The digital twin is giving companies the ability to enable a fully digital enterprise and get their products to market faster than their competitors.
I recently spoke with two colleagues about how they see companies leveraging digital twin technology to overcome challenges and continuously innovate, as well as the ways different industries can learn from each other about using the digital twin to perfect their products and processes. Dave Riemer is the Vice President of Aerospace and Defense Strategy, as well as one of our Thought Leaders, and Dave Lauzun is the Vice President of Automotive and Transportation Strategy. Here’s what I learned.
How are aerospace, automotive companies responding to the digital twin?
The digital twin is an important part of innovation in any industry because it helps companies create a virtual representation of everything it needs to take something from an idea to a product. But a digital twin by itself isn’t enough to help you innovate, Riemer says.
When he discusses digital twin technology with aerospace companies, he emphasizes that the digital twin is able to tell you that something is happening, but not why. The digital thread is what helps you connect that information – and that’s the message he sees resonating most with companies.
“The thread ties that information together so it’s no longer separate islands of information,” he said. “This message is really resonating with customers, and that message is everywhere, too.”
This message also resonates with automotive companies. They’ve known about the importance of a representative digital twin for years, Lauzun said, but they’re realizing how much their digital twin technology must improve as they continue their work – particularly work on autonomous vehicles and electric vehicles, which he calls “the pinnacle of automotive innovation.”
With autonomous vehicles, for example, it’s impossible to test vehicle reliability using physical testing and imprecise analytical models because there’s an infinite number of combinations to test. Automakers need to include new factors, such as environmental conditions, other vehicles, pedestrians and traffic signs, as they test autonomous vehicles.
Lauzun said the increasing number of factors to test, as well as industry predictions that virtual testing will soon face a 10-fold or 100-fold increase, is forcing automakers to realize that traditional methods simply don’t cut it – and that their digital twins need a much higher level of fidelity.
“If you’re going to do much more virtual testing, it’s much more critical that your digital twin is as representative of the real vehicle and traffic conditions as possible.”
How will companies change how they leverage the digital twin in the future?
As Riemer has talked with aerospace companies about digital twin technology, the biggest change he’s seen is the level of commitment to create one. Many of the companies he’s met with are working to have a full digital twin implemented in their systems within the next five years, and if not, then well within the next decade.
“Initially, even a year ago, it was sort of an abstract concept,” he said. “Now it’s much more tangible and real. They understand what they need to do through a lot of what we’ve done as a company.”
Automotive companies need to continue making their models more representative of the many factors they need to test, but Lauzun says there still needs to be more fidelity in the digital twins they use.
These precise models are crucial as they work on innovations such as autonomous vehicles. Companies working on autonomous vehicles now use what Lauzun calls environmental digital twins – twins that represent roads, traffic signals, other cars and even people – to gather that information and teach those cars to make accurate, safe decisions.
The fidelity of these twins will be crucial as companies use the results of their analytical and virtual tests to make important decisions.
“They have to really understand if that vehicle will be able to swerve around that baby carriage in the road, for example,” he said. “They’ve never had to deal with that before.”
How is the digital twin increasing innovation and competition?
Innovation continues to be a competitive differentiator in the aerospace and automotive industries, and digital twin technology plays a major role in that innovation.
Companies currently innovating in the aerospace industry, for example, are at the forefront of that innovation because of how they’ve implemented the digital twin and the digital thread, Riemer said. He pointed to one company frequently making headlines for its innovation: SpaceX.
“What enables a company like SpaceX to develop a rocket for half the cost is their ability to, quite frankly, create processes that take advantage of the digital twin and the thread,” he said.
Aerospace companies have experienced plenty of headaches with the time and money it takes to fix problems later in a project. Riemer says many of these companies, including SpaceX, are realizing the value of leveraging the virtual world to fix problems and meet performance requirements before they ever build products.
But the industry is a competitive landscape, he added, and Siemens PLM continues to work with multiple companies to ensure innovation continues.
“We’re giving them the tools to develop cheaper rockets – maybe even cheaper than SpaceX.”
Digital twin technology continues to play a crucial role in automotive innovation, particularly with autonomous vehicles, Lauzun said.
“Everyone’s doing it and using it,” he said. “No one, maybe other than a few start-up companies, are trying to get to autonomous vehicles without very representative digital twins of their vehicles and their performance.”
The fidelity of the digital twin is the key to that innovation, he said, but companies are also using digital twin technology to work toward more perfect change management.
Record keeping and model management hasn’t always been great in the industry. Lauzun said companies have often found they were using older models on top of newer models to compare analytics. This can’t happen when designing autonomous cars, which will need to make decisions affecting the safety of many people.
“All models need to be equally strong and have high fidelity,” he said.
Synergies between the aerospace and automotive industries
Riemer and Lauzun agree that the aerospace and automotive industries are much more similar than most people realize.
Integrated electronics in cars, for example, is making the automotive industry today more like the aerospace industry, Riemer said. The systems are all highly sophisticated, and they resemble a lot of what’s been developed in the aerospace industry for decades.
“These systems won’t be completely independent from the rest of the vehicle anymore,” he said. “Everything is all electrical and integrated.”
Lauzun also sees how similarly products are developed in both industries.
“How you apply them to airplane or to a car is different, but the basic process and tools you use to design a car aren’t that different than what you use to design an airplane,” he said.
Each industry is taking something from the other as they continue using the digital twin in their processes. In aerospace, Riemer says there’s a much higher adoption rate from the automotive industry of robotics. Automotive led the way in robotics to do specialized tasks at a high volume, but they can be more flexible for aerospace companies.
“We don’t need a robot limited to one or two welds or activities,” he said. “They can be far more flexible, so we’re seeing much more flexibility.”
In the automotive industry, Lauzun says companies are facing a lot of the same challenges aerospace companies face, including next generation design methods, integrated software development, weight reduction, verification management and system safety/reliability. These challenges are providing a unique opportunity for each industry to teach the other.
“As I see it, the aerospace industry has been ahead of the automotive industry in a few areas, and the automotive industry has been ahead of the aerospace industry in a few areas.”
He pointed to how automotive companies can learn from how aerospace companies have led the way in system safety and reliability, as well as autonomous abilities. But the automotive world is ahead of the aerospace world in a few other areas, such as lean product development, or agile and lean manufacturing.
“We can learn from each industry about the common challenges in these areas.”
Riemer thinks one big thing the automotive industry can take away from aerospace companies right now is the system safety and analyses they’ve done for decades, especially for autonomous cars. He says the automotive industry could be in for “a real surprise” when autonomous cars hit the road.
“It’s inevitable that there will be accidents,” he said. “There will be far less than today, but things will still fail on the car. When it happens, it won’t be you driving – it’s going to be the vehicle.”
That means that the automotive company that put the car on the road will be at fault, and Riemer says this means the industry will see big changes with liability.
“I think product liability will dramatically change that landscape and affect the way they do their design and analysis,” he said, adding that the digital twin will be crucial as liability cases go to court so companies can show how the digital twin was used to test and verify safety processes.
These are certainly big challenges automotive companies must face with autonomous cars, but it isn’t all dire. Lauzun thinks another technology that could come from autonomous cars has the potential to merge aerospace and automotive industries: flying cars.
“We’re headed to the point where we’re potentially converging these technologies,” he said. “It’s a perfect example of how these industries not only have common challenges, but would be merging together.”
These topics were highlighted at the 2017 Digital Twin Summit, where my colleagues and speakers from leading companies in the aerospace and automotive industries discussed digital twin technology.
About the author
Toni Boger is the editor-in-chief of Digital Transformations, the Thought Leadership blog for Siemens PLM Software. As the marketing coordinator and content strategist for the Siemens PLM Thought Leadership initiative, she oversees the content creation, management, publication and promotion for all content in the initiative. She graduated from Saginaw Valley State University with a Bachelor of Arts degree in communication and English. Prior to joining Siemens, Toni worked as an associate site editor for TechTarget, a technology media company.