With data being constantly collected from thousands of different devices, sensors, and machines, a new term is being coined for the frontier that will support the migration of that data from the confines of the real world to a universal cloud.
That intersection, where massive amounts of streamlined data can be processed at the speed of light, is called the edge. A pioneering mash-up of cloud technologies, the IoT, and traditional data storage centers, the edge integrates all these disparate and complicated areas. “It’s still a really new technology, but it’s a really powerful way of bringing things together. It’s all about streamlining traffic to the cloud,” Dai Chen says.
Still in its infancy, edge computing is being developed by markets focusing on the brave new world of autonomy. And while China has proven to be a hub of innovation in recent years, its manufacturing industry has yet to foster cloud computing at the rate of their competitors. Dai Chen, a consultant for Siemens in China, hopes to change that and is helping industry adapt to cloud technologies by showing them how to create their very own edge.
On the brink of true autonomy
It’s all very well collecting masses of data, but if you don’t have the capacity or technology to process it quickly and turn it into real meanings then it might as well not exist. Take autonomous cars. Without a person there to take the reins, the car has to rely on its own central nervous system; a spaghetti nest of networks sending information to and from hundreds of sensors and the machine’s processor.
“Autonomous cars send all their data to the cloud, but that’s not always ideal,” says Dai Chen, “Imagine two cars are about to collide. They need to contact the cloud to know how to best avoid the crash, but there’s just not enough time. A better way is for the cars to directly communicate with each other, decide the best course of action, and then send the whole process to the cloud afterwards for analysis.”
It’s not just cars that need an additional veneer of computing power to help them think and act like humans. Any system relying on data to drive insights needs decisions to be made in the blink of an eye. Think of manufacturing.
“We’re sending more and more data from the factory floor to the cloud. And I mean a lot of data. But not all of it needs to be in the cloud, because that tends to be used for long-term optimization. When the data is really urgent, it needs to receive feedback from the system within a standard industrial communication cycle — that’s about 50 milliseconds.”
There’s not enough time to send that data elsewhere, be processed, and returned back to the device, so it makes sense to keep it local: “A powerful device directly on the shop floor could just do all of that, in time, and pack up all the information to send to the cloud.” Rather than a deluge of unsorted information flooding the cloud around the clock, the edge acts as an intelligent filter; sorting through and packaging relevant data before transferring it to the cloud as and when it needs.
Crossing the world for innovation
Even when he was a student, Dai Chen knew he wanted to study a different type of engineering and that it might mean leaving his home country in order to return with a wealth of experience.
Every country has their own way of teaching engineering, but France has a very particular type of program. Developed in 1934, the CIT (Commission des titres d’ingénieur) is the only body in the whole of France authorized to award someone the engineering degree. Today, they oversee a range of schools and universities that train engineers in every subject across the sciences and engineering.
Dai Chen wanted to focus on mechatronics — a hybrid of mechanics and electronics. “It’s not just about the hardware,” he says. “We also covered simulated software, automation, and IT.” Combining physical and virtual types of engineering, Dai Chen used every tool at his disposal to solve complex problems.
Then one day, a visiting professor on his course mentioned he worked at Siemens Industrial Software. “The company develops their own software and we ended up studying it,” he says. Immediately, Dai Chen’s professor saw he had a knack for it: “Even though my French wasn’t as good as that of native speakers, he suggested I have an interview with them.” After a year of intense experience gained while working in one of Siemens’ software headquarters, Dai Chen found himself immersed in the world of simulation. Even when the placement was up, he knew it wouldn’t be the last time he worked for the European arm of the engineering giant.
New talent driving the cloud
After graduating, Dai Chen returned to China. Having acquired such a mixed bag of skills, he wanted to push his proficiency one step further — into the world of consultancy. “I find communicating with other people across different markets fascinating,” he says. “But I wanted to get some more experience with factory automation and was really keen to work in a more developed market.”
After applying and getting onto the Siemens Graduate Program (SGP), he was offered two assignments in his home country of China, and a third eight-month assignment at the company’s state-of-the-art Digital Factory in Nuremberg, Germany. It was there that he was exposed to the notion of edge computing: “I was incredibly privileged to lead the first application using edge computing with Siemens technology.”
Called the SIMATIC Edge, the application combined edge and cloud computing to assess two years of historical data to maximize the productivity of an electronic assembly line. The application was a hit — in a short period of time it used simulation to add a whole new level of value. When on show at the 2018 Hanover Fair — the world’s leading trade show for industrial technology — it was one of only a handful of applications using edge computing, and it beat its competitors. From conception to realization, Dai Chen led the SIMATIC Edge to success.
But despite working predominantly with data, Dai Chen isn’t a number cruncher. “I’m not a data scientist,” he clarifies. “My work doesn’t actually involve a huge amount of data. I create and improve the way we retrieve and process it.” So rather than analyzing the data itself, his role is to develop the systems that orchestrate it. It means keeping abreast of all the inputs and touchpoints that make up whatever system Dai Chen is trying to decode — by extracting every bit of information he can.
Following the success at Hanover, he is now architecting the first app build on the Siemens cloud in China, which will help small- to medium-sized customers get to grips with the upper echelons of the data that’s now driving manufacturing across the world. It’s early days and Dai Chen’s team haven’t come up with a name for the application yet, but he’s working hard to ensure the product pushes cloud technology to its limits. “Edge computing is where I see the future of my career,” he says. “It’s great to be able to see it grow as fast as possible.”
Dai Chen Pu has worked for Siemens in three different countries — China, Germany, and France — and is now a Production System Engineering Digitalization Consultant in Chengdu, China. Find out more about working at Siemens.
