In this episode, Allen and Joel speak with Tom Brady, CTO of SkySpecs, to discuss the challenges and solutions in managing multiple data sources in wind farm operations. Brady explores how SkySpecs is revolutionizing wind turbine maintenance through integrated data analytics, advanced drone technology, and AI-driven decision-making tools, while sharing a glimpse into exciting R&D developments that promise to transform the industry’s approach to predictive maintenance.

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Welcome to Uptime Spotlight. Shining light on wind energy’s brightest innovators. This is the progress powering tomorrow.

Allen Hall: Welcome to the Uptime Wind Energy Podcast. I’m your host, Allen Hall, along with my co host, Joel Saxum. We’re going to discuss a challenge that’s becoming increasingly critical in our data driven world, managing and integrating data from multiple sources in wind farm operations. In the age of smart turbines and lot sensors, wind farm operators are awash in data.

But here’s the catch. According to a recent industry survey, a staggering 54 percent of operators find managing multiple data sources to be difficult or very difficult. It’s like trying to conduct an orchestra where every instrument is playing from a different sheet of music. In today’s episode, we’ll be diving into this data dilemma.

We’ll explore why integrating data from various sources is so challenging, how it impacts decision making and operational efficiency, And, most importantly, what innovative solutions are emerging to tackle this issue. But that’s not all. We are also pulling back the curtain on some exciting R& D projects at SkySpecs that promise to revolutionize how we handle data in the wind energy sectors.

From advanced analytics to machine learning, we’ll get a glimpse of the future of wind farm data management. Our guest is Tom Brady, the CTO at SkySpecs. And Tom leads the technology vision and development at SkySpecs, overseeing the creation of innovative solutions for the wind energy industry. His expertise in managing complex data systems and R& D initiatives is crucial to addressing the challenges of multi source data management in wind farms.

Tom, welcome to the program.

Tom Brady: Glad to be here. Thank you for having me.

Allen Hall: So we have a lot to discuss actually. So we just got the grand tour of the Sky Specs R& D facility. Both facilities. This is true. We were in the offices also this morning and, we meet with operators all the time. And one of the things they’ll tell us is, or especially if he asked them for data, they go, yeah, we have it, but I don’t know how to access it.

Or I’m not sure what system it’s in. Let me go figure it out. Let me call somebody see if they can figure out where the data is. Or I have too many logins. Oh, absolutely. That’s a common one. Yeah. So what is happening right now? Is it just because we’re just getting so much information? We just lost track of it.

We don’t have any place to put it. We’re using Google Drive still. Some of the operators are using Google Drive, which is insane to me. Is that where we are in the wind industry?

Tom Brady: I would say all of the above. Winding back a little bit to when we got started in the industry back in 2016, we launched our autonomous drone inspection or blade inspection product.

And prior to us being on the scenes we did our typical market discovery, customer discovery, learning a little bit about the market that we were about to try to enter and something that we saw was common across the board was exactly as you say, I’ve got folder folders in Google drive folders in box.

And, maybe I’ve got I’ve got something like maybe I’m organizing by site, turbine, inspection date, blade, and then, radial distance. That might be how I’m organizing my inspection data. We, a couple of times, tried to ask our customers, Okay, can you show me the data from last year versus this year?

Has anything gotten any worse? And, I’m like, It wasn’t even a question that anyone was thinking about, at least at the time. There’s also this backdrop of increasing blade issues and blades becoming an even more important operations and maintenance concern. But I would say it wasn’t even a thing back then to try to answer those kinds of questions.

So I think that is one part of it. There weren’t, without now we’re seeing more of these modern data systems that can actually relate. And answer those questions in different ways that customers want to ask them. So that’s a big part of it. And I think the other big part of it, which we probably don’t talk enough about is that it’s really hard to compare apples to apples when I’m talking about, maybe it’s a drive train related issue or a blade related issue or performance related issue.

So all of these systems exist in these different silos. And you talked about the, I have too many logins. Like I’m thinking about who is that asset manager? Who is that person that cares about, All of the issues, not just the blades, not just the drivetrains, not just the performance, but all of it holistically and I personally can’t imagine what that must be like for them because there is no, there’s not a there’s not a common way of speaking about maintenance issues or asset health risks that is common among all of those different data sources or main components.

So I think that, that’s a big one for me and that’s one that. Drives a lot of our strategy, especially as it relates to our acquisition strategy. You may have seen in the last three years, we’ve acquired, a CMS company. We’ve acquired a finance class management company and a performance company.

And that’s what we have our eye on is how can we actually tell a cohesive story and drive that insight to action across all of these different main component areas?

Joel Saxum: At the simplest level let’s dive down and do just a blade problem because I’ve seen this before, right? At the simplest level and internal damage.

And an external damage many times are related. Absolutely. But unless you have a decent data set, that is a, catalog data set, you can’t do that. You can’t look at them because what you’re saying about the, how you guys got into, the blade inspections with autonomous drones, that was really the first, really good data structured inspections where you could call up on, Hey, I would like to look at this radius on the leading edge of these blades.

Okay, so you guys started that as a cascade and everybody else has followed suit and now it’s become normal in the industry and that’s fantastic. But now even two years ago, internal inspections, people were not looking as it was more of there’s technicians in there, they have a camera and they’re pulling a tape measure and they think they’re about four, 14 meters in the blade and they got a picture.

Am I looking at the trailing edge or what bond line is that? But now you see that how those things could be related. So when we talk about large data sets, Now you’re talking, you’re getting even more in depth saying there may be a way where we can tie CMS data to blade damage data or something of that sort.

Absolutely. But you need to be speaking the same language. This is a thing I always go back to language wise is what people don’t understand, they say the Wi Fi. Actually, Wi