The Trend that Puts PLM and the Manufacturing World on Its Head
Verdi Ogewell posted on May 02, 2019 |

Siemens’ large stands at the recent Hannover Fair largely represent today’s clearest trend in PLM, automation and manufacturing. Few players, if any, have come as far on the journey in the digital industrialization project as the German industry-IT giant.

Among the visitors–over 150,000 people from the world’s leading companies passed through the stand during the week of the Fair–the curiosity is also great: What does it look like, the digital enterprise, which the company claims is the embodiment of the fourth industrial revolution, Industry 4.0 and Industrial Internet of Things (IIoT)?

Seamless connections, which not only link product development and manufacturing but also play a decisive role in the products in the end users’ hands, “put the world as we learned it on its head,” said Siemens CEO of the Nordic Movement, Ulf Troedsson.

Engineering.com met Troedsson and the company’s Nordic head of the PLM, Mats Friberg, at the Hannover Fair.

“At the basic level, it is about being able to transfer the entire code for how the manufacturing process will look like to the production line,” Troedsson said.“With digital twins of the production processes, these can be virtually simulated and optimized before being transferred to the physical world and to the PLCs. The virtual and physical worlds are approaching each other.”

This fact becomes more important than one can imagine. It means that we don’t have to experiment, or optimize, where it is expensive to make changes in the physical world.

“We can make it virtually instead to a fraction of the costs,” Friberg said. “This is extremely valuable in today’s tough competition. And with MindSphere, the IoT solution as an interconnected, communicative ‘umbrella’ throughout the solution, there are few who have to think about ‘if’ it’s worth to make a bet. The question is rather ‘when.’”

At the basic level, it is about being able to transfer the entire code for how the manufacturing process should look to the production line. With digital twins of the production processes, these can be virtually simulated and optimized before being transferred to the physical world and to the PLCs. The virtual and physical worlds are approaching each other, says Ulf Troedsson, left.
At the basic level, it is about being able to transfer the entire code for how the manufacturing process should look to the production line. With digital twins of the production processes, these can be virtually simulated and optimized before being transferred to the physical world and to the PLCs. The virtual and physical worlds are approaching each other, says Ulf Troedsson, left.

The faith in the future is unlimited among the Siemens’ people in Hannover. The company has put together a suite of digital tools that live up to the dream of the entirely connected development chain, and it is the software that makes most of the job.

150% BOM

Sure, the company has always been well-equipped in the software portfolio. On the product development page, Teamcenter is the backbone of product data management while the CAD flagship NX is the engine of the product definition work and the Simulation & Analysis (S&A)platform, Simcenter, creates the virtual environment where everything can be tested.

Neither is the Tecnomatix digital manufacturing platform–closely linked to Teamcenter–any news. This solution is used to plan, connect and optimize production management and then send the ready code to the workshop floor in the next step, where the PLCs and everything else inoperative technology (OT), takes over the physical production.

All that has been in place for a long time. But, step by step, the capabilities have been refined, the “tentacles” have been stretched further into the workshop floor and the integration between IT/PLM and OT has reached new heights.

“Today we realize what we call 150 percent BOM (bill of materials),” Friberg said. “The information is now flowing in an unbroken, automated stream from the eBOM (engineering BOM), via the mBOM (manufacturing BOM) to the sBOM (service BOM), including the BOP (bill of process).”

The information is now flowing in an unbroken, automated stream from the eBOM (engineering BOM), via the mBOM (manufacturing BOM) to the sBOM (service BOM), including the BOP (Bill of Process). “We are the only one here to realize the industry,” asserts Mats Friberg, responsible for Siemens’ PLM area in the Nordic region.
The information is now flowing in an unbroken, automated stream from the eBOM (engineering BOM), via the mBOM (manufacturing BOM) to the sBOM (service BOM), including the BOP (Bill of Process). “We are the only one here to realize the industry,” asserts Mats Friberg, responsible for Siemens’ PLM area in the Nordic region.

GE’s Predix Platform Felt as a Threat

True or not, it sounds impressive. Not least in light of the importance of the BOMs in, for example, the automotive industry, where BOMs can be described as the industry’s “bread and butter.”What makes the German workshop-IT giant’s heart beat even a little faster is the MindSphere software.

“Absolutely, that’s how it is,” Troedsson said. “Sure, as most others in the automation industry, we were a little worried when GE launched its Predix platform four to five years ago. It felt like a threat. But we gathered and invested. With MindSphere in place, we have taken PLM and IoT to new heights.”

What is MindSphere? It is an open IoT platform and operating system, according to the head of Siemens Nordic movement. This solution concludes the product lifecycle loop: Data from the product in the field is fed back to the PLM system (in this case, PLM/Teamcenter) to further sharpen the innovation based on how the product works in real life.

Mendix Closes Aras’ Opportunity Window

He also noted that the purchase of the low-code developer Mendix, a little over a year ago, meant a lot to the customers and has added opportunities to quickly build apps, thus significantly improved the capabilities related to both PLM and ERP.

“Mendix sucks information from enterprise systems, such as PLM and ERP, and can present this information in a modern app format. In our view this closes the window for challengers like Aras, who often come in with a whole system as a solution to something that might actually really just be a specific, individual problem,” Friberg said.

When is edge computing needed? “Take complex AI-controlled machine operations as a typical example of occasions when edge can be useful. You do not want to send the gigantic data volumes involved through the cloud while requiring second-rate response. Now we can instead process this locally within our solution,” says Mats Friberg. (Image courtesy of Siemens.)
When is edge computing needed? “Take complex AI-controlled machine operations as a typical example of occasions when edge can be useful. You do not want to send the gigantic data volumes involved through the cloud while requiring second-rate response. Now we can instead process this locally within our solution,” says Mats Friberg. (Image courtesy of Siemens.)

Edge Computing for Faster Response

Another thing that attracted interest in Siemens solutions among the visitors was the edge computing bits.

“Yes, we’ve noticed this here in Hanover,” Friberg said. “In our solution, Sinumerik Edge, we encounter things that require immediate, millisecond-capable response to large amounts of data. Take complex AI-controlled machine operations as a typical example of occasions where edge can make a difference. Nobody wants to send the gigantic data volumes involved through the cloud while requiring second-rate response. We can instead process this locally within our solution.”

The edge concept goes back to the huge increase in data traffic. The network giant Cisco predicted an almost four-fold increase in cloud traffic between 2015 and 2020, from 3.9 zettabyte to 14.1. One byte is equivalent to 1 billion terabytes.

With these volumes as a background, it becomes clear that cloud traffic is becoming very troublesome when the infrastructure is burdened with these enormous amounts of measurement data from tens of millions of connected IoT devices.

So, what do you do? Edge computing is the quirky answer. Instead of sending up these oceans of data into the cloud, solutions have been built up where as much as possible of the large data volumes can be processed locally on the connected units as close to the origin of the data as possible—“at the edge of your network.” Hence the term “edge computing”.

“Edge is also an appreciated capability found in MindSphere and solves data-intensive user cases,” Friberg said.

With the MindSphere solution, one can connect entire fleets of technical units. Take SKF, the ball bearing giant, as a good example. They are a typical example of how to develop new business models according to the “Product-as-a-Service concept”. SKF’s model is to pay per rotated lap in combination with parameters such as early guarantees. (Image courtesy of SKF.)
With the MindSphere solution, one can connect entire fleets of technical units. Take SKF, the ball bearing giant, as a good example. They are a typical example of how to develop new business models according to the “Product-as-a-Service concept”. SKF’s model is to pay per rotated lap in combination with parameters such as early guarantees. (Image courtesy of SKF.)

SKF Connects Ball Bearings and Sells the Service Per Rotated Turn

Perhaps the really heavy point of MindSpere is the IoT ecosystem of partners that adds capabilities through apps on all fronts. Siemens is not alone in the development work. Here, new functionalities, skills and solutions are pushed onto the platform in a continuous stream—AI, machine to machine, APIs, etc. “The sky sets the limit,” is a judgment I heard in the Siemens stand. A rating that does not get worse, related to MindSphere, runs on Microsoft’s Azure and Amazon Web Services (AWS).There are even plans to run it in Chinese Alibaba.

“Additionally, let me point out the advantage of Siemens standing as a guarantor of an open environment with maximum connectivity,” Troedsson said. “You can quickly connect directly to the devices you want to pick up, capture data and automatically configure the system so that they are entered according to the structures you want. In short, integration time is no problem, it all goes very fast.”

Another thing worthy of attention is the scaling capability. One can connect entire “fleets” of technical units. Take SKF, the ball bearing giant, as a good example. They are a typical example of how to develop new business models according to the product-as-a-service concept.

SKF’s model is to pay per rotated lap in combination with parameters such as uptime guarantees.

“It is the principle to charge for their services instead of transferring ownership of the product,” Troedsson said.“The value lies in the services the equipment stands for. Atlas Copco is another good example. There you are paid in the same way per liter of air instead of selling compressors.”

“The concept of digital twins can play a productive role in optimizing the manufacturing processes,” says Siemens CEO of Nordics, Ulf Troedsson. “You can optimize your process by simulating it in the digital twins of a manufacturing line before then ‘shooting’ the code into the PLC environment. This saves both time and money and prevents you having to fix any potential problems in the physical manufacturing environment.”(Image courtesy of Siemens.)
“The concept of digital twins can play a productive role in optimizing the manufacturing processes,” says Siemens CEO of Nordics, Ulf Troedsson. “You can optimize your process by simulating it in the digital twins of a manufacturing line before then ‘shooting’ the code into the PLC environment. This saves both time and money and prevents you having to fix any potential problems in the physical manufacturing environment.”(Image courtesy of Siemens.)

The Digital Twins Play a Key Role

The line of companies that have begun to implement this type of business model can be made longer, but it’s all landing in the product-as-a-service principle.

“The new technology, with sensors and software such as MindSphere, in combination with other solutions such as NX (CAD), Simcenter (CAE), Mentor (PCB & IC design), etc., makes it possible for the new business models where digital twins play a key role,” Troedsson said.

Why are the digital twins so important in this context?

“The digital twins are the virtual replicas of virtual 3D models,” he said.“They can be in the form of product or, for example, a manufacturing line. The virtual world can now be linked to the physical world by means of solutions on the MindSphere platform, where real-time measurement data can be returned to the virtual. There you can then utilize the experiences that have been made and use them for innovations and improvements. In other cases, one can control and optimize a system; or use them for predictive maintenance.”

The latter is, after all, a function that is often emphasized in the context. Predictive maintenance (PM) means that you, for example, change a worn part before it breaks instead of following a fixed schedule, thus keeping production from stopping.

“You can really optimize the operating conditions with PM,” Troedsson said. “Take turbine blades in gas turbines as an example of how this type of maintenance effort is not only used for predictive maintenance but also where you can choose to run a turbine with a 95 percent power effect because it, for different reasons, maybe isn’t suitable to change the rotor blade at the time it was intended. But of course there are a number of parameters that can be weighed into the overall picture, such as temperature, vibrations, power output, etc.”


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