Episode #53: Automation as a Present-Day Necessity: Building Scalable Robotics Platforms with Darragh de Stonndún
U.S. Manufacturing Today host Matt Horine interviews Darragh de Stonndún, CEO of Automated Industrial Robotics (AIR), about why automation is accelerating and how manufacturers can deploy it successfully. He shares his path from a Guinness apprenticeship in Dublin to engineering and decades in industrial automation, emphasizing attention to detail and disciplined execution. AIR’s platform model unites specialized automation firms across the US and Europe to provide shared standards and global capacity while retaining deep domain expertise. Key capability shifts include data-driven operations, validation-ready systems for regulated industries (e.g., GMP and 21 CFR Part 11), and greater flexibility enabled by robotics, vision, and servo systems. De Stonndún says automation demand is driven by labor shortages, cost pressures, supply-chain resilience, and policy, representing a long-term structural shift tied to reshoring and reindustrialization. He outlines where projects fail (scope and integration), what roles are rising (automation technicians, process engineers, quality/data), how AI will enhance inspection and control layers, and cites a pandemic-era pharma turnkey filling system that improved throughput, consistency, and validation speed.
Links
- Darragh on LinkedIn
- Automated Industrial Robotics (AIR)
- Veryable Is Revitalizing U.S. Manufacturing
- Sign Up on the Veryable Platform
Timestamps
- 00:00 Automation Is Here Now
- 01:21 Darragh’s Shop Floor Roots
- 03:12 From Engineer to CEO
- 04:32 Building the AIR Platform
- 06:46 New Demands Data Validation Flexibility
- 08:44 Why Automation Demand Is Surging
- 10:13 Structural Shift and Reshoring
- 12:47 Automation Augments Workers
- 15:31 Skills That Matter Most
- 18:11 Why Automation Projects Fail
- 19:26 How to Deploy Automation Right
- 20:55 Advice for First Automation Program
- 23:46 Best Processes to Automate Now
- 25:08 Full Systems Over Point Solutions
- 26:33 Pandemic Case Study in Pharma
- 28:35 AI Meets Robotics
- 30:23 How Close to Lights Out Factories
- 32:20 Automation Powers Reindustrialization
- 33:51 What’s Next for AIR
- 34:50 Where to Learn More and Wrap Up
- 36:02 Final Takeaways and Subscribe
Episode Transcript
Matt Horine: [00:00:00] Welcome to US Manufacturing Today, the podcast powered by Veryable, where we talk with the leaders, innovators, and change makers, shaping the future of American industry, along with providing regular updates on the state of manufacturing, the changing landscape policies and more.
One of the clearest trends shaping manufacturing today is the acceleration of automation, not as a future concept, but as a present day necessity. Labor constraints, rising costs, reshoring efforts and increasing global competition are all converging to force. A fundamental shift in how things get made.
At the center of all that shift is robotics and industrial automation. And today's guest is someone building directly into that transformation. Darragh de Stonndún is the CEO of Automated Industrial Robotics, a rapidly growing automation platform, bringing together engineering firms and robotics expertise across the US and Europe to deliver complex high performance manufacturing systems with decades of experience in automation and a background that started on the shop floor.
Darragh has a unique perspective on how [00:01:00] manufacturers can scale productivity. Compete globally and actually execute automation successfully. Today we're gonna talk about what's really driving automation demand, how manufacturers should be thinking about robotics, investments, and why automation is becoming foundational to Reindustrialization.
Darragh de Stonndún: Morning, Matt. Thanks for having me.
Matt Horine: Absolutely. We're excited to have you on and we'll jump right into it. Would love to know more about your background. I think you've got a really unique one from the shop floor to your position now. Can you walk us through that and how you got started in manufacturing?
Darragh de Stonndún: I'll have to go back 30 years and try to remember all that. But yeah, manufacturing has been something I've done ever since I left school. I started as a mechanical fitter turner at Guinness's in Dublin, in Ireland. If you can't tell from the accent, that's where I'm from. Just to avoid confusion, I started there as an apprentice really learning the, the details of manufacturing a small gear, a shaft, like how important those those details are, if that single thing is incorrect or wrong.[00:02:00]
The whole manufacturing process breaks down over time. Maybe not immediately, but over time I learned there that details are not just details, like they're, everything. Details really matter, no matter how small or insignificant it should feel, right? You're part of a broader project and contributing that to that, to the best of your ability and being attentive to details and quality really, really matters.
And from my apprenticeship, I moved on then to study mechanical engineering, which broadened that horizon, right? It went from contributing a part. To a design to actually designing it, uh, and having that understanding of the single part tolerances, single part detail and quality really helped shape the designing of systems, which then moved me into, really into industrial automation back in the mid nineties that, that, that was starting to gain traction, high speed automation, fuel, Sheila Packard in ink check cartridges and things like that were starting to come to the forefront in mass production and automation.
Highly engineered. Automated systems is what attracted me and [00:03:00] really I stayed in that industry since then.
Matt Horine: Yeah. I think you hit on something really important there. Leading and working in this industry, it's important that operators are building for operators, right? And learning that from the ground up is significant.
So what led you into your leadership roles and ultimately becoming the CEO of your current company? And I know your journey was long, but what's, what led you to automated industrial robotics?
Darragh de Stonndún: It was never a straight line. I don't think anyone in this industry has had a straight line into positions like that.
I learned a lot about the automation working and building automation systems for some of the world's largest companies, dealing with projects, dealing with customers, moving into sales roles, application roles, project management roles. I spent a lot of time in each of those roles, which ultimately had me then pivoting from being an individual contributor.
Leading teams, leading approaches, strategies. I spent a lot of time in Europe leading the broader strategy on commercial engagement with wallet share expansion [00:04:00] within key accounts of that company, and ultimately took me then to figuring out there there's a better way to serve customers. Stand from a single division of a company's perspective and really treat the customer and and offer the customer every engineer's ability within the company than just being limited to a single facility.
And with that vision of wallet expansion, partnerships with our customers. Drove us to start automated industrial robotics and to build on it from there.
Matt Horine: Yeah, that journey brought together a lot of pieces. And let's get into a little bit more about what it actually takes to build an automation platform, because I think that's the real question that people are looking into and as they talk about this and hear buzzwords, it's about what is the platform, right?
And automated Industrial robotics is built as a platform bringing together multiple automation companies, if I'm not mistaken. And what's the vision behind that model?
Darragh de Stonndún: The vision is simple. The execution is anything but simple. The automation industry [00:05:00] is, yeah, it's far from simple on the execution and the auto automation industry.
It's full of brilliant specialized companies, businesses that are world class at doing ing. A couple of things really. Well, if you look at our case, we have, we have companies within air with subject matter expertise and pharma, pharmaceutical filling lines, semiconductor automation, inspection, high speed medical device assembly, consumer goods.
And those companies, they were all islands of individuals doing a great job with their customer base. They can't scale across with their, they can't scale with their customers. Across geographics, across production lines, full scale lifecycle programs to smaller businesses struggle to make that step change.
But at air, in creating air, we brought together these businesses with decades of experience, some of the teams who've been solving like the world's hardest problems. I think Matt, we spoke earlier on. When we got to know each other about probably everything that you [00:06:00] touch, one or two of those things has been influenced or came off one of our pieces of production.
So since the late 1970s, the team at Air Hub been solving really challenging manufacturing problems and ultimately enabling OEMs to bring their products to market. So what we did at Air is we've given them a platform and infrastructure to operate as a company. Shared delivery standards, shared certificates, shared global capacity engineering, and the customer gets the depth of a specialist, but the reach of a global partner with air.
And that's the combination that didn't exist before we, we found air.
Matt Horine: It sounds like the space is, it's historically somewhat fragmented based on our earlier conversations and your scale is, is the ability to serve these different types of manufacturers. But more interestingly, what capabilities are manufacturers demanding today that didn't even exist five to 10 years ago?
Darragh de Stonndún: There's three things come to mind on that, that have dramatically changed data. Data today is [00:07:00] everything, manufacturing systems. In the past, you were reliant on people knowing the system really well. There's an old saying in machines, maybe similar to the older cars, you have to let it warm up before you drive it.
I remember back in the Hewlett Packard Days automation, you had to let it warm up. The oil would get right, tolerances to start to settle. That is no longer the case. Data is everything. So we're seeing a dramatic shift in data is informing us on how to run and get the most out of our machines. That wasn't the case before.
That's very, that. That's very different. Now. The second thing that's very different is validation. Ready automation. When we think about pharmaceutical or highly regulated industries, especially pharma, medical devices. Reg, the regulatory bar has moved for automation companies. It's shifted from building the A piece of automation and make sure it's right to making sure that it's validation ready.
Customers need system that are GMP Ready, 21 CFO part 11 compliant electrical batch records, audit trails. Those things are being asked from day one, [00:08:00] and it has shifted from bolting it on at the end. To now being part of it. And the third thing that comes to mind is flexibility. There's a shift in automation, there's a term going around, lot size one, manufacturing.
We as consumers, we're very fixed on i customization of things and, and automation has gone from hard to, if we go back to the in chart, in ink check cartridge, but those things were, they better be all the same, otherwise they're not gonna fit your in, in, in your printer. And that was easier to tool for.
Right? Tight tolerances, set designs. And the automation now has moved in with robotics and vision and servo motors versus traditional can driven systems. So flexibility is the third thing that we see a shift in the market now that customers are looking for.
Matt Horine: Yeah, those are all kind of converging themes, and I think turning to why automation is accelerating now, it's a blend of the technology, the consumer demand, all those types of things that come into play.
What is really driving it right now, and how much of this is labor driven [00:09:00] versus cost driven versus policy driven?
Darragh de Stonndún: I, I don't think there's one thing that's driving that. I think all those pressures have arrived at the same time. You have labor availability and cost, like they're the most visible that manufacturers struggle with.
They struggle with staffing, production lines, right? How do you face wage inflation? How do you tackle that and the changes in economics. From manual assembly as assembly systems is really driving that need and that that's part of it. The supply chain reliance, the companies got ver got burned during single sort offshore dependent production during COVID, and they're now investing in domestic capacities to break that dependencies.
And then you look at policy, policy on borders between US and Europe. That's gen, that's generating then a a second tailwind on investments and automation for reshoring. So I think it's all those things combined under meeting here at the same time that's driving that demand. But I would go back to. [00:10:00] The biggest drive for manufacturing systems.
The demand in the market is there, but it's definitely labor shortage, which is people, customers are struggling to find people to come in and run the lines.
Matt Horine: That's something that we hear a lot about, but also a recurring theme on our show is this what we can perceive to be a structural shift or long-term structural shift to this type of automation.
Reshoring and tying up those vulnerabilities that you highlighted that became very apparent during the pandemic years and beyond that, it led to questions of manufacturing as sovereignty. Do you think this is a temporary cycle or are we in a long-term structural shift?
Darragh de Stonndún: Structural, I think it's definitely structural.
The demographic. They're not gonna reverse the labor supply problem in manufacturing. It's not a blip. It's a multi-decade trend that we've seen labor shortages, and as volumes start to increase, we just don't have the people to staff these lines. [00:11:00] The geographical pressure that our customers are under, the geographical supply chain pressures like that isn't going away.
The the same mistakes that we saw through the pandemic, or the same issues that arise during the pandemic, customers don't want to see that happen again. And so there's no real going back on that. And now you start to see the quality, consistency, the operating cost. It's hard to revert from that. When you have automated systems that are running well, it's really hard to reverse that.
And you set you, you set the bar new for the next system. It needs to be more flexible, more reliant, more consistent, and then we can't forget about the products that are being designed for automation to assemble them, not the human hand. And the dexterity that the automation gives you in quality control outputs, like that's just not a hype cycle.
I think that that's a permanent reset in how manufacturers think about their product design and how they think about the manufacturing as, when we think about the, about the Americas, [00:12:00] like we're, when you're trying to compete with a lower cost country, with manual labor. How do these auto, how do these manufacturing companies, how do they gain a competitive edge?
Some of the greatest manufacturers here in America, they're not the cheapest, but they have consistency. They have quality, they have true put. They have the ability to innovate the product. Because they're doing that in partnership with the automation tighter tolerances, which makes ultimately a better product.
And I do believe that you do see this reshoring, the sprint in manufacturing being a competitive advantage for manufacturers right now, and the best manufacturers in the world, they're not the cheapest, but they're the most consistent. They've got the most flexibility and the most capital. Efficient automation makes those things possible.
Matt Horine: You hit on something really important there because the automation and labor pairing the, the comparison between the two, it's also framed as a replacement versus reinvention or augmentation piece. Right? And so [00:13:00] there's still this perception that we've had a lot of guests on this show. It seems to persist in the market, but I don't think it, it's what's reality on the ground.
There's a perception that automation replaces workers. What are you seeing in reality and what are the best. Use cases around those.
Darragh de Stonndún: I, the perception is totally understandable. It's totally understandable, but I, I think it's largely wrong in practice. What I see on the shop floor are systems and manufacturing running at 60% efficiencies, right?
Certainly far from world class because they couldn't staff them, struggle with part quality. And when you start to look at, when you start to bring in the automation, you start to increase those efficiencies. You're not replacing people, you're enabling those people to output more, drive, more consistent quality, and certainly not replacing people.
And what I do see is the jobs that have disappeared, if you follow the media, they're the ones that nobody wanted to keep. They're repetitive, they're physically demanding the high errors in in, in the [00:14:00] repetitive repetitiveness of it. And they're the hardest to recruit for. They're the jobs that, where automation comes in, and they're the jobs that that, that the manufacturing companies can't staff for because people don't want to do those jobs.
And when we think about our, the products that we manufacture, you think about a medical device you have, you have zero tolerance for errors. And, and how do you get to zero tolerance for errors? You start to put in very disciplined automation that can feel the process, they can feel and sense if something's wrong and identify a reject in that.
And then when you think about the automation systems today, they're not AI self thinking systems. They require. Roles from people that require judgment, adaptability, technical skills, the narrative or the perception of mass displacement doesn't match the operational reality. In the facilities that we work in, people are being enabled and people are needed to make the best judgment with these pieces of automation.
And [00:15:00] we as a company, design around people, it's not about designing automation to replace people, it's about designing automation to enable people and enable greatness. That that's the approach we look at. And many companies too.
Matt Horine: That's a really great perspective and ties into a lot of what. You know, we hope the reality would be right.
And it's, it's a conversation that comes up with artificial intelligence too. Is it gonna be this great replacement? It's not. It's something that we've seen augment workers in ways that were not conceivable even a couple of years ago. Taking this from a forward looking approach, what roles are becoming more valuable as automation increases?
Darragh de Stonndún: Automation. So the roles, automation technicians, systems operators, people that can diagnose PLCs, interpret vision system data, troubleshoot or robotic. These people are worth, they weight in gold and there isn't enough of them. There isn't enough of them. Um, and that started, if you think about Europe and apprenticeships, and 20, 30 years ago, that was a [00:16:00] great avenue to go down.
You finish high school, you go into an apprenticeship and you look in Europe, in some of those manufacturing mechatronics technicians, that skill set in America is missing. It's missing, it wasn't cultivated. And there's a huge demand for those skill sets today, process engineers who understand the product and the automation, and it's the harmonization of the two.
It's baking a cake. If you don't have the right ingredients, it doesn't matter how good you are, it's not gonna taste very good. And having process engineers that really understand the componentry, which in that analogy is the ingredients now tied together with the automation and you harmonize and optimize those things together.
Then you get brilliant systems, quality roles. You think about quality and automation, the data that's been driven, we need people to interpret that data and act upon it. The machine does not act upon it itself. We need to interpret that data digest, that DA data and the shop floors are getting smarter and, and it's the people that are doing that and [00:17:00] they're elevating themselves into that.
Matt Horine: You hit something really important there. I think. I remember touring the Peterbilt plant a number of years ago, and they'd gone through several rounds of automation. There was always this persistent fear that automation was somehow gonna displace the workforce, and they made a pretty bold statement.
Even on a tour for people who are just interested in peterbilts and trucks, it hadn't displaced one worker, it had upskilled or moved workers into different types of roles that helped them act on that data. That took out some of the repetitive process, and we see this a lot of the time at Variable.
There is this idea that fragmenting that kind of work around real operational need versus just a persistent, steady state. There are real results to that there through addressing your demand, but also if you're tying that in with automation, there's the ability to get tighter tolerance tolerances and get more throughput.
So it's a really nice paired system and good to see it playing out in reality, because you've implemented these at a number of different businesses, it's interesting to always find out what [00:18:00] actually works on the shop floor and where it meets reality. Right? People have an idea. A lot of times artificial intelligence is the easiest one.
They think it can do X, Y, Z, and you have to build and build the inputs to it. Automation, very similar. Where do automation projects typically fail? Where's a fail point? Or is it an expectations thing? Is it the implementation of it or something that your company has addressed, which is bringing the full package?
Would be curious to get your take on that.
Darragh de Stonndún: That's a big question when I stand back and look at it. Scope and integration are the two things. When I look at nearly every failure or I think about it, it always traces back to one of those, one of those two things. Either the scope wasn't defined tightly enough at the front end, so the system we built didn't match the problem that we were actually trying to solve for, or the integration into the broader facility, right?
The upstream, the downstream processes, the ERP, the MES, the facilities infrastructure, they were either underestimated or just addressed too late, and. Automation projects, they don't fail because the robots or [00:19:00] the server motors or the PLC, stop working, they fail because the system wasn't designed for the real environment it was going into.
And time again. You really, when you analyze these things. In order to fix them, right? We don't have, the industry doesn't have failed automation projects all over the manufacturing infrastructure. They've all been fixed. And it goes back to those two things and really defining it well upfront is where you trace that back to.
Matt Horine: What separates a successful automation deployment from one that under delivers? Is it about setting those expectations or scope or what's the real separator and is that some type of customer alignment or what's, what are your thoughts on that?
Darragh de Stonndún: Disciplined, disciplined process from the very, very first conversation all the way through to the final signature on the project.
Closeout at Air. We have a P-D-L-C project, delivery lifecycle process. There's seven phases within that. Successful projects, they don't happen by accident. They're successful. [00:20:00] Because every stage gate that is enforced with the same rigor, the same discipline, the same attention to detail, every assumption is validated.
Before we spend money, cut steel procure products, go to our customer and ask for approval. The customer's engineering team, the quality team, the operational leader, leadership there, everything is aligned before the next phase that our project starts. So like attention to detail all the way along. Some companies rush and they rush from the concept into build without really thinking through, working through the design, the development, the rigor that goes in, that goes into each of those decisions.
No matter how small they are, we put the same amount of detail into it. And when we get to the commissioning of these machines, when you've paid attention to the details, the problems become less and less.
Matt Horine: Certainly a complex problem to solve, but one with that type of discipline and rigor can be, this is the [00:21:00] part of the show where I kind of tax you a little bit and ask for some free advice for our listeners, because automation is top of mind for most manufacturers in some way.
What advice would you give manufacturers starting their first major automation initiative?
Darragh de Stonndún: Three things come to mind. Three things come to mind on it. The first one is starting with the problem and not with technology. We find some people come and say, oh, I love this technology. Let's start there. Really drive and focus yourself on what's the problem, right?
Don't start by asking, how do I use robots? Start by asking, what's actually limiting my throughput, my quality? What's driving my cost? Start there. The technology choice flows from that. The technology, once you understand what you're trying to solve for, there is so many cool. Technologies in our industry, we're not gonna struggle to find a technology to solve a problem.
Understanding what you're trying to solve for would be the first piece of advice that I would give people on that. [00:22:00] The second is, I would not underinvest and underestimate the front end of trying to design that system, come up with the right solution for the problem, the time spent in on concept definition.
Feasibility studies, proof of principle studies scope alignment. Before a single line of code or a single drawing is pulled together, a piece of steel is cut. That time pays for itself 10 times over. A dollar spent at the beginning is saving you $10 LA $10,000 late later on in the system. Time money invested upfront, pays dividends in in the long run.
And number three, which is closest to my heart, is pick a partner. Pick an automation partner that you trust with a program that has failed. How the partnership shows up in failure is indicative of how the partnership truly is. So when I look at customers, I explain to them and talk to them about it's, it, everything's great.
In the beginning it looks, my partner Brian [00:23:00] always says, it looks great in Excel until reality hits. And you really need to sit down and study. Like how did the, how does the partnership work? Under pressure, how does the project, how does the partnership work when something goes wrong? It because things do go wrong.
And how does that partnership, and I think that's the third thing, is pick a partner with the lens of how did they show up when it goes wrong, how did they react? What resources have they, are they self-sufficient or really think that's an important element in that decision process.
Matt Horine: Really important points because I think a lot of people do think about this a lot and knowing where to start is sometimes you gotta take a step back and look at the bigger picture.
As you said, if you're doing it from an Excel sheet, it's probably, it probably looks great.
Darragh de Stonndún: Oh, totally.
Matt Horine: It's my Excel sheet. Maybe it doesn't look great, but getting it out into the real world application is important. With that, with real world applications and how it impacts the businesses and the partners that you do work with, what types of manufacturing processes are most ready for automation today?
Darragh de Stonndún: Definitely high mixed. High volume [00:24:00] assembly, vision, guided handling. The tech. Those technologies have matured where you can automate processes that would've required way too much programming and engineering to do in the past. That type high mix is absolutely trying to be automated today. Inspection and quality control.
The systems we have on vision system, AI plays a huge role in vision Today. We're able to inspect everything, so you might manufacture or assemble a defect, but you will catch it. We have the abilities today, no product should be going out to the market. That is rejected, given the inspection and quality control systems that the manufacturing, manufacturing systems have.
Regulated systems that are in a highly regulated environment. The automation is now, it has processes, it has ways of complying with ISO 13 4 85, which are OEM Medical Device Customers work under pharmaceutical filling sterilization, label tracking, track [00:25:00] and trace. These are all item, these are all processes in manufacturing that are perfect for high volume automation.
Matt Horine: Are you seeing more demand for full system automation versus point solutions?
Darragh de Stonndún: The trend is definitely, the trend is definitely towards full automation solutions, point solutions, single islands of automation. They're still part of conversations that we have. Some, sometimes customers, they need to solve a specific.
Problem, a bottleneck and they need to solve that fast. And then you do end up with a point solution to do that. But the bottlenecks on that, or the constraint on that becomes apparent really quickly and the question becomes now, oh, how do I integrate this point solution in into the overall full system?
I think customers have learned. That isolated automation cells without coherent systems architecture create their own inefficiencies and problems. So the manufacturers who are investing most aggressively right now, they're thinking about lines and factories, [00:26:00] not individual assembly cells. That's what we're seeing.
Matt Horine: Good to hear, because it's capturing the full picture, right? It's always determining that scope. As you mentioned earlier, you've got a lot of experiences, a lot of customers, and without really having to name any 'cause, I'm sure there, uh, plenty of them are confidential. Do you have a, a favorite story or example of where automation significantly improved throughput or quality or lead times, which is something that's highly concerning?
We talked about the. 2020 pandemic era that just uprooted supply chain, lead time, lead time's. Certainly something front of mind. But do you have a favorite story from all those builds?
Darragh de Stonndún: Yeah. Which one? I guess my most. Everything we do has dramatic impact in a lot of different ways. Maybe to pull on the pandemic example that you brought up.
1 1, 1 definitely comes to mind from there and it, it stuck with me on air now for quite some time. We referenced back to it. 'cause brilliance came from it. During that pressure, during the engineering, and what we were trying to solve was not just automation, right? It had a bigger impact than just a piece of automation in [00:27:00] the environment that we were all living through at the time.
And it was a pharmaceutical client that was running clinical trials and clinical trials, high mix, small batches, regulated across multiple drug formats. It was a very manual process, heavily dependent on skilled labor, significant variation in the output. So we were asked like, how can we help automate this and bring this to market faster?
And we designed a full turnkey automated filling and assembly GMP compliant 21 CCF, CFR 11, throughout with a quality dashboard for batch releases. The throughput improvement was very meaningful. The quality impact was real. Batch to batch. Consistency went to a level. The manual process just wasn't able to, it wasn't able to sustain, and the Val validation life cycle became a fraction of what it was in the manual process, which enabled that pharmaceutical client to bring the clinical trials faster to [00:28:00] market, and ultimately get drugs and prescriptions out to us a lot faster.
They got to the answer quicker. And, and that really stuck with us as a, it was a challenge in how we use the automation and that was the project that we're proud of all of them. That one sticks out though as we think about the pandemic, about the pandemic times
Matt Horine: for sure. And it also highlights the necessity of automation in critical industries.
But how that critical can be defined by a lot of different qualifiers, right? It's, if it's your supplier, it's critical, but for the customer and for the general population, that is certainly a critical industry. Turning to a topic that we cover on the show often, AI and how that integrates with with automation.
How do you see AI intersecting with robotics and automation going forward? You mentioned earlier in the show data was the biggest, latest thing that maybe not wasn't there just a couple years ago, but how do you see that intersection happening today?
Darragh de Stonndún: AI is going to unlock the next tier of automation.
[00:29:00] The processes that have been historically too variable, too judgment dependent, too unstructured to automate reliably. Right now, AI's immediate impact is envisioned on inspection, identifying defects, guiding robots through variable part presentation, adapting to product changes without reprogramming there.
There are areas where AI are having immediate impact. If you take a massive step backwards, I back. I think the bigger shift is in the control layer. The control layer of the automation. AI driven process optimization, predictive maintenance that prevent, prevents downtime rather than just predicting it.
Adaptive systems that self adjust based on real time production data, those things are becoming like real capabilities, not interior, ethical ones. The factory of the future. Is it, it's about automation, but it's about systems that learn. And I, I think that's the impact that AI is gonna have on in, in the automation space.[00:30:00]
And like I said, the broader one is like that control layer between the OEMs manufacturing system and our automation system.
Matt Horine: Yeah, that's a really important point is the ability to make kind of those decisions off of the inputs. We talked about that earlier, is that just automation does the job at making those kinds of insightful decisions or fixing the problem is a really interesting direction that it's all heading.
And do you think we're closer to fully autonomous manufacturing than people realize? In
Darragh de Stonndún: structured applications, yes, in very specific use cases. Their facilities are running today with extraordinary levels of autonomy, very dependent on the process. I think the honest answer is that fully autonomous is to a spectrum that there's 20% that will never get to.
Right now it's awfully hard. Right? The last, that last 10%. It's so hard to get there. It needs so much. Human intervention. Analyzing the data, understanding the [00:31:00] process, processes that require physical dexterity in unstructured environments. Judgment about quality, the situation that pops up, right? How do we deal with that?
The adoption of conditions that weren't anticipated in the design. They remain really difficult to go. Lights out fully autonomous. I say 20%, like put a number on it, it's 5% matters. It's, they're the things that I think we have a lot to learn from and how we educate AI to understand those things, to really adjust with it.
But we're closer than most manufacturers I think would realize in that. And it's going to be really exciting to see how that evolves and how that, once we get established with that data layer, I think that's gonna start to really inform automation system designs. How the systems able to interact with that, listen to that, talk to that.
The robot will do. In the most cases, what you tell it to do and telling it and programming it, that infrastructure's there. [00:32:00] These systems, listen, they need to be programmed. They need to be told what to do and how to act. So I think once we start to see this data there. We'll be able to understand and drive our design decisions from that and hopefully close that 20% gap.
That is really hard to to predict.
Matt Horine: Very hard to predict, but that's a great prediction. You can see that the trend lines going that way. I think one of the big things that we talk about on US manufacturing today is reindustrialization and global competition. Your company is a global company. We talk a lot about it on this show re industrializing the United States.
How critical is automation to making that a reality?
Darragh de Stonndún: I don't think it's optional. It's part of the solution. There's so many elements to it. We play that role. I do not believe it's optional. Without automation, a strategy for building new manufacturing facilities. Right. When you think about the people, the cost, the, the competitiveness of products out there, automation, I do believe it's the only way to bring that back to the US and bring it back at a scale.
That [00:33:00] economically matters and it creates, like we spoke about jobs being displaced. The manufacturing systems, they create durable jobs. They build real industrial capacity, and it's to build around automation from building around automation, then from the ground up. The companies that are doing this right are not trying to recreate what we, what they had offshore.
They're building facilities that com, that compete on capacity, consistency, speed. It's not about it. It's not all just about the labor cost. Automation is what makes the most viable commercial decision for these manufacturers. Coming back to America and automation is a huge enabler and key to that and have done will be successful,
Matt Horine: right?
Spot on. I think that's something that people think about and talk about, but what the critical path is to achieving that scale that you talked about There is so important. So exciting stuff ahead for air, which I've been, I believe is the abbreviation for the company. What's next for Air and what you're working on over the coming [00:34:00] months?
Darragh de Stonndún: Yeah, we're going to keep growing, keep building, but air, we're very focused on growing our share of wallet within our customer base. We want to be an important partner to our customers. We want to be able to exp expand, expand. Our capabilities to be more meaningful to our customer base, to take more on, to solve problems that we say no to Today.
We wanna be able to enable ourselves to say, yes, we can solve that. We found those capabilities, so we're working with our customers to understand their long-term needs. And deliver short-term, automate short-term needs that they have in the automation systems and, and really building our culture, building, building our company, honing our skill sets, and really excited to be part of the manufacturing around the globe And Air hopefully can play a very meaningful role in that.
Matt Horine: Very exciting things ahead. If our listeners were interested in automation or wanted to find out more about you or your company, where should they go?
Darragh de Stonndún: People are always welcome to reach out on LinkedIn, [00:35:00] industrial robotics.com. Always open to facilitate visits in our buildings. Reach out to subject matter experts, people that are thinking about.
I'd encourage people if you're thinking about a new product. You're trying to figure out how you can unblock a bottleneck, reach out to us. It's it curiosity leads to solutions, and we love to get involved here today. We do two simple things. We help our customers innovate their products, unlock the challenges that they have on bringing that next product iteration to market.
We help them innovate, we help unlock the manufacturing challenges and we help them scale. So if you're thinking about unlocking innovation, you're thinking about scaling your production, that's what we do. That's where we focus, that's what we build our capabilities around, and that's what we love doing it.
And by loving it, we're really good at it.
Matt Horine: Awesome. Really compelling case there. If you're interested in growing scale and improving your product, be sure to reach out. Darragh, thank you so much for joining us. We learned a ton today. Really appreciated it and excited to see what the future holds for air.
Darragh de Stonndún: Very [00:36:00] welcome, Martin. I appreciate it. It was fun.
Matt Horine: Automation is no longer optional. It's becoming the foundation of modern manufacturing competitiveness. As companies look to reshore production, increase resilience and meet growing demand, the ability to scale efficiently will define who wins and who falls behind.
Leaders like Darragh are helping build the systems that make that scale possible, not just through technology, but through real world execution on the shop floor. The future of manufacturing won't just be built by machines. It will be built by the people who know how to deploy them effectively. Thank you for joining us today.
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