Digital Twin: Enabling 21st Century Manufacturing 4.0

Michael Grieves

Cheif Scientist, Advanced Manufacturing at Florida Tech

Learning Objectives

As a 21st-century concept, the Digital Twin captures the idea that we are moving work from the physical world into the virtual one. It moves toward using bits, which are getting cheaper all the time, in place of atoms, which are getting more expensive. We are replacing expensive physical time, energy, and material with much cheaper digital information.

The Digital Twin is the concept driver behind Manufacturing 4.0. It moves us from a functional- centric approach to a product-centric one. It integrates manufacturing as a critical aspect of product creation, so that how to manufacture products is not an after-thought once a product is designed and engineered. It will improve both productivity and quality.

" has garnered great attention because it is a great use of digital information to to minimize resource use in a factory..."

Michael Grieves

Cheif Scientist, Advanced Manufacturing at Florida Tech


Hi, I’m Dr. Michael Grieves. I’m the Chief Scientist for Advanced Manufacturing at the Florida Institute of Technology. My discussion today is on the Digital Twin: Enabling 21st Century Manufacturing 4.0. What I’m going to talk about is industry, or 4.0, or Manufacturing 4.0, or Smart Manufacturing, or Industrial Internet of Things, or IoT, or however you want to call it, but it’s this idea that we’re in the fourth wave of the Manufacturing era.

Just to give a brief reminder, the first stage or era was machines, steam power, central power shafts. This sort of took place after the steam engine was developed and occurred in the 1800s. When we moved to the beginning of the 20th century, we started to have electricity. We have individual motors, and then clearly, the idea of mass production introduced by Ford Motor Company of my hometown Detroit was a particular value in terms of being able to manufacture. The third era gets a little fuzzy, but but we can consider that as computer based PLCs and robots. This took place in the second half of the 20th century, let’s call it around the 70s, 80s, maybe even a little bit into the 60s, but it was this idea that we were going to have robots and computer controlled machines. The claim is now that we’re in the fourth era, which are smart-connected machines, and cyber physical systems, and I will sort of contend that is digital and physical twins. This whole idea of where the digital twin comes into play, but I’m gonna also talk about the physical twins because I think it gets a little short shrift with respect to how we have to look at smart connected products to basically drive our digital twins.

This is kind of the presentation, piece, where I’m going to talk about what do we mean when we have the sort of digital and physical twins. I’m first going to start off with the idea of the digital twin model. This is the underlying premise. I introduced this in about 2002. It hasn’t changed much, except for the fact that the technology has made it a reality, as we have had exponential increases in computing technology to enable us to have the kind of robust digital representations that we would need for digital twin.

From my perspective, and I’m not big on definitions, because I think that complex concepts, have a tough time being captured in a few word definitions. If you believe the old adage of “a picture’s worth 1000 words,” then I think an idea of a model is much more relevant in terms of being able to describe this kind of capability. On the left hand side, we have the physical space that we’ve always had. This includes the physical products, and in point of fact, as soon as we sort of had an idea about a physical product, we actually had to put it into physical form. We either drew it or created blueprints or even created physical prototypes. Where this basically changed is the ability to having this digital information in a computer based system, and that’s on the right side where you can see that we have the digital twin itself. These are the digital representations of what was on the left hand side. Our focus here was basically to create a robust digital versions of the driven by use cases, because information is granular and we can have as little or as much information about the product on the left side where we have to have the entire product or no product at all.

The third aspect is basically the connection between the two spaces. We want to collect data from the physical space to populate the virtual space, and then, we can use that information in the physical space to basically be more effective and productive with our products. We can develop them quicker, we can manufacture them quicker and better, and we can support them. My focus is going to be more on Manufacturing, but it basically entails the entire product lifecycle. What we’re doing is moving work, which we’ve always done in the physical space, from the 20th century and before into the 21st century. Why? Because bits are much cheaper than atoms. They continue to get cheaper or atoms continue to get more expensive and so we can actually do much more work in terms of working with our digital twin products. The ideal is we like to basically create the product to test the product, and back to the product support the product, and then we got it all right in this digital environment. We would go out and actually move around expensive atoms.

The middle part with the connections is often called the Digital Thread. Frankly, I’m not a fan of the term. I’ve hung on by a thread too often in my career. To feel comfortable, I’d like it to be called the Digital Pipe or the Digital Eyebeam, but we’re sort of stuck with the Digital Thread nomenclature. When you hear digital thread, it doesn’t contain any information. It just connects the physical space and the virtual space, my digital twin and my physical twin.

I’m going to talk about the digital twin types because I think that that’s kind of important in understanding that the digital twin encompasses the entire life cycle. It is not simply about connecting a digital twin to a specific physical model, but it’s about being able to use a digital twin throughout the entire lifecycle from the beginning of the life cycle until the product is disposed of, and even then the digital twin can continue on. That’s sort of represented in the lower left corner, where I divide the lifecycle into sort of four areas. I create the product, I build the product, I operate and sustain the product, and then I dispose of the product. What the digital twin has allowed us to do is to move from a functional centric version, where every area had its own information to this product centric version, where we could basically have the information populated and consumed no matter where we are in the product lifecycle.

The first kind of product that we digital twin type we have is what I call the prototypical digital twin or the digital twin prototype. This is not the same as the sort of the prototypes that we make for experimentation, but is basically all the products that can be made. As you can kind of see from the from the visual, it starts off as this fuzzy idea of what we want, we start to build requirements up, and as we move through the process here in terms of creating the first physical product, we basically could start to develop and to collect all the information that we need to build not only that product, but the variants of that product.

The next kind of digital twin type is the digital twin instance. Now, we start to make individual products that we want to track throughout its entire life. As we manufacture physical products, we want to, in essence, create the digital twin of it that we’re going to connect it through a slide. We obviously need to collect it at this point in time because this is the as builds and this will provide the base for our digital twin moving forward. We obviously want digital twins for complex products, pacemakers, jet airplanes, nuclear aircraft carriers, industrial machinery, we certainly don’t need them for things like paper clips. It’s all about the complexity of information that we want to caption. These are all the products that are made. The focus here is basically that we want it to start to manufacture these complex physical products, and then we want to connect them through their digital twin, and connect them throughout his life so that we can have information about that product no matter where it is. We can get that information instantaneously and simultaneously with others.

The third type of digital twin that I propose is the digital twin aggregate. These are all the products that have been made. Why this is important, is what we really want to do here is to basically be able to collect all this information about the products as they’ve been formed. The more products that are out there, the more information I’m going to get. We can do such things as be able to predict performance. If I see this sensor reading and that sensor reading and another sensor reading, I know that I’m going to have failure of that particular product within a period of time. If I’m good enough, I can even put probabilities on it to say, “Within four weeks, there’s an 80% chance of failure. Within six weeks, there’s a 90% chance of failure.” I can also use it for machine learning. Earlier versions of the product can help later versions of the product to maintain the performance, because they now have gone through the learning process and they can share that with, with newer products that are coming down the line. These are the digital twin types, and these come out throughout the entire lifecycle.

There’s sort of a misunderstanding that I only can have a digital twin once I have something that rolls out on the factory. That can’t be farther from the truth. I have my digital twin first, because I can do a whole lot of work in the virtual environment that will save me time, energy, and material. Speaking of that particular issue, why is information important? I think this is not as well understood as it should be, and it set the idea that information is a trade off for time, energy, and material. If I take any particular task, and let’s take manufacturing, since we’re sort of talking about that. The idea of manufacturing a product, I could have it in my factory and I can divide that task of manufacturing that product into two distinct areas. One is the most efficient, effective way, using the minimal amount of physical material and physical resources as possible. That’s the green bar down at the bottom. I can cost that because I can cost time, energy, and material. The red part is all the information and efficiencies that are over and above that green area. If I look at the use of information, information replaces, not the physical resources, I need to complete that task. If I was omniscient and omnipotent, I’d only want to do the stuff in the green and to minimize the use of resources. The blue information doesn’t replace that. It basically can replace the information and efficiencies. Now, I show it replacing all the information and efficiencies, and that clearly is not the case. This is the ideal, but it’s the idea that I can replace information in efficiencies with the information. The issue is that I don’t have a unit of measurement for information, but I can cost it with a proxy of the cost of my hardware, software, people’s time, and organizing information, so I can get to that.

Why does this work and when? This work if I have sort of repeatable tasks, which I usually do in manufacturing, and if the cost of the information over all the time for the task is less than the cost of wasting physical resources. I’m basically going to save money and in point of fact, make far less mistakes in the physical world. For those of us that may or living in the information system business, this pretty much holds true in terms of using information to replace wasted physical resources. This is the underlying premise behind not only the digital twin, but pretty much all other information system. As I said, I don’t think that that is particularly well understood. Lean Manufacturing, which is this idea of the minimal use of resources. The digital twin, I will contend, probably gets us closer to Lean Manufacturing than moving things out around on the actual manufacturing floor and expanding energy because we can do this in the virtual world, and basically be able to model and simulate this information, and be able to to come up with the leanest way of manufacturing products without having to expend that time and effort on a factory floor.

I’m going to talk a little bit about sort of the digital twin model of the factory because that’s sort of one of the more extensive uses of the digital twin because not only it requires the digital twin of my products, which I have on the far right and left hand sides, but it also requires the digital twins of the means of production. [Unintelligible] good to basically create this wonderful virtual product if I can’t actually make the physical version of it. Otherwise, all I have is a pretty picture.

What I want to do is to basically use the information and have my digital twin of my machines be able to then send that information to the physical machines to create the physical product. The ending result here is while I use the prototypical digital twin on the right hand side, what I want to do is as I’m making physical products, be able to create the digital twin instances I talked about that match up with the individual products that exist. This whole idea of the digital twin model for the factory is important. In fact, one of the first papers that I wrote on the topic, but it has garnered great attention because it is a great use of digital information to minimize resource use in a factory. Quite frankly, the ideal situation in a factory is it’s Groundhog Day, assuming that the day was the minimal use of resources, the factory manager wants every other day to look exactly like that. This helps that in terms of being able to capture that information, and to be able to use that information to produce products in an efficient and effective fashion.

This is Industry or Manufacturing 4.0, as I say, it’s called Smart Manufacturing. It uses the industrial internet of things because I have to send to these machines, in order to be able to feed that data, that solid arrow into my virtual world, because I gotta collect that data and turn it into information that I can use in order to replace wasted resources.

In terms of the factory itself, the first one I propose is what I call a Factory Replication. That’s the idea of, “If I can capture this information, if I can have that data flowing into my digital twins of my manufacturing process, I can have the information about the factory, no matter where I am, and it could be instantaneously and simultaneously across, doesn’t matter where I’m at.” If you’ve been on the factory floors, you’ll notice that the factory management is up above so they can see—this actually gives them the visualization. In point of fact, they can collect data information off the factory floor and merge it with their simulations, and be able to understand exactly what’s occurring on the factory floor. This idea of replication, I think, is an interesting one, and was sort of the first ones I proposed for factories using digital twins.

Where I really would like to go with this is the idea of obviously replication, so quite simply, I talked about the idea that we could replicate this information and have the the information that I would have to gain from the factory floor by being in close proximity to it, but I also gonna have information that I couldn’t even get. How is the machines producing? Is there any sensor readings that are causing a problem? What I would like to do is, in essence, I like to engage what I call a Front Running Stimulation. This is the idea that says that, “If I have this information, I can merge my collection of real time data with my modeling and simulation to predict the future.” Every time [inaudible], I want to run a new simulation to see what’s happening. Is a bottleneck occurring because there was a glitch in one of the robots? Are we going to run out of material at a particular station based on production? I would, ideally, like to predict what’s going to happen in the future with respect to my digital twin of my factory and production.

Where I sort of differ from industry 4.0 is the idea of industry 4.0, as you can see from this chart, is about the idea of decreasing the amount of time from a some sort of failure to remediation. My position is, I think that’s good. You really want to do that if you can, but I would like to eliminate the problem altogether if I could predict that there was going to be a failure and I could basically fix that failure before it even occurred. I could bring material to a station that was going to have a stock out, I could readjust my assembly line if I knew that there had been a glitch on a robot that was going to cause a bottleneck later on. It’s sort of the difference between the digital twin concept and industry 4.0, there’s a lot of similarities there. The digital twin, first of all, allows me to implement industry 4.0, but secondly, is I really would like to get out and predict that particular problem rather than wait till the problem occurs and an attempt to remediate it even quickly. Even a quick remediation means that there is going to be increased cost of not having production up to my Groundhog Day of being perfect.

This is a quick idea of the digital twin and its use in Manufacturing 4.0, industry 4.0, and I’m going to leave you with a couple resources that you can use. I have a couple book chapters. The first one was probably the seminal chapter on digital twins—it’s in a book called Transdisciplinary Complex Systems. The second is one that came out in 2019, and it’s in a book called Complex Systems Engineering, Theory, and Practice. You can find that chapter on ResearchGate under my name, but if you would like, you can simply send me an email, and I’ll be happy to send those chapters.

With that, I’d like to thank you for your attention. I hope I’ve at least given you a pretty good view of Manufacturing 4.0, the use of the digital twin, which I think is sort of critical in order to be able to implement that, and our ability of an essence being able to decrease the waste of physical resources by using a digital twin. Thank you very much.

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