How to Simplify Energy and Utilities Field Service with Digital Platforms
Chris Fox posted on September 18, 2020 |
Digital methods to determine how to maintain products and check their performance.
Siemens Digital Industries Software has sponsored this post.
Hydro-Québec, North America’s largest producer of renewable energy, has optimized turbine maintenance schedules with digital methods. (Picture courtesy of Hydro-Québec.)
Hydro-Québec, North America’s largest producer of renewable energy, has optimized turbine maintenance schedules with digital methods. (Picture courtesy of Hydro-Québec.)

The world of energy and utilities has seen major challenges with the onset of the COVID-19 pandemic. While many of us have been relegated to working from home and finding new ways to do work from remote locations, many who perform service and maintenance on infrastructure utilities have to navigate the challenge differently.

Most service work simply can’t be done remotely for energy and utilities companies. What’s more, oftentimes the information to respond to equipment issues is relegated to a single source: a binder in the office.

John Lusty, Global Industry Marketing Manager, Energy and Utilities at Siemens Digital Industry Software. (Picture courtesy of LinkedIn.)

John Lusty, Global Industry Marketing Manager, Energy and Utilities at Siemens Digital Industry Software. (Picture courtesy of LinkedIn.)

“It's really tough to respond to equipment issues when you need to get information out of that binder in the control room or in your office, and it only exists in paper and the office is locked down,” explains John Lusty, a global industry marketing manager at Siemens. “Customers that have a more sophisticated digital enterprise strategy are a step ahead of the document-driven world in that their technical information supporting those assets is accessible to those who need it, where they need it.”

Service and repair systems are being stressed even more as capital expenditure (CapEx) budgets are being reduced.

John Nixon, Senior Director, Energy and Utilities at Siemens Digital Industries Software. (Picture courtesy of LinkedIn.)

John Nixon, Senior Director, Energy and Utilities at Siemens Digital Industries Software. (Picture courtesy of LinkedIn.)

“That's going to mean the existing equipment is going to have to get pushed even harder, run longer with shorter outages and so forth,” says John Nixon, Senior Director for Energy and Utilities at Siemens. “Siemens comes to this industry with a lifecycle view and we really mean that. We look at the front-end CapEx and we look at how it's beginning to put pressure and stress on service and repair for existing OpEx [operating expense]. So when I look at COVID, the longer the virus is in place and the more resources are being released, the more CapEx is being reduced and the more pressure you're going to see on service and repair.”

The Value of a Digital Twin

A digital twin, essentially a digital replica of something in the real world, can leverage the same systems and data used in the real world to test or simulate in the digital space.

Digital twins are valuable when designing and developing a system, but they often get lost in the shuffle as a useful tool for operations. Nixon argues that the digital twin may be even more valuable when it comes to servicing energy and utilities systems.

“When you look at service and repair, you've got to make sure that the digital twin is right, that the data and the models and the drawings—all the documentation that went from commissioning over to the operations group or the maintenance group—is in the digital twin that they're using to determine ‘How far can I push this before the next service outage?’”

While it’s easy to see the value of having a digital twin when it comes to maintenance—such as proper service roadmaps and systems documentation that are accessible anywhere—keeping that data up to date is vital. That means that the digital twin needs to stay updated with the service and maintenance being done, who did it and what any other inspections may have implied.

“What is going to be required for repair? How can I do that digital repair effectively? Does my digital twin match the physical reality in the field?” Nixon asks. “We're seeing challenges on the front end, looking at this holistically, that pressure is on service and repair. With COVID and with this pressure of keeping resources to a minimum, it's even more important to make sure that your digital solutions support that minimalistic deployment.”

Gathering Data Is Just Part of the Equation

“I always think IoT and AI and machine learning are the first part of the question,” says Lusty. “The second part is, ‘Okay, I've got that information; now I need to do something with it, and it needs to provide an insight that has value that solves the business problem.’ That's a lot harder.”

The inclusion of IoT and all of this data gathering has been said to be the harbinger of the next era of manufacturing, engineering and logistics, but there’s often still a disconnect. We have the ability to collect lots and lots of data, but then what?

For example, Hydro-Québec is an organization that provides customers with hydroelectric power as the largest power utility in Canada, while also commercializing its expertise and innovations. Hydro-Québec wanted to optimize the maintenance of their large hydroelectric turbines, but since these turbines are needed around the clock, shutdowns need to be kept to a minimum. To that end, maintenance and repair needed to not only be efficient, but also infrequent.

Nixon explains, “Because Hydro-Québec was taking IoT data and they were saying, ‘Well, look, we run these turbines at 120 percent. If you did that, what would it take back on those turbines? Could we get more power? What is the trade-off between wear and tear, and potential outages versus what we can actually do for supply and revenue generation given the competitive nature of the power utility industry?’”

Leveraging a digital twin and the viable data, companies like Hydro-Québec can test their theories before ever putting their equipment to the test. “We do it first with a physics-based analytics tool before you would ever do anything physically,” Nixon says.

Finding the best way to use the data and provide it with a solid backbone structure so that the information is properly distributed seems to be essential to the valuable use of IoT, AI and machine learning.

Using PLM as the Backbone for Data

Product Lifecycle Management (PLM) has long been considered a product-based concept, but in the world of energy and utilities, there really isn’t a physical product.

“Well, really you do [have a product], your product is an electron coming out of your plant. It could be a barrel of crude too, but at the end of the day, you're taking factors of production,” explains Lusty. “You're adding value to them, and you're going to produce something that's going to be sold. The data doesn't care what the rendering of the finished product looks like. There's still change to be managed. There are processes that have to be executed and optimized. They're really not that different.”

There is a lot of data floating around, but unorganized information is more often than not useless information.

“While we love Excel as much as the next group of engineers because it's so accessible and we can do anything with it, it's fundamentally unmanaged and not secure,” says Lusty. “So how does a customer, when they've got to react quickly, get at that digital twin in an effective manner?”

Lusty argues that the proper implementation of a PLM system can make all the difference in the world for managing and leveraging this data.

“Unlike the manufacturing and mechanical CAD worlds, plant CAD tools were never designed to come together. At the end of the day, you have the owner operator who is trying to operate their facilities, sometimes under duress such as COVID or an outage or market volatility, and their information is scattered in several buckets, and they can't bring it all together in order to make consistently good decisions.”

“With CALM [Capital Asset Lifecycle Management] we worked hard to build the ability to bring data sources together that had never been brought together,” Lusty continues. “In energy and utilities, it's not so much an emerging technology as it is an emerging capability to actually create that true digital twin.”

Service and Maintenance Done Remotely

While there are many ways to gather data, and leveraging that data has become simpler, in the age of the COVID-19 pandemic—or any other market-disrupting challenge—is it possible to do field service and maintenance remotely?

France’s Naval Group uses Diota, a Siemens partner, for an augmented reality check of a part. (Picture courtesy of Diota.)
France’s Naval Group uses Diota, a Siemens partner, for an augmented reality check of a part. (Picture courtesy of Diota.)

Siemens partner Diota is providing augmented and extended reality solutions to help with servicing in the aerospace industry. “With some of our aerospace clients, you have very specific bulky procedures as you do in energy,” Nixon says. “And it will actually highlight which bolt is next and to what torque you're to do it, and it sits there and highlights it right there as an AR or an extended reality experience.”

Lusty explains further, stating, “In energy and utilities, we have just as many of the baby boomers getting ready to retire as every other industry. So, one of the challenges in our industry is that all those assets that people are working with are often filled with flammable liquids, and being able to access the right information on the spot is incredibly important.” That information is difficult to access if it is buried in an office binder, or in the mind of a recently retired engineer.

Augmented reality, combined with having the information organized on an accessible platform, could be used to inform a less experienced professional as they encounter challenges. “That information has to come from somewhere, so we come back to a comprehensive digital twin. Without that, you're in trouble,” Lusty adds.

With a digital infrastructure that includes digital twins, accumulated data and a backbone to connect all of the information, service and maintenance could not only become easier, but also more efficient. Entire facilities could, in theory, become much more resilient by tying together all of the data that the system creates and using that to test new concepts and techniques, without ever shutting down a piece of equipment, much less a plant.


To learn more about Siemens Xcelerator, visit siemens.com/portfolio.

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