EECO Asks Why Podcast
EECO Asks Why Podcast
AI Agents: Manufacturing's Secret Weapon
Artificial intelligence is revolutionizing manufacturing, but not in the way most people think. While traditional AI responds to prompts, AI agents represent something far more powerful – autonomous programs that learn, adapt, and make decisions independently in real-time. These intelligent systems are transforming how factories operate in an era defined by supply chain volatility, labor shortages, and rapidly changing market demands.
The predictive capabilities of AI agents offer a fundamental shift from reactive to anticipatory operations. By simultaneously analyzing data from sensors, drives, PLCs, ERP systems, and quality control mechanisms, these agents create a comprehensive view of factory operations, uncovering patterns that signal potential issues days or weeks before they occur. Manufacturers implementing these systems report remarkable results – up to 78% reduction in unplanned downtime, 45% decrease in maintenance costs, and equipment lifespans extended by more than three years.
When paired with digital twin technology, AI agents can simulate thousands of production scenarios in hours rather than months, optimizing configurations for maximum efficiency. Quality control systems achieve near-perfect defect detection rates while supply chains become more resilient through AI-powered forecasting and dynamic adjustment. The factory of the future isn't just automated – it's autonomous, continuously learning and optimizing itself.
At EECO, we're committed to walking beside you through this technological transformation. Our team can help you explore how AI agents might integrate with your existing systems, providing the expertise and partnership mindset needed to turn these possibilities into practical realities. The future of manufacturing belongs to those who anticipate tomorrow's opportunities rather than react to yesterday's challenges.
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Host: Chris Grainger
Welcome to Eco Ask why, a podcast that dives into industrial manufacturing topics and spotlights the heroes that keep America running. I'm your host, chris Granger, and on this podcast, we do not cover the latest features and benefits on products that come to market. Instead, we focus on advice and insight from the top minds of industry, because people and ideas will be how America remains number one in manufacturing in the world. Welcome to EECO Asks why. I'm your host, chris Granger, and I'm looking forward to spending some time with you today. We've been talking a lot lately about digital twins and these evolving technologies that are happening all throughout industrial manufacturing. Twins and these evolving technologies that are happening all throughout industrial manufacturing. And for today, I'm going to pull on something that's another thread I think you're going to have a lot of fun with, and that's the predictive power of AI, particularly these AI agents in manufacturing operations directly. Okay, so this is going to be a lot of fun. Hopefully you're going to enjoy this, because we have to recognize that the manufacturing sector is in really a time of transformation right now. I mean, there's lots of pressures to optimize, there's lots of pressures to reduce costs and we got to get as much productivity out the door right, because the supply chain out there is volatile, we have labor shortages and market demands are changing at just incredible rates. And we think about traditional automation that really follows a lot of static, pre-programmed rules right, and sometimes the need to adapt is moving so very quick and it's very complex. So for manufacturers out there that are trying to remain competitive, you have to think outside of just the standard box of reactive processes and start thinking about intelligent systems that can, in real time, adapt, learn and make these decisions for you as you move forward. So at ECO, we recognize that there's power in the predictability, particularly with AI that's out there, these artificial intelligence agents that are out there, and they're game changers. Ok, and lots of solutions, lots of things represent far more than just like little incremental improvements. We're talking about a fundamental shift here. It could be really, really a big time in industrial manufacturing, manufacturing where you can think about optimizing, you can think about intelligent manufacturing ecosystems. And at EECO, we want to walk beside you. We want to walk beside you with the manufacturers that we represent so that it may help you evaluate, pivot, start scaling this technology and help uncover where AI agents may have the greatest impact in your particular facility.
Speaker 1:Ok, so we need to think about this in some realm outside of traditional AI, because AI agents are these programs designed to perform tasks and make decisions on their own, so it's not like traditional AI or even generative AI. So it's not like traditional AI or even generative AI. That AI that you think of, like ChatGVT, responds on what A prompt that you give it. Right, you give it a prompt, it gives you an output. Okay, and these systems don't really like if a prompt given to AI system doesn't analyze data. They're acting on insights from what you give it. Okay, and the cool part about these AI agents that we're talking about today is they have the ability to learn, to adapt and collaborate with not just us, but also other agent sets and really make a big impact in your manufacturing.
Speaker 1:Okay, so we're talking about the next step of AI evolution, and this is where you have independent action, continuous improvement and probably problem solving in a highly dynamic environment. Ok, so this is really cool. This is really fun stuff, and I know there's lots of questions out there on this stuff and we have questions too, but we're here to walk with you, to help demystify this new generation of AI that's out there, and we have lots of manufacturers we work with that are leaning into AI and the results are clear out there for sure. So, again, as you're listening to this, if you think, man, I think I'd like to have a conversation about that. Please reach out to us. We're here to serve, we're here to serve, we're here to help and, with our network and different resources that we have, we can have a great conversation with you and maybe move the ball down the field a little bit.
Speaker 1:Okay, so you have to think about how you're going to harness data to predict and optimize performance, because the core strength of an AI agent lies in the ability to process and analyze massive amounts of data. Okay, so I mean, just think about that. So much data out there and the thing about these agents they're doing it simultaneously. Okay, so think about traditional manufacturing facilities. These inputs can come from many different places. I think about when I go back when I used to call on plants on a regular basis and just walk through. You had sensors, you have drives, you have, obviously, plcs. You have all these different devices, the IoT devices, that are just bringing in data. Then you have your ERP system, then you have your scheduling system, you have your quality control system and you have your environmental system. All these things together right. All these things together right.
Speaker 1:So when you start integrating this in this type of model, the data starts providing a holistic, real view, time of okay, real-time view, rather of the factory, and this using advanced machining learning algorithms. These agents can really uncover patterns and corrections that may be buried in the noise. And so think about it Like you could connect a conveyor throughput machine, vibration signatures and like ambient, just standard old temperature gauges, right. And an agent could detect trends that signal a performance dip, and that could be hours or days in advance. So the predictability here is really interesting when you start thinking about it, because it's shifting the way that you could plan. Instead of focusing just strictly on yesterday's numbers, you could start anticipating tomorrow's challenges, and that's pretty useful right there. And think about how you measure traditional OEE overall equipment effectiveness right. But if you start modeling how interconnected factors affect the throughput man, you could really have a big impact on that before problems happen. And there's research out there, there's studies out there and there's companies that have started adopting this level analysis and some have reporting up to like a 31% increase in OEE, or a 67% faster response time. That's crazy when you start thinking about it, right? So we're starting to see a few use cases where this is proving itself out. And it's not just, you know, just magic in a box, right? No, these things are happening and they're aligning with existing automation infrastructure and the priorities that the plant has. So it's not like you have to make this massive, massive investment. Sometimes you have the technology there, you have the data there. It's just bringing in this agent to walk alongside you, okay.
Speaker 1:Now, speaking specifically about predictive maintenance, this is a clear area that AI agents can help. Okay, and think about your traditional strategy with maintenance and there's different ones and some stuff you just have because that's just the way it is right. You're going to have reactive maintenance. That's basically you fix it when it breaks or you have that scheduled maintenance, right? So you're going to do that maintenance on a defined period of time, regardless of condition. We're going to change this bearing, we're going to do this grease schedule, whatever it may be, and sometimes you may be doing things that aren't quite necessary, but both approaches have a cost. They do, they have a cost. And if you're reactive on everything, if it's a catastrophic failure of a piece of equipment that could take your entire line down right.
Speaker 1:So these AI agents change the game because really they're leaning into the whole predictive maintenance element a lot harder and they're continually analyzing this IoT sensor data. So think about the IoT sensor data that's out there. We represent a lot of manufacturers and we have these alignments. So you have sensors like vibration sensors, you got the temperature sensors, you have acoustic sensors and if you couple these with the right AI agent, what they can do is they can give you early indicators of wear and tear. I mean, we're talking about weeks or even months before something occurs.
Speaker 1:But prediction is only a component of where AI can help here, because the way that they work, they may be able to help you automatically schedule these maintenance windows, even order replacement parts or adjust production schedules to minimize the impact. So it really starts to take some of the guesswork out of what adjustments need to be made. And again, manufacturers out there some of them are leaning into this. Some of them have seen up to a 78% reduction in unplanned downtime. That's crazy right. Or a 45% decrease in maintenance costs crazy right, or a 45% decrease in maintenance costs. And there are even reports out there that there are manufacturers that are seeing 3.2 years extension of equipment lifespan. Now, when you start thinking about those type of numbers and those type of impacts, you have to start leaning in and considering okay, what does this look like for me?
Speaker 1:And at EECO again, we've been big proponents of predictive maintenance. We recognize this is a big area for manufacturing. It's just kind of cool right now to get to explore how can we bring AI into this right and if you can start really getting a rapid return on investment while you build this, that gets exciting there. That gets really exciting. So another area worth considering is simulation. So, beyond prediction, which is really cool, ai agents can really have a lot of advantage because they can experiment Right.
Speaker 1:If you, if you kind of pair an AI agent with what we've been talking about for our last two episodes of Eco. That's why the digital twins you know, you can really play a lot of games and test thousands of what-if scenarios, right. So we're not just talking about visualization, we're talking about simulation, where you can maybe even adjust the machine speed or an output, where you shift the material flows or alter production sequences to try to figure out what is the best configuration right, and so this could take, you know, just trial and error, with months and weeks to model this stuff out. Where this could be done with AI agent, potentially within hours you could find this, and there are studies out there that pharmaceutical companies have used this digital twin coupling to redesign complex production lines and some of them have seen a 28% increase in throughput. Think about that and you know all the type of regulatory compliance that goes with the pharmaceutical industry. So they're keeping that while increasing throughput. So I mean, that's kind of crazy to think about. So when you have risk, when you have the need for capacity moving faster and faster and faster, these AI agents can give you opportunities to innovate with confidence. And again, we're here to help you, we're here to support you, we're here to help you explore these tools and maybe think about simulations, okay.
Speaker 1:And when you start thinking about the power of AI, a lot of it comes down to data analysis, right, and it's not just analyzing data for analyzing data's sake, but if we're trying to enhance our quality and really improve our supply chain management, so start thinking about the quality controls, like AI agents. If you start integrating it maybe with, like a computer vision system, okay, and you're trying to really detect defects that are happening. Man, these AI agents can do it at an extremely high accuracy rate. I mean we're talking about there's reports out there like 99.97% accuracy rate. That's crazy, I mean it's incredible. We're talking about spotting microscopic cracks or little color variations right, it can go even beyond detection. They can shift quality assurance toward prevention by predicting when the processes are really starting to get out of spec, and then you can start correcting it. Right, and then, from a supply chain standpoint, you can analyze supplier performance, inventory levels, trends from your customers and just start thinking about the overall networks that you're working with. Then you may be able to start accurately demanding forecasts and dynamically adjusting your production plans based off that.
Speaker 1:So I mean, disruptions happen, right. I mean you maybe have a delayed shipment out there, right? Well, if the AI agent can pull that data in, it may be able to automatically identify alternative suppliers or reroute logistics or rebalance that inventories, so you can cut disruption down. That's where the big thing is. We're trying to cut that disruption down to make better decisions. And I'm telling you, I think this is something that more and more manufacturers are going to be leaning into, because the markets are volatile, the markets are competitive, so you have to be thinking what can you do to gain a competitive edge, and bringing in tools and resources like this could be that.
Speaker 1:And I mean we have to consider from industrial manufacturing, the future is predictive and autonomous, right, so the integration of these agents is not just an enhancement of what you already have. Okay, this is kind of like a fundamental re-imaging right, or kind of rethinking of how manufacturing could be, because it's these types of intelligent systems that create factories that are not only automated but are increasingly autonomous. Ok, so they're learning it all the time, they're adapting dynamically and they're optimizing proactively. I mean, it's like it's like future scifi movies, except it's here now. And so it shifts from forecasting to the OEE models and enabling predictive maintenance to really optimizing processes through using digital twins and safeguarding quality. And I'm telling you, the opportunities are just endless, right, but there's measurable impact. We're talking about greater uptime, lower costs, more product that you're getting out the door and that resilience right, the equipment is being more resilient.
Speaker 1:So, again, we have several cases and resources that we pull to kind of help us understand this at ECO and at the end of the day, we're here to walk beside you. We recognize this is a new frontier. We recognize this could be viewed as scary, it could be viewed as unknown, but we have lots of experience and we have lots of resources within our ecosystem to support you, from electrical systems to automation modernization, and we can bring some technical expertise. More importantly than that, a partnership mindset. So you're not going into this alone, right? You're going to have somebody within an electrical equipment company who's willing to walk alongside you, because our goal is just not to introduce you to new technology by. Good luck, wish you the best.
Speaker 1:No, we want to help deliver you long-term value. We want to help you unlock the future potential If these AI agents work for you and your manufacturer facility and your model, and we want to help you explore that. And at the same time, we know we can't just live in the clouds. We need to stay grounded in operational realities and that's what we're here to do, because we recognize the future. Manufacturing really is not going to be defined by those who react to yesterday's challenges, but the ones who recognize and anticipate tomorrow's opportunities. Have predictive power of these AI agents and you align it with partnerships like electrical equipment company, you can take a big step forward in building truly intelligent, resilient and future ready operations, and that is worth getting excited about. So we're here for you.
Speaker 1:Again, you can reach out. There's going to be links for our podcast. There's going to be links, if you're checking this out on YouTube, to connect with us. Probably one of the best ways to connect is just set up a time to come to one of our labs. We have labs throughout our service area, so come connect.
Speaker 1:We have, again, subject matter experts. That would be love, love, love. To sit down to hear what your applications are, to hear where you're at with your industrial facility, and also just to hear what your goals are. Just to do some some brainstorming, some fact finding, some goal setting, some dreaming even, and just to see, ok, based off of that, how would we approach it, what would we recommend and get you connected with the right resources out there to turn this from from a dream into reality. All right, so if you enjoyed this, if you thought there was some value, maybe sharing this with others, that would be wonderful. Obviously, if you give us a rating and review, that would be awesome. But, most importantly, come check us out, go to ecoonlinecom. Again, connect with us on the resources.
Speaker 1:We'll have links underneath the podcast for you to connect with us directly, but schedule some time. If you don't want to come into the lab, reach out to us, we'll come to you. We love coming to industrial manufacturers, to seeing the facilities, to understanding the complexities and just having a fresh set of eyes and sometimes a fresh set of eyes is a big deal, okay, so we love to connect with you again. All those links will be there. Follow us on LinkedIn as well and you know what's coming right. Just remember to keep asking why. Thank you for listening to. Eeco Asks why this show is supported ad-free by Electrical Equipment Company. Eeco is redefining the expectations of an electrical distributor by placing people and ideas before products. Please subscribe and share with your colleagues and friends. Also leave comments, feedback and any new topics that you would like to hear. To learn more or to share your insights, visit EECOASYcom. That's E-E-C-O-A-S-K-S-W-H-Ycom.