The concept of a Digital Twin is mostly applied to the case where more insight is obtained from a physical operating product and an Internet of Things (IoT) platform. But in the case of virtual prototyping, the Digital Twin concept is applied to an old practice in mechanical hardware.
One approach to developing a smart connected product, one that hooks up with an IoT platform, is to just build it. Just cobble it together. Throw some sensors on a product. Wire that to some kind of embedded system. Wire that to your antenna. Start sending data to an IoT platform. You and your organization can actually learn a lot from going through that exercise. It is almost a “coming of age” experience for companies exploring IoT.
While that needs to be done, you will quickly run into limitations on the experiments you can conduct with physical prototypes. Swapping out a sensor isn’t easy when it’s soldered in place. There might not be room, physically, for the sensor you really need for accurate measurement. You might run into too much electromagnetic interference for the antenna you planned to use.
Working through these issues is new to some companies as they transition traditionally mechanical products to smart connected ones. However, the problems associated with resolving issues through physical prototyping aren’t new. In fact, that is an old concept when it comes to hardware. Long ago, mechanical and electrical engineers figured out that modeling and simulating a design virtually means you are more likely to get it right the first time when you get to prototyping and testing. The benefits of an approach utilizing virtual prototyping with digital twins are many. You have fewer rounds of prototyping, saving money and time. You have fewer ECOs. You stay on schedule. You stay on budget.
So while virtual prototyping is new to some organizations, this approach has advantages when applied to the development of linked smart, connected products and IoT platforms. In fact, Digital Twins are a key enabler.
The Setup Required
How exactly can Digital Twins be used to virtually prototype smart, connected products and IoT platforms? You first need to set up the digital model component of a Digital Twin. As discussed in our entry on Digital Twins, that is one of the following:
- Numerical Models: These models use algorithms such as machine learning and artificial intelligence. These applications or agents either extrapolate that data and/or correlate data to existing events. Both are an effort to predict future behavior.
- 1D Simulation: These models are a combination of flow diagrams with equations or formulas behind the blocks that simulate the performance of embedded software or multi-disciplinary engineering systems. These models can provide deeper insights into ongoing operation.
- 3D Simulation: These models, often in the form of multi-body dynamics, are commonly used to predict the dynamics and structural performance of products. These models can provide deeper insights into ongoing operations.
For scenarios based on engineering physics or asset operation, no prototype or operating product exists. As such, there is no sensor data to feed this digital model. However, the model can be fed historical sensor data from prior products or even from past physical tests or operational data. In the worst case, a set of inputs can be modeled using statistical analyses or even a higher level simulation, such as a multi-body dynamics model. This creates a set of input data that can be fed to the digital model.
The combination of that digital model and the input is enough to get started. You run the model as a simulation, generating data from virtual sensors, which are points of measurements from the simulation. In this application, the data generated virtually from the simulation is used instead of physically recorded data from sensors. That output can then be fed to an IoT platform as if it were receiving streaming data from a running product. Only, in this case, there is no physical product. There is only a virtual product that is running in a simulation.
In this scenario, you overcome many issues that you might experience when trying to physically prototype a smart, connected product.
- You can change anything related to the sensor configuration, including placement or type.
- You are not limited by network bandwidth other than the limitation between the compute resource running the Digital Twin and the one running the IoT platform.
- You can change the product’s design in terms of mechanical or electrical hardware, embedded software, systems and more.
There is a tremendous amount of flexibility with this approach.
The Answers Gained
Alright. So we now have this concept of using a Digital Twin to virtually prototype a smart, connected product that is linked to an IoT platform. What does that get you? Interestingly, it allows organizations to answer a set of serious questions.
- Is the electrical systems’ configuration right for this product?
- Is the right data being captured from the product?
- Are the right sensors being used to capture that data?
- Do we need to use a physical sensor to capture this data, or can it be a virtual sensor?
- Is the data we want to flow to the IoT platform limited by network bandwidth?
- Is edge processing required for the sensor data?
- What data should be processed on the product versus being fed to the IoT platform?
- Is the mechanical design right for this product in the context of electrical systems?
- Are there changes that should be considered to improve the placement of sensors?
- Are there changes that should be made to avoid electromagnetic interference?
- How will the smart, connected product and the company’s IoT platform work to fulfill requirements?
- What conclusions can be drawn from the data once it is in the IoT platform?
- Should the data be analyzed manually?
- Should machine learning be applied?
- What data trends are precursors to events critical to the smart, connected product?
The powerful aspect of this use of a Digital Twin is that you can answer these questions without any physical prototype or testing. Everything is digital. So you are getting smarter about the operation of this product without spending any money to build anything physical.
The Impact Realized
What’s the outcome here?
Engineering organizations have been using the “Get It Right the First Time” principle to avoid all sorts of nasty development disruptions for decades. At this point, applying it to mechanical and electrical hardware is a no-brainer.
With respect to developing smart, connected products linked to IoT platforms, we’re in the early stages. But soon, some companies are going to want to sidestep all those nasty development problems they’re experiencing. They’re going to realize that building and testing five rounds of prototypes is unacceptable. They’re going to realize that a three-month delay completely undermines their competitive position in the marketplace.
As a result, those companies are going to want to adopt more proven and standardized practices. Virtually prototyping with Digital Twins is not there yet. But given the rush of companies toward the Internet of Things, I expect the demand for this practice to only increase.