its performance.

The more you collect the more you have a digital thread

If you can imagine a digital twin is never static, there is always something changing. It is this historical trail that is seen as the digital thread. It can slice and dice to give the ability to view and inspect the digital representation of the product, asset or entity, at different points in time.

The digital thread becomes an increasing asset to refer too and use throughout the product’s lifecycle, you can predict, disclose and document it but more importantly, you can measure the lifecycle far more accurately by having a digital twin in place. For highly valuable assets this becomes very useful for future design, predictions, and new innovations.

The digital thread builds the communications framework and you can dip in and dive to the right information, at the place and time you want to explore. To make for a more effective and optimization of your assets. You can implement a more continuous refinement and begin to build interplays between multiple connect digital twins, to eventually have everything that has a sensor hooked up and built into a virtual digital factory, or our planes aircraft engines, to access, integrate, transform, inform and analyse performance for optimum delivery, that meets that moments time of need.

Having the digital thread gives you the opportunity to simulate performance under different conditions, loads, or environmental changes. As you learn, everything should get smarter. It allows for the engineer to understand the physical asset in real-time or in simulation, at different times, optimal or imposed conditions, to build better future solutions or manage the physical product today in better ways, to learn about performance, and how they will perform in different operating conditions, or providing predictive conditions in the future.

The key enablers to having digital twins

There are many, the basic ones are recognizing the value of being digital. Achieving a digital Enterprise allows for exploiting all the value in digital technology. The growing need is to place all that is digital onto a common platform where you build a new learning system of your physical world as you collect massive amounts of data, that need translating and evaluating.

Through PLM design we build the digital model of an object before it turns into the physical asset, making this initially a virtual product, then you can actually simulate this digital model into a virtual production process. It is then, you can turn a digital concept into a physical asset for real production testing and asset performance testing.  We can visualize, build, refine assumptions, troubleshoot and manage complexities and linkages within systems-of-systems, without even going onto the factory floor, although those physically managing the “asset” often have years of wisdom to incorporate in any future design.

So, a digital twin really is often ‘born’ before the physical end product. When you have got to this point you have reinvented your business around digital operations and you are talking the language of systems-of-systems, within a digital thread and you exploit hidden dependencies, seek out optimal points of intervention and integration and really innovate within your ‘operating’ environment, pushing the product or physical asset in better design, performance and optimization.

Wrapping up this introduction to Digital Twins

So, to finish this brief introduction into digital twins;  they form the basis for digital enterprises, they build the digital threads and can combine to build the digital factories but I want to add two more definitions to hold in your mind as we finish.

Firstly, “the digital twin is the virtual representation of a physical object or system across its life-cycle. It uses real-time data and other sources to enable learning, reasoning, and dynamically recalibrating for improved decision making.”  

Secondly, “an evolving digital profile of the historical and current behavior of a physical object or process is one that helps optimize business performance. It is the exact replica of the physical entity. It becomes a digital avatar that combines modelling and simulations with sensors and big data” Deloitte “Expecting digital twins”

In the future, I will explore these digital twins, threads, enterprises, and factories as these will all have a profound effect on us, in manufacturing, in service environments, in critical and equally hostile environments in their growing uses to build our lives differently. We will all need to re-imagine having “digital twins” in different ways.

The smartphone changed our lives, the digital twin has the same potential. We will all need to become comfortable with “digital avatars” all around us.