One of the most important technological trends in the Industrial IoT realm is the digital twin. By replicating a real-world object or system, industrial companies can use digital twins for product testing, streamlining maintenance and optimizing asset performance. Gartner has hailed the technology as one of the top strategic trends for 2018, adding that the technology will only gain power with the proliferation of connected sensors, which could number 21 billion by 2020.
But digital twins are real, live and in use now, said Deborah Sherry, senior vice president and chief commercial officer at GE Digital. “We are approaching a million digital twins in active deployment across the world,” Sherry said in a recent interview. “You get a digital twin with every piece of GE equipment that we build and ship. Every jet engine we make — 70 percent of the world’s jet engines — has a digital twin.” Those intelligent jet engines track 5,000 parameters from two dozen sensors enabling the company to predict what happens to the engine and when it needs maintenance.
In the following Q&A, Sherry shares her perspective on digital twins, the GE Predix platform, the bright spots and challenges in the IIoT landscape, as well as the importance of diversity in digital transformation efforts.
Where is GE in terms of digital twin adoption?
Sherry: We are using digital twins for all kinds of equipment — not only with our own. We have deployed a digital twin with one of the world’s largest beverage makers, which is using it for their filling and labeling equipment.
Digital twin technology has been industry ready for a long time, and it can help you solve real problems. It is deploying AI to continuously look and to make better predictions and analyses to enable you to manage your equipment and processes better. We are deploying the technology in more circumstances for industrial pieces of equipment and for whole plants or factories. It is improving and delivering better and better results.
Another important point about digital twins is their potential for simulation. If you determine what a repair should look like, you can simulate it with a digital twin to make sure it is going to work. And then you send the right technician at the right time with the right tools.
What do you see as the current bright spots and challenges for IIoT?
Sherry: In terms of challenges to broader adoption, there is the technology fragmentation of the industry. There is also a lack of visibility into a lot of industrial assets. I would say that those are two key issues.
Another big barrier to the success of IIoT in the short term is that it requires a significant cultural shift in companies. If you study organizational behavior, you know it can take many years to make a massive cultural shift in a huge business. From a structural organization standpoint, it requires a significant cultural shift to change how you operate — to shift from slow timelines to flexible ways of working and applying agile development in the industrial sphere.
Security is another area I would look at. It is much bigger than just a technology issue because it also involves a culture and people and behavior. People need really strong internal processes supported by IT functions to protect data.
There is still a host of opportunities in Industry 4.0 and IIoT and a host of companies working to drive change. One example [of a promising technology] is additive manufacturing. We acquired the German company Concept Laser active in this area. There are just enormous cost efficiencies and production efficiencies. Depending on the parts that you are printing in additive manufacturing, you can achieve many other second order effects. With jet engines, you also can get fuel savings from printed fuel nozzles. You also have a lower cost to produce those nozzles and less waste.
Also with IIoT, another gamechanger I see is the use of edge computing with cloud computing. You can get the best of both worlds. You can do superfast and super secure computing at the edge but also pull masses of data into the cloud to do unbelievable AI at scale.
What do make of the current state of IIoT security?
Sherry: A lot of times, people think IIoT security is about IT security. In fact, it is about OT security when you are looking at the industrial internet of things. There are a lot of great products that enable you to secure all of your operating technologies including cloud-based data, whether it is upstream or downstream. But I am not sure every company always has the right depth of understanding. A lot of times, companies think: We have IT security and we’re done. But in large and mid-sized organizations, you are seeing more focus on securing operational technology. The security tools and the expertise that is out there is growing by leaps and bounds.
How important is it for industrial companies to have role models to help guide their digital transformation?
Sherry: Political issues notwithstanding, if you look at an Amazon or an Uber or Airbnb or even a Microsoft, you see that the most successful players have created broad ecosystems of technology. They created platforms first of all that changed the economics, enabling them to scale rapidly. You see that with Android and Apple and that was the driver of success of companies like Uber or Airbnb — they had a platform that enabled them to scale rapidly. And when you look at an Android or an Apple, you see an ecosystem around it. That enables you to create value, with your developers, consultants, end users. In the end, it is about scalability — having scalable platforms and ecosystems that enable you to deliver broader value.
You could argue in the old days that this is what a fax machine was. It was a platform deployed for communication. Suddenly, before the modern digital world existed, you had people sending documents all around the world. The fax machine was a scalable platform in that sense.
That is what is great about using an Amazon, an Uber, an Apple or an Android as a role model. Digital inventors basically spearheaded this transformation in their industry by building an ecosystem that enabled you to form strategic partnerships across the industry and drive it forward as an ecosystem by delivering a platform that enables you to scale rapidly. That is exactly what we have done at GE. We have spent the last five years developing our industrial internet operating system, the Predix platform, creating an open community of partners. We have over thousands of certified developers and systems integrators on Predix.
There are thousands of developers certified on Predix and hundreds of applications that have been developed for it outside of GE. It is an open community. Anybody can develop for the platform and it is an ecosystem that allows us to foster a relationship with partners and customers so that they choose something we built. Millions of applications are on this platform. You might want a specific microservice and application for a very specific problem that doesn’t exist yet. And you can build that within weeks.
Predix is a development platform that can accommodate a wide range of applications spanning multiple technologies. That goes from connectivity, embedded computing right through to AI, analytics, security and data governance.
In terms of role models, we’ve learned this platform approach from them. And we hope to be a role model as well going forward. We have deployed this technology in the industrial space. We sought to deliver similar results as our role models in terms of value and scalability across the industrial ecosystem.
What do you make of predictions that the IIoT platform space will consolidate in 2018?
Sherry: The industrial space is definitely very fragmented. I would say that many folks claim to have a platform where what they have is a subset of capabilities. But I don’t think you will see 2018 be the year of shakeout though. We are at quite an early stage in IIoT.
How do you recommend that industry professionals keep their bearings in the IIoT landscape?
Sherry: I think you need to identify what are your key business terms and problem areas. Maybe you are in manufacturing. Machine or equipment uptime could be a priority. Or logistics could be. If I had to advise on where to start in IIoT, I would say identify the business problem and look at the technology capabilities that could deliver that. Narrow your IIoT search and find out what you are tracking and the value of that. Start with the business problem and stop trying to pay attention to everything. That can help crowd out some of the noise.
I’ve heard you say before that diversity is an essential aspect of digital transformation. Can you tell me more about that?
Sherry: First of all, when you are transforming your company digitally, there is always a cultural transformation. When you are going through a transformation, there is a good chance to really challenge all notions. Culture change is also an opportunity to pay attention to issues of diversity.
There are studies out there that show that companies that have diversity of all sorts make better decisions. They make better return on investment. Whatever products you make, when your company actually mirrors your customers, you understand your customers better.
If you are going to deploy a technology to improve performance, the best way you can do it is having diversity through your company at the same time for a double win-win.