The Energy Transition – Transcript – Part 2
At the beginning of this year, the Industry Forward Podcast featured a discussion with John Nixon, Vice President of Global Strategy for Energy Chemicals and Infrastructure at Siemens Digital Industries Software. John walked me and Dale Tutt, VP of Industry Strategy at Siemens Digital Industries Software, through how the energy industry is approaching its transformation for the future, including some of they key challenges and technologies that may prove crucial to the global energy transition.
You can listen to the podcast here, or read a transcript of that conversation below!
Dale Tutt
You know, one of the things that we talk about in many industries in aerospace and automotive electronics, semiconductor is the amount of digitalization and how digital transformation is enabling these companies to, you know, to bring new products, new ideas to market faster, 30, 40, 50% faster. When they get into manufacturing, they’re increasing their yield. They’re reducing their scrap rates. And so they’re seeing advantages of the ability to both engineer and manufacture products or processes. Across the. So think about the energy companies now. You know, how are they approaching digitalization for the future. And really, what advantages can it bring to them?
John Nixon
Dale, great. When I think about digitalization, I go back in my own personal. I look at 2014, the second-half of that year, we saw the price of oil plummeted going into 2015. Didn’t look like it was ever coming back. It was. Was. It went from like $120.00 a barrel to like $20 a. And it. Just sent the industry reeling. And there was an interview of Craig Ferguson, the CEO of Synovus Energy, in 2015 by Business Insider. And he said I’ll never forget it. And it for me, it just was. Was a perfect. Encapsulation of how everybody felt at the time and he said we must do capital projects with a manufacturing mindset because the delta between efficiencies of the manufacturing floor, the factory floor versus the field that delta has only grown. Exponentially.
And you know, while construction just has struggled while we have struggled in the design build. In the field, manufacturing has continued to you know, quarter by quarter, year by year, decade by decade to improve its efficiencies. And digitalization has only accelerated that, so within. Our asset or process intensive industries of energy, chemicals and infrastructure, digitalization offers huge benefits. I mean tracking from requirements industry regulations. Customer specifications. All of the contract line items. All of these demands upon the design build process that you have to make sure you get right the first time cause the last place you want to do rework is in the field. I’ve seen so many times. Where the failure to ensure requirements are being met, the latest specifications are what you’re actually designing to and all the contractors involved. You may have you know 5-10. More contractors and suppliers all involved in these very large projects and because they’re all operating in a very siloed fashion.
They’re all operating against different versions of different specs over many years, and you find yourself like I did one time where I was in the field and we had an interface between two different contractors and 1 ended up with an 18 Volt flange and another one had a. Volt flange and they were different elevations and suddenly we were pulling our hair out realizing look at all the rework we’ve got to done. How did this happen? And that was one of a multitude of examples. And this goes on all the time, but with tools like digital twins. Right, companies can simulate the entire life cycle of that project before we ever pull out a hammer wrench or screwdriver, right? We can improve everything from materials innovation to maintenance efficiency. And this will only not cut. It’ll drive reliability. The way I look at it, Dale is we talk about product lifecycle management. When we talk about service lifecycle management on all of those equipment and systems, but in between. Is really a capital asset lifecycle management that needs to occur.
So you’re moving from equipment manufacturers to engineering, procurement and construction companies are what are referred to as EP CS as well as the owner operators who at the end of the day take delivery of that plant and. To drive it and operate it to maximum profitability. Well, throughout that you’ve got to have a manufacturing mindset. You’ve got to have a lifecycle approach. And you know, Dale, we hear a lot from people like Roland Bush, for example. He gets up at the Consumer Electronics Show in January of 24 this year, and he starts talking about the industrial metaverse, and this is this incredible vision of what we can bring to customers today.
And within the industrial metaverse are all these investments in artificial intelligence retrieval augmented generation, which we lead in, and how we can drive, you know, intelligence around? But at the foundation of all of that, before you ever get started in driving AI before you ever get to the industrial metaverse, you’ve got to have a strong taxonomy. Got to have strong. Ontologies between the different data within those taxonomies. Translation. You’ve got to have a strong work and plant breakdown structure that has traceable well-orchestrated data throughout the life cycle of any asset or system. And that’s what we, Dale, you and I here at Siemens, that’s what we focus on. That’s what we drive that. So that you have the intelligence in your artificial intelligence that when you’re looking at an industrial metaverse. You actually are looking at a physics informed digital twin of all of that complexity.
Dale Tutt
Yeah, it’s awesome and. And agree and what I really like. You know, I talk a lot about how various industries are learning from each other and we see this everywhere that you know, aerospace is learning from automotive on how to automate and automotive is learning from aerospace on how. Do more software and. And you medical devices are picking up from both of these industries. And so you see this across the board. And I love that and especially when you start to talk about how do you use the digital twin and the metal. The industrial metaverse and do systems engineering all of these aspects that you’ve talked about and then as you were talking. I was thinking about like the. The you know what’s the biggest? You know, when we when we think about and you, your example of the flanges coming together and not matching up. Mean common story in many industries, by the way, and you know, and it’s those kind of changes. That because these big projects, these big capital projects to be overrun, I’m sorry to be, you know, over. Over. They’re late. They’re over budget. And so you have these. Big cost overruns and so you know I think that’s an area where again we’re seeing the value digitalization. Energy, you know, obviously has a lot of these big massive capital. You know the stories. What I was saying earlier about these nuclear power plants and how much they. Costing the 70 S. And. They were always late and so, you know, so let’s talk through how digitalization. You’ve talked about it. Started talking a little bit about it already with calm and with our industrial. But how does IT support a major energy project like the planning and engineering and construction and operation of advanced nuclear plant? Well, what would that digital? Ized planning phase look like for nuclear site. Easy for me to say, huh?
John Nixon
Fantastic. No, you’re asking the very questions our customers are asking us that this industry is wrestling with, you know, like you mentioned, nuclear. I’m glad we are, because that’s one of the most. I mean next to SpaceX, who we support. You know, looking at advanced nuclear moving into this world. For example look, look at. They there was a headline, just what, 2-3 weeks ago? They’re going to launch seven plants, 7 nuclear plants to support their needs. You’ve got Microsoft saying we got to turn three Mile Island back on. I mean. No one would have ever thought that was going to happen. So it just shows you that the demands on the grid, the demands for power that, that, that, that ever growing need is only going to force us to take a hard look at digitalization. How are we planning these? How do we make sure that we plan? To the to the greatest detail as we would on a factory floor, right again that manufacturing mindset, how do we bring that lifecycle mindset into the planning phase so that we. Can have integrated digital platforms throughout the design and the engineering. The procurement, you know a lot of investments been made in energy since the 90s.
I was part of an original ERP roll out when I joined an energy company coming right out of the army. And I remember ever since that point on, it seems like there’s always some kind of ERP roll out. There’s always some kind of digital investment being made and a reinvention of the company, so there’s no shortage of incumbent systems out there. So if you’re involved in and you mentioned about nuclear, but this is true of really anything that’s in an acid intensive world like energy. If you look at the incumbent systems that exist for enterprise asset management or computerized maintenance management systems or enterprise resource planning and the list goes on, you have to think about how can I not lose all of that valuable investment in data. If I’m going to really drive and embrace this digitalization, this lifecycle mindset that John Nixon’s talking about. And so your digital twin, whatever that solution is, needs to be fully. And I and I could say with pride. Dale, you and I are part of a team. We talk about that every in every conversation. How do we drive integration? How do we drive interoperability?
My good friend who leads our integration team? We talk about this. Time. How do we drive a better return on investment for these energy projects? Because we’re fully integrating to all the different side sources. Data to create that digital backbone, and then you really do have not only a physics, but what I would say is a financially informed digital twin around all of this complexity. You know, it’s not just about the engineering. It’s the engineering coupled together with sustainability coupled together with profitability coupled together with. You know of equipment and material and marrying all that together and being able to make the balanced decisions you need to throughout the design build process. As you’re driving towards start up commissioning and start up so we can simulate, we can optimize, we can do all of that before you actually get into the field. And that’s what’s so very important.
And one other thing Dale I’ll mention. I, I said. You know, I’ve talked to a dozen, you know, advanced nuclear companies in as many weeks. And one of the challenges in nuclear specifically, we want to make sure it never happens, is we see headlines like. The word nuclear and delay or, you know, over budget or anything like that, because what’s going to happen is in the psyche of our species. All we’re going to hear is the words nuclear and fail. Then alarm bells are going to go off and the emotions are going to take over. And I talked to our nuclear, you know customers about this that we’ve got to make sure that we bring the lessons of the factory for that they’re going through right now. Designing and building the nuclear devices of the future, the fusion. The small module reactors and then they’re going to bring those to the field.
Well, we have to make sure that when we are deployed to the field, we know how we’re going to build these behind the meter. For example at existing facilities. We’ve got a headline from January 2023. Dow Corporation announced after the 2021 freeze were for a month or I live here in Texas. We lost lights for 30 days and it shut down all of the production of the Gulf Coast. Cress. And you had Dow say that’s it. We’re not doing this again. We’re putting power on site behind the meter and we’re going to put small modular reactor behind the meter.
That’s great, but you’ve got an incumbent chemical facility, lot of complexity, you’re going to need to now build. A power. A nuclear plant based upon advanced nuclear behind that meter. So you’ve got you’ve got all of the interfacing, all of the utility connections, all of the supply that goes in and the supply of power that comes out and the interfaces in between. That’s. That’s an incredible. Now it’s one we can meet. But it’s going to take a life cycle. So again, for advanced nuclear for these kind of major projects where you’re now adding in the complexity of a brownfield or an existing facility, you’re you are, you cannot. Have to take this. From a life cycle perspective, you’ve got to make sure you before you ever get to the field, especially with nuclear that we’ve planned this out. We’ve simulated this out to the nth degree. We get it right the first time and we’re on budget and we’re. Schedule.
Dale Tutt
Wait, you’ve covered a lot of ground there and but you know, it’s fascinating to think about. Hey, we’re just going to put a nuclear plant inside of our chemical plant or whatever. And you know, I guess it’s, you know, when you think about like you know the big ships and the big aircraft carriers and their floating cities and they have a nuclear power plant. On site. Maybe that’s. Along the lines of what we’re going to see more and more often, and that will certainly give a lot of robustness to the grid. But you know, so you did cover a lot of ground there and there’s a couple detail questions wanted to get, make sure we get. And one is, you know you’ve talked about is your designing and using digital twin to design and build a facility and you talked a little bit about model based financial optimization but. Once you get into building the facility itself, I mean that’s, that’s where these problems occur. So, so many of the problems can be addressed with the design activities. I’ve used the digital twin and I’ve basically validated or I’ve commissioned my plant before I ever start building anything. But, and that’s one piece of it and maybe expand on that a little bit, but you know, as you get into building the facility itself, what else can digitalization do to really improve that process?
John Nixon
If I look back at my own history, when you go through construction, often times when you move from construction, then into commissioning and then from commissioning into start up, a lot of the challenges you have in construction, you kind of hand those over to operations and you do it in a big lunge. And so you’ve got all of this data and documentation that gets handed over in commissioning all at once. Or let’s say, in really big chunks. And it can be quite overwhelming.
What I love about digitalization and a lifecycle approach is you now have continuous handover. I was just recently speaking. I say recently it was about, let’s call it 6 to 8 months ago I was talking to the lead for capital projects at a very large energy company in in Canada. And I said picture if you will, that when you have a project you can stand up a cloud in that project. And there are requirements and specifications around contractors and the kind of data you want them to continuously hand over. So that as we go along, we’re able to track against a more manageable volume of data coming at me as a, as an owner operator. So when I. Into the commissioning process.
I’ve already had, you know, weeks, months or maybe even some cases. Years of being able to gather data as we go. That it’s not this overwhelming. Effort to get to the commissioning process and then I spent two years sifting back through all the data that just got dumped on me by my contractors. That kind of environment that, that the lead for capital project, said John. We can do that. Then you put me back in charge of my data. And I actually can have a far more effective and efficient means to consume that data to ensure that requirements have been met and to streamline the commissioning process. So for me, as you think about construction, you’ve got to think about. Digital underpinnings for it and the fact. That every contractor comes with their own fiefdom of data, their own of data, and you can have quite a few contractors and subcontractors on these very large projects. But now, today, because of the cloud. We have an opportunity to mimic what you do physically on a job. What I mean by that is, if I’m a contractor and I want to come work at your job site, I have to get safety training. I have to get permitted. I’ve got to go through quite a litany of. Effort to be able to just get out on site. Then I have to be trained in. For example, if I’m a welder, the Weld procedure I have to be certified on it. Have to actually go through and follow very specific procedures to ensure that the work that’s performed meets specifications.
If I have all these physical requirements for people that are trying to get on my physical job site, I should do no less. I should have digital requirements for people to operate in my digital environment, and so we really need to rethink. The cloud and its capabilities, when we look at construction, it’s a huge opportunity for us as a species to be able to drive a better, more holistic, more effective transfer of data. That becomes well orchestrated and traceable from every contractor, because the last problem you want to have is you’re in operations. And you’ve got a weld and you see crack propagation on that welding. What are you going to ask yourself? Who did the? Did they follow the well procedure? The well procedure certified. Were the materials handled correctly? The list goes on and. Was an X-ray performed or a Hydra test or? On and on and on.
If you don’t have what I just said, this life cycle approach during construction. Then I can’t forensically understand what I’m seeing in front of me and whether it’s a local or systemic issue and if it’s systemic, how big is it? I about to have breaches everywhere. Or is it something that can wait until the next shutdown? This kind of traceability throughout construction leads to success long term in operations.
Dale Tutt
Yeah, that’s good. We I mean you really you know. It sounds like you’re moving from the days of we toss it over the wall from, you know, the you know who’s building it, and then now it’s the operators problem and really having a more holistic view and actually being able to apply more data analytics and. Use an AI to really optimize. The maintenance of the plant and the operations of the plant. So it’s a lot of opportunities here.
Conor Peick
Yeah. And actually, Dale, I think to you know to follow up on that, you know, John, I wanted to ask you a bit more about the actual kind of operations of an energy plant like that and how digitalization can play a role in in the on. Operation the maintenance, the. The upkeep or you know, optimization of how the plant is being run in the long term.
John Nixon
Yeah, Conor, that’s a great. And so, you know, we’ve talked about design, we’ve talked about construction and commissioning. We’ve you’re asking about long term operations. Now, Dale, you often speak about model based systems engineering. I would go a step further. Just as you know, rolling gets up there and he talks about physics and form digital twin, right? We hear Cedric, we hear Tony. We hear all of our leadership zero-in on where we are differentiated when it comes to that physics informed world and I would go further to say because of our integration interoperability that we focused on. We now can drive a model based financial optimization long term with these customers.
So for example, if they’re sitting here and I gave that example of weld and crack propagation and so forth. At the entire acid intake. Landscape at these complex facilities and you think about, OK, how long, how much longer can I go before I’ve got to actually shut? Or can I shut down and part you start making all these trade-offs between revenue and profitability versus safety and reliability. And how do I balance all that to get the best? For the environment, the best for my end customers and the best for my shareholders and I would tell you that. If you’ve got real time operational data, what we call IoT, right, you know, all this operating flow of sensor information that’s coming in and I can couple that with as I said before, a very detailed forensic understanding around the life cycle of every asset right at any data. I would want to ask, you know, where did I source it from? Is it shipped here? Who received it? Who inspected it? You know, so and so forth.
I look at it as a very powerful means to drive long term operational. Now let me let me use an analogy. If I go see the doctor and I’ve got a problem, first thing, the doctor’s going to ask me for is my family history, right? Going to, they’re going to look at the data. Of me the acid, right. They want to look at that family history. They’re going to do some diagnostics. Stethoscope and they’re going to take my blood pressure and so on and so forth. They’re going to get real time sensor data on me. Going to combine that together. To then make an assessment operationally about what needs to be done to ensure my health, that same analogy is exactly what I’m talking about here in operational excellence. I’ve got a full forensic history of family tree, if you will, of data around these assets. I’m coupling that together with the sensor data coming in and or off of the historian.
And now if I combine that with what we call rag or retrieval augmented generation now AI enters into the fold. And can provide me reliable decision? Not hallucinations, but real data and real decisions and decision support around what should be done with this asset or this system or this system of systems. And when you do that, that’s a systems approach, but I would go further to say that you’re also modeling your financial optimization. For me, it’s not MBSE Dale, it’s MBFO, model based financial optimization, becomes a reality. In the industrial metaverse, when you have all of your data sources, all of these silos in operations brought together reliably and traceably then you can attain operational excellence.
Dale Tutt
Maybe you need? Maybe you need a little bit of model-based systems engineering as well as your model based financial optimization. What I’m thinking about here is too often. The in many industries, people tend to think about the comprehensive digital twin. They think about the product, the car, the watch, the smartphone. And they also might think about the manufacturing process, but I think often times they forget about that other aspect of the digital twin, which is really around your business processes that you have all these operate, you have all this operational data, you have all this supply. So that you know, part of that digital twin of your supply chain is actually having that traceability to know how everything. Built where it came. From and was it inspected I mean that those are business transactions, oftentimes their work is completed that needs to be that needs to be done.
But the end operator, if they really want to know the whole history of the plant, they have to have that digital twin of all those business transactions that happen. It’s a business. You know your business, digital twin. Thing is in as you go down into the operation, you’ve got all this data and you’ve got to figure out how to optimize it. And you’re, you know, especially as I say, you’re looking at, you know, maintenance schedules and how do you optimize those maintenance schedules to you? To keep your plant up and running, and as you said you can’t afford. You know you can’t afford to shut down. Plant has to keep running. And you can’t afford an accident that you know that that you know that that causes. I’m going to say, you know, bad press that you know that you can’t afford any of those things.
So you want to make sure that you’re optimizing it and running in the best way so. Really is a great. I think great use cases for the digital twins, so as we’re getting close to wrapping up here, just my last question, but you know is. You know, we’ve talked about so much already, but what do you? Just, you know, as a potential business impacts of digitalization on the energy industry. You know, really think about. How can it help companies? Dr. Efficiency on the business side, which we’ve been just talking about along with engineering and technology side. There anything else you want to add about that?
John Nixon
Well, the impact, it’s transformative, Dale real time data. It of course helps businesses remain agile in their decision making. And the collaboration tools though that you couple with that this is going to enable you, you know across the globe with your global teams to work far more efficiently together. We’ve had customers that have had significant reductions or I should say, improvements in efficiency. Thus, reductions in the amount of time spent. For example, just searching for data. I mean, you, you, you, you hire engineers to come and solve problems and they spend 80% of their day just trying to find a document or find you know the relevant data or the appropriate version of a specification and the list goes on and on, you know.
You’ve got to drive efficiency and innovation. Not only on the business side, which I was just talking about, but on the technical side, you’ve got a lot of expensive people. People that need to do very thought provoking, very powerful decision making and problem solving and I don’t want to have to pay them to spend all their time searching for information. So digitalization, if done right. Just at the most basic level, transforms the day-to-day of your engineers and everyone else in the digital enterprise.
Dale Tutt
Yeah, well, that’s a great. It’s, you know, I think back to my days as chief engineer and how much time was spent by my engineers doing drawings, creating documents. Looking for data, chasing data and the more that we could simplify that I you know, I often felt like maybe 50 to 60% of the time was spent on things that were really just kind of administrative and not really. Allowing them to unlock their creative talents and to really solve the most complex. And in the end, really increase their overall efficiency and in their productivity and maybe their job satisfaction. Anyway, so thank you.
Conor Peick
John. Yeah, I’ll. I’ll second what Dale just said there. John, you know it’s been a genuine pleasure and a really fascinating conversation today. Really glad that you came on the show so quickly to wrap. I was just wondering if there was any more knowledge that you would like to impart on us or the listeners about the energy sector before we before we go.
John Nixon
Energy transition is the defining challenge for our species and for our and for all the generations that Live Today. Digitalization is no longer optional. It is a necessity. Companies in energy that embrace these tools will lead the way. And there was a quote I heard at a trade show. It was someone said along the lines of the future belongs to those who believe in the power of data. I’m actually going to go a step further. The future belongs to those who understand the power of data, the power of digitalization. And you know. Nowhere is that more true than right here in the energy sector.
Dale Tutt
Yeah. Well, absolutely, John. And I, you know, I would probably the only thing I would add to that right now is that something I always tell people is that to truly have business transformation, you have to have digital transformation. You cannot survive going forward if you don’t do digital transformation. And the companies that do embrace it are going to survive, and they’re going to thrive. As a result, they’re going to have more competitive advantage. So you know, obviously energy sector is very important to all of us. We love it. I’m excited about the advancements that are coming and. And you know, maybe we’ll, you know, replace that small. You know, backup generator on our houses with small nuclear reactors. Well, maybe that’s a bit much right now, but in anyway I just want to say thank you for joining us today. Been. It’s been awesome having you here. Very informative for. For me and for all of our. So thank you, John, and I hope you have a great day.
John Nixon
It’s a real pleasure and my whole career and my life at Siemens is to do one thing and that’s to keep the lights on for everybody.
Siemens Digital Industries Software helps organizations of all sizes digitally transform using software, hardware and services from the Siemens Xcelerator business platform. Siemens’ software and the comprehensive digital twin enable companies to optimize their design, engineering and manufacturing processes to turn today’s ideas into the sustainable products of the future. From chips to entire systems, from product to process, across all industries. Siemens Digital Industries Software – Accelerating transformation.
