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Beyond the numbers: The next wave of industrial evolution

• Eclipse Automation • Season 1 • Episode 1

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In the debut episode of People B4 Machines, host Amanda Cupido dives into the evolution of Industry 4.0 and the emergence of Industry 5.0 with guest Jeff Winter, a globally recognized thought leader in industrial automation. Together, they explore the shift toward human-centric, sustainable, and resilient industrial models, emphasizing the importance of collaboration between people and technology. Jeff shares insights on the challenges of scaling digital transformation, the role of leadership and culture, and the critical need for clear strategies in navigating this transformative era. Tune in for actionable advice, bold questions, and a fresh perspective on the future of manufacturing.

Thanks for listening to People Before Machines, conversations on the chaos of factory automation, from Monday morning to the very near future. For more bold questions and sharp insights, visit us at People Before Machines.com. Our next episode, with Jeff Burnstein, Top floor to shop floor: Why is it taking so long to connect these floors? drops November 18th. And remember, the future isn't fully automated, it's people-powered. Now back to the show.

For more bold questions and sharp insights, visit www.peopleb4machines.com. Remember, the future isn’t fully automated—it’s people-powered.

Jeff Winter:

In addition to our workforce not being ready, I honestly think our leaders aren't ready either. We've poured billions into technology, but far less into preparing our people. You know, the workers are told, oh, artificial intelligence is going to help you, but then not show them how their roles evolve. Leaders talk about digital first strategy, but can't explain what that means for decision making or accountability or career paths.

Intro:

People before machines. Conversations on the chaos of factory automation from Monday morning to the very near future.

Amanda Cupido:

Welcome to People Before Machines. Conversations on the chaos of factory automation from Monday morning to the very near future. I'm Amanda Capito, a speaker, author, and entrepreneur with a passion for the intersection of technology and humanity. This episode, we're discussing Industry 4.0 and beyond, specifically, what it looks like to shift the focus to creating a human-centric, sustainable, and resilient model of industrialization. We'll dive into best practices, who's driving this shift, and potential pitfalls with today's guest, Jeff Winter. He is the vice president of Business Strategy for Critical Manufacturing, where he leads strategic growth initiatives and business development and has helped position the company as a global leader in MES technology. Jeff has 20 years of experience working for different industrial automation product and solution providers. He's known for his ability to communicate complex concepts to a wide range of audiences, which is why he has been recognized by more than one group as the top industry 4.0 thought leader globally, including being a top voice on LinkedIn with more than 85 million views of his content, which is why I am especially excited to have him on the podcast. Welcome, Jeff.

Jeff Winter:

Thanks for having me here. This is going to be fun.

Amanda Cupido:

It is. Let's dive right in. So we talk a lot about industry 4.0, and some are even already talking about industry 5.0. What are the key differences between the two and why does it matter right now?

Jeff Winter:

You know, when people ask me the difference between Industry 4.0 and 5.0, I always like to start with a little history lesson. So the term Industry 4.0 was actually born at Hanover Fair in Germany back in 2011. And then a couple years later, it became part of the Germany's official high-tech strategy 2020. And at the time it was all about these nine technology pillars, things like IoT, big data, robotics, simulation, all that stuff. But then the idea took hold all around the world. And when it did, it took on different meanings all around the world. So what I've learned over the years is industry 4.0 can really be seen in two different ways. Some people use it to describe or as a label for the era that we're living in right now, basically the digital transformation age of manufacturing. Yet others see it as a destination. So they think of it as this perfect end state of hyper-connected, self-optimizing factories. Now, both views are valid, and that duality is part of what's fueled conversations like these all over the years. Now, then comes along the idea of Industry 5.0. And it first showed up really around 2021 with some of the European Commission papers that came out. And what is interesting is it's not even pitched as a brand new revolution, it's described as an evolution of Industry 4.0, which is why so many people get confused. Now, what it does is it layers on three really important themes. It layers on being human-centric, sustainable, and resilient. In other words, it's all about making sure that all this tech that we built doesn't just crank out efficiency, but it also actually serves people. It protects the planet and it holds up when disruptions hit. Now, very few disagree with this concept, although a lot of people don't like the term, the label industry 5.0 to describe it, myself included, as I think it appears misleading since it's not a brand new industrial revolution, but rather an evolution. So I personally like to describe industry 4.0 more as the era that we're living in right now, with a vision of what it could be, which means all the stuff that we're talking about, in my view, is just part of Industry 4.0 or the fourth industrial revolution. And why does this matter right now? Because if you look at the past, oh, 15 years or so, the pace of change has been relentless. Cloud, artificial intelligence, IoT, advanced automation, digital twins, you name it. And it's not slowing down, it's accelerating. So having a clear strategy for how to take advantage of all these disruptive technologies collectively, together, is no longer optional. It's becoming essential. Whether you called industry 4.0 or 5.0 or something entirely different, it really doesn't matter. What matters is that you don't ignore it and you approach it with a proactive strategy to thrive in this transformative time that we're living in right now.

Amanda Cupido:

Okay, thanks for that history lesson. I think it's really important to set the stage. And it just makes me think about the role of this human-centric innovation. So whether we're referring to it as industry 5.0 or just at the second iteration of 4.0, how does it differ from what we're doing right now? That's the core question, I think, of how we want to move towards that or what would need to change.

Jeff Winter:

And this depends on how you view industry 4.0. Once again, whether you see it as a description of our era or as a destination. Now, for argument's sake here, I'm going to be answering more on the destination side, meaning we're talking about the European Commission-specific version of Industry 5.0. So now, in that framing, Industry 4.0's destination, if you want to call it, was all about automation, connectivity, and autonomy, essentially machines and systems doing as much as possible on their own. And the role of human was often minimized. And Industry 5.0 kind of changes that narrative. It flips the narrative. Human-centric innovation says, wait a second, the purpose of all this tech isn't to push people out, it's to lift them up. So instead of treating workers as obstacles to efficiency, Industry 5.0 treats them as creative partners. You know, artificial intelligence, robotics, and digital platforms become tools that enhance human judgment, intuition, and problem solving. That shift matters because humans bring what machines can't: empathy, ethics, context, and imagination. So in Industry 5.0, you see innovation aimed at collaboration. Cobots are collaborative robots, you know, designed to safely work side by side with operators. Augmented reality and virtual reality for personalized training, decision support systems that explain the why behind recommendations. So it's not about replacing human input, it's about designing technology that adapts to us. And the stakes are high with skill shortages and generational workforce shifts and rising expectations for meaningful work. Human centricity becomes a competitive advantage. And companies that get this right won't just have more efficient factories, they'll have more engaging employees, more innovative ideas, and stronger resilience when things inevitably change.

Amanda Cupido:

So you're talking about these shifts. Who is driving these shifts?

Jeff Winter:

So what's funny is I've been asked this several times. And so I found actually about a year ago an interesting study from 2023 on industry 4.0 adoption in developing countries. And it was by uh Tsungua University. And the the study surveyed, I think it was something like 215 Chinese manufacturing firms, and found out that industry 4.0 adoption isn't really about the technology itself, even though the managers generally agreed, actually an average of 4.6 on a five-point likert scale as part of the study. And what they found is that, yeah, the tech had big advantages. Everyone agreed on that, but that didn't actually push them to adopt. What actually mattered was government support, which had an average of 4.4 out of five, and competitive pressure, which was a 4.2 out of five, which together nudged the top executives to get on board. And once the leadership backed it, adoption followed. And bigger firms, the ones over 2,000 employees they found, and those with stronger technical know-how, were also much more likely to adopt. And when you look across these 14 technologies that they evaluated against, the firm split into three camps. About a quarter of them were light adopters, around 40% were moderate adopters, and roughly a third were heavy adopters. Now, in addition to this Likert scale that they used, they also provided uh beta values. And these these beta values come from structural equation modeling, which is basically, in layman's term, a type of regression analysis. So instead of just showing averages, which is what I talked about before, it looks at how much one factor actually influences another when you control for everything else. So for example, government support had a beta of 0.34, meaning that for every increase in government support, say an average from a three neutral to a four agree on that Likert scale, there was a strong positive jump in the likelihood that top management would support industry 4.0 adoption. And I found that fascinating. So overall, companies in developing economies don't actually adopt Industry 4.0 just because it looks good on paper. They adopt it when leaders feel backed by government, when they feel pressured by competitors and confident that they will have the size and the skills to make it work. And that's why over the past decade, you've actually seen a lot of countries invest billions of dollars and even set up institutes to help advance manufacturing, both either in their country or globally.

Amanda Cupido:

This is fascinating. In an ideal world, though, do you feel that's the way it should be? Like that's how the shift should be driving? Or do you feel like it should be, yeah, or where would you put the power, so to say?

Jeff Winter:

It's kind of a funny question because in an ideal world can mean a lot of things to a lot of people. So if you look at more as just kind of like the free market laissez-faire approach, it should be driven by uh mostly competitors, just a new technology comes out, and then people adopt it as they see an economic ROI for them to adopt it to win in their marketplace. But when you start to look at country-to-country comparisons, then there's this incentive to go, but we want our country to advance. And so if they're not seeing the natural inclination to do it, we want to help them. We want to help them get over that hump so that we can we can push them to that edge, because if they do, then our country will do better overall. So it's one to go, I would say I like that the governments uh around the world have set these institutes up. I mean, I'm part of CESME, which is the US government institute for smart manufacturing. It's one of well over a dozen set up by Manufacturing USA to help, you know, manufacturing competitiveness in the United States, you know, against the world. And I do believe it's working to help elevate and lift, especially the small to medium-size manufacturers, to give them a boost so that they can compete in a world where other countries are supporting their manufacturers.

Amanda Cupido:

Yeah. And it must be interesting then to follow what government leaders are, what actions they're taking around the world, because we might get a surprise country pop-up with them embracing 4.0 technologies and beyond just because their government leaders are taking that kind of a stance. So that's exciting. All right. It seems as though some manufacturers have yet to figure out how to begin with realizing the value of digital manufacturing as a whole. So I just thought it would be good if we zoomed out for a second and talk about your 10 golden rules for digital transformation. I am gonna rhyme them off quickly. It's prioritize end user experience, commit to continuous learning, uphold data security and privacy, embrace agile methodologies, break down data silos, conduct regular testing, design for future growth, regularly revise digital strategies, engage and involve leadership, and finally maintain transparent communication. Now, I zoomed through them all because as you yourself note, there are no surprises there. And the hardest part of transformation isn't knowing what to do, but it's sticking to it. So why don't you elaborate on that?

Jeff Winter:

Sure. So this was a fun post that I made. I actually made the list last year and then rewrote an article to kind of back the post. But one of the things that I like to encourage every manufacturer is you need to have a clear definition and vision of what industry 4.0 means to your company. Pick a term that works for your company and come up with that definition and that vision. Because if you don't agree as a company on what it means, what do you think the chances are of you actually succeeding in it? The moment you turn it into a collection of projects, they get evaluated as a collection of projects rather than a transformative change of your organization. So I came up with these, I call them 10 golden rules to help companies think about what they should be putting in place for their company that kind of guides all decisions across the company. So this is like the step beyond the vision. And it's more what rule book are you giving employees so that not only do you have the vision, but you're giving some guidance for how they make decisions so that you're all working together collectively as an organization across departments and achieving the result that you want. So I tried to do this to spur conversation. I doubt that any company would use my 10 exactly, but I put my 10, I put my, you know, my definition of what they each meant to try and get companies to go come up with your list. It could be five, it could be eight, it could be more, but something that helps to define how you guys are actually making decisions in the company and what you're trying to do as a result of industry 4.0 or digital transformation at your company.

Amanda Cupido:

This is great. And especially tying into how we started this conversation, everybody is using these words a little bit differently. So even providing this kind of clarity for your team so that we're all making sure that you're talking about the same thing. I think it's important. So kudos to you for prompting that for leaders.

Jeff Winter:

I actually did a workshop in June of this year where we asked everyone the formality of their industry 4.0 or digital transformation definitions in the company across the series of manufacturers and then asked them to kind of state what they thought it was. And what I found funny was the inside single companies, we had one that had like four companies in attendance. They didn't all have the same definition for what industry 4.0 meant. And this was a real workshop where we got to discuss this as a group, and yet they had theirs fairly standardized on their rankings. So it's funny to see how it works out for the companies to go, oh, we absolutely have a definition. Yes. And they go, what is it? And then all four people have slightly different answers.

Amanda Cupido:

It's so interesting because we always just think that what we're thinking is what everybody else is on the same page about. It just really uh holds up a mirror to how wrong we can be. I actually even think that this comes up with the word podcast. Since we're on a podcast, we might as well uh lean into it. You know, when someone says the word podcast, the people who have been podcasting since its inception in 2004 are thinking audio only, RSS feed, right? But podcasts of now, that word, there are video podcasts, they're on YouTube. Does it count if you only put up one episode? Is that a podcast now, right? Or is it a standalone video? Like that definition is so unclear. So even when we're talking about things that seem straightforward, like a podcast, let alone industry 4.0, like people think so differently. So I find this fascinating. Thanks for sharing that example. I want to do a gut check here. Okay, so I wonder if, on average, you think manufacturing professionals are overestimating the technological capabilities that we currently have and what's in the near future.

Jeff Winter:

So I think the key thing to remember, going back to industry 5.0 as defined by the European Commission, it's not actually about a brand new set of technologies, if you look at it. It's it's not like someone invented 5.0 tech and dropped it on the market. The tools, artificial intelligence, robotics, digital twins, cloud, augmented reality, edge computing, all that stuff is it's already there. The real question isn't do we have the technology? It's can we use it at scale in a way that delivers on the vision that we're trying to achieve? Whether you have the vision of industry 4.0 as originally defined or industry 5.0, the same question applies. And that's where companies get tripped up. Demos look amazing, pilots look slick, but stitching it all into day-to-day operations with real people, real data, and real business models, that's the hard part. So are we overestimating? I'd say in some cases, yes. Now, the technology is ready enough to support industry 4.0's vision, industry 5.0's vision, but the bottleneck isn't the hardware or the software. It's leadership, right? It's strategy and it's culture. The vision of human-centric, sustainable, and resilient industry, it's completely possible. The technology is there and it works. The challenge is whether companies are really ready to run with it or not.

Amanda Cupido:

And so, what advice do you give to a leader or even somebody on the factory floor who's excited but feels that hesitation from the team around them? Like, what would you advise for these folks who might be needing that extra push to be more ready?

Jeff Winter:

So, a lot of initiatives that I see are driven by new technology advancements. And even if they're just dabbling, they're experiments, they're pilots, they're driven by it. Look at just AI in the past couple years since ChatGPT came out, and how many companies now have made initiatives and strategies around generative AI and now agentic AI, just because the technology is there and people are starting to see other people have successes, which results in fear of missing out or FOMO, and then that drives this need for companies to go, we have to do something or we're gonna be left behind. But not many take a step back to actually really understand the art of the possible in terms of what it actually can do. So they can apply it towards two aspects of their company. The first is solving problems, which is what most I would say do focus on. They think of the technology and they go, what problem can this technology solve? I think that's a great starting point. But I would argue it also misses half of what you should be looking at. The second is a concept called future solving, which I actually got from Brian Evergreen in his book, Autonomous Transformation. And I love this concept because it shifts away from looking at technology, especially AI, to going, but what can we fix today? And it re-asks the question, but what new future can we create? There is no problem today. We're talking about creating something, whether it's a new business model, a new offering, a new way of working, whatever it is that's new. So it's not fixing something that wasn't working. It's creating something entirely new based off of where we want to go. And if you start thinking in that mindset and educate yourself on what the technology is and what it can do, you will come up with a better vision and a better strategy and a better set of communication internally and involvement of employees so that they know how and why and where to use the technology to benefit them as individuals, their departments, and as the companies. Because technology doesn't fail often technically. In fact, I rarely know of technology failing technically or the initiative failing because of technology technically. It fails because the employees either resistant, they don't understand how it helps their job, they don't understand how it fits into a purpose or a mission. And so it ends up stalling for non-technical reasons. And that's the part you need to focus on more because it gets back to understanding what are you doing, why are you doing it, where are you going.

Amanda Cupido:

What about people who are caught up when the because they're thinking about factory debt?

Jeff Winter:

So the way I look at it to answer any question of I'll call it any new purchase or adoption or application of technology is you need to understand the category of initiative that falls into. And this is related to another post that I made, actually, one of my more famous ones, which is around the types of industry 4.0 initiatives. And I broke it up into modernization, optimization, and transformation. And those are very different. Each of them have different purposes, each of them have different goals, each of them are graded differently. And where I see a lot of failure occurring is by labeling something one and then treating it like the other. So a good example, modernization is usually about replacing older, outdated technology with new, more modern technology systems or ways of working. The justification for that is widely different than an optimization where you're trying to just get better at doing something using your existing systems, ideally already modernized, but maybe not. And that's way different than transformative, which is fundamentally changing how your company works, how it creates value, how it captures value, or how your employees work. So if you label something as transformative and it's really just upgrading an old tech system, you're gonna fail overall because you're gonna grade it wrong. It's not gonna achieve what you want. And that's that's a huge impact. So in the case of let's say you're in the middle of a deployment and a new technology comes out, you can decide does that impact where your vision is going? How does it relate to your initiative? Was it a modernization initiative where now it makes a fundamental difference in whether you transform to a new thing or not? Then it may be justified to replace your technology, even though you just did it, you know, right before. Or you may decide to go, this doesn't add any value compared to where we're going. The current version of modernization that we have is sufficient for the vision we have for where we're going. So I think it depends on a case-by-case basis, but you really need to understand why you are looking at this technology and what type of initiative are you trying to do.

Amanda Cupido:

All right. We can't have this conversation without talking about cybersecurity. So as we look ahead, there's only going to be more device interconnectedness and even more personal data involved. Are you concerned about the expanded attack service?

Jeff Winter:

Cybersecurity is one of the probably the biggest elephants in the smart factory. And because every time we connect another robot, another sensor or AI tool, we're not just creating value, we're creating another doorway. And attackers only need one open door. I mean, if you look at uh IoT Analytics last year said that there was something like 18.8 billion connected IoT devices. I mean, that's that's a huge amount of devices. That doesn't even include laptops and cell phones. Just those devices alone is a huge amount of interconnected ways of accessing systems. Provides a huge value, but it does potentially open many doors. So the mistake companies make, I think, in my opinion, is thinking of cybersecurity as an add-on, something that you bolt on at the end. In reality, it has to be has to be baked in from the start. And this means, in my opinion, three things. You design for security, not for efficiency, or not just for efficiency. Every connected device or data stream has to be secured by design, not patch later. The second is you need to treat people as the front line. The best firewall in the world won't help you if an employee clicks on the wrong link. And so training and awareness are as critical as the technology you use. And third is make it continuous. Threats evolve daily. Cybersecurity in the factory of the future isn't a project, it's a living capability, just like maintenance or quality. So you have to treat this as one of the core fundamental aspects of how you approach your journey and your vision of industry 4.0.

Amanda Cupido:

Thanks. So well put. As we look ahead, are there any learnings that you think stand out from everything we've implemented already that we could take as we continue to implement and evolve into the future?

Jeff Winter:

We aren't done with industry 4.0 yet, regardless of whose definition you use for industry 4.0, either as the vision of and destination of where we're going or description of the time that we're in right now. We still have a ways to go. A lot of manufacturers are stuck in pilot purgatory. Great demos, lots of proof of concepts, but not enough at scale. And that's lesson number one. Don't confuse experimentation with transformation. I would also have to say that another big lesson is that technology alone doesn't move the needle. Industry 4.0 has taught us so far that you can have tons, thousands of IoT sensors. You can have many on every single machine and dashboards and every office. But if the data isn't trusted, if workflows aren't redesigned, and if people aren't engaged, the value never shows up. And maybe the biggest lesson as a result of this is communication. Too many initiatives were framed as tech projects instead of business strategies, business imperatives. And that's why they fizzled out or met resistance. People didn't really understand the why. I love Simon Sinek's golden circle. It all comes back to the why. And if the why isn't clear, adoption never sticks.

Amanda Cupido:

Yeah. And I was just about to ask, how do you make sure people don't get left behind? But I think you've just answered it. Is there any other tips that you have for making sure that everybody is coming along with you and you're not just running with the torch alone and you look back and find out there's no one there? Or in other words, is the global workforce prepared for all of this?

Jeff Winter:

The simple answer is no, not yet. I mean, we're going to leave people behind if we treat this as a tech upgrade instead of a workforce transition. The tools are racing ahead at speeds that most of us have a hard time comprehending. But skills, organizational design, and incentives haven't caught up yet. So if we digitize tasks without redesigning roles, we create automation anxiety. And if we buy platforms without building capabilities, we we manufacture dependence on a few heroes. So if we we end up scaling pilots without the proper training, we're gonna end up widening the gap between the early adopters and everyone else. So I think, in my opinion, that the fix is simpler and maybe maybe harder than just buying something new to try and solve a particular problem. So a couple of things I like to point out here. First is we have to redesign the work, not just the workflow. Pair every use case with a role map. You know, what the human now does more of, whether it's judgment, whether it's it's you know exception handling improvement whatever it is and less of repetition number two is upskill in weeks not years bite-sized job embedded learnings micro credentials you know augmented reality job aids onboarding for all the new technologies peer coaching measure skills adoption kind of like you would measure OEE overall equipment effectiveness make sure that you're constantly improving next is build career lattices not ladders create visible pathways from operator to you know tech to analyst to improvement lead and reward problem solving and cross skilling and last I would say is make change management a first class citizen communicate the why I've already mentioned the importance of this involve the frontline champions and link incentives to new behaviors not just new outputs but in addition to our workforce not being ready I honestly think our leaders aren't ready either we've poured billions into technology but far less into preparing our people you know the workers are told oh artificial intelligence is going to help you but then not show them how their roles evolve leaders talk about digital first strategy but can't explain what that means for decision making or accountability or career paths. And that disconnect breeds fear on the floor and confusion in the boardroom. So the the risk isn't just leaving frontline workers behind it's leaving managers and executives behind too. Many still lead with playbooks from the last industrial era, assuming efficiency alone is going to win and in a world of artificial intelligence, in a world of autonomy and and human-machine collaboration, that mindset is already outdated.

Amanda Cupido:

All right you put so much into that answer. I hope people were taking notes um I got another one for you which might have a meaty answer as well. How do we measure the success of industry 4.0 and when should we begin to bridge to the next level of industrial innovation?

Jeff Winter:

Great question. And there's no silver bullet for this one. So first up it depends on how your company defines industry 4.0 and your role within it are you trying to survive the revolution are you trying to just stay afloat until the next one? Or are you trying to lead? Those are very different ambitions. And I hear all the time but my company isn't even at industry 3.0 yet that's only true if you think of industry 3.0 as the epitome of automation and digitalization. But if you view these eras 1.0 steam we'll say 2.0 electricity 3.0 automation you've already lived through them we're done with industry 3.0 you've made it your company might be thriving now or struggling now but you're here you don't have to be the perfect golden star of industry 3.0 to start making advancements in industry 4.0 you can still have paper processes you can still run a lot of your operations in Excel. It doesn't disqualify you I don't advise it but it doesn't disqualify you. The game isn't about it's about knowing what technologies to apply where to apply them and when to apply them in order to either survive or to thrive. And you have to make that choice. That's where the two views of Industry 4.0 matter if you treat it as an era then success is simply engaging with the technology of our time. Pick your favorite technology and just engaging with it so that you're not left behind. And if you treat it as a destination then success is judged by how close you get to that vision of fully connected autonomous self-optimizing operations for industry 4.0 or the human-centered sustainable resilient approach of industry 5.0. And there are many maturity models out there you can use to evaluate your current capability or maturity against the art of the possible the highest level of achievement but no company is there on any of these maturity scales and honestly I don't know any company trying to get to the highest level of achievement it's all about the right level achievement for your company at the right time. And either way grading success has to go beyond tech adoption for some it's cost savings, efficiency gains or uptime. For others it's more ambitious data-driven decisions, new business models, customer co-creation. And in some cases success is also about societal impact. Are you empowering your people? Are you advancing sustainability and are you building resilience?

Amanda Cupido:

All right one last curveball question for you before we let you go if you could fast forward 10 years, what decision are you making today that you think you will regret the most?

Jeff Winter:

I would have to say it's experimenting more. I think of myself just in general as an earlier early adopter just like on a technology you know adoption curve I'm always someone that kind of adopts new technologies when they come out. But the one thing I think I could do better at is experimenting with them, trying to focus on looking for ways that they can help me with my work, my job, my career rather than just going, this is awesome and I'm going to use it because I'm an early technology adopter that's probably one that I would say that I might look back on because the amount that things are changing is happening so fast that failure to react quickly can be catastrophic at a personal level or at a corporate level.

Amanda Cupido:

Yeah, for sure. Well Jeff we'll leave it there. Thank you so much for joining us and thank you for tuning in to People Before Machines conversations on the chaos of factory automation powered by Eclipse. We're here to challenge the status quo in factory automation because machines don't build factories, people do. The technical producer for this podcast is Ryan Dentinger. I'm Amanda Capito if you got something out of today's episode we'd appreciate it if you share it with a teammate, a plant leader or anyone who's tired of the automation echo chamber. Be sure to follow for real talk, bold questions and sharp insights and remember the future isn't fully automated. It's people powered talk to you soon.

Outro:

Thanks for listening to People Before Machines conversations on the chaos of factory automation from Monday morning to the very near future for past podcast episodes search people before machines on Spotify Apple Podcasts Amazon Music YouTube or EclipseAutomation dot com

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Amanda Cupido

Host
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Ryan Dentinger

Producer
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Jeff Winter

Guest