Demystifying AI on the Shop Floor

While artificial intelligence is transforming modern industry, separating practical shop-floor applications from speculative buzzwords is essential for manufacturers seeking measurable productivity gains.

In this episode, host Michael Thiessen sits down with global technology expert Chris Carter to demystify artificial intelligence (AI) in discrete manufacturing. With an extensive background spanning automotive and aerospace engineering, Chris breaks down how practical AI algorithms, machine learning, and predictive analytics are applied directly to machining operations. Together, they discuss overcoming data silo challenges, automating quality control, and deploying intelligent software tools to optimize toolpath efficiency and machine uptime.

Whether you are a plant operations manager, CAD/CAM programmer, or manufacturing engineer, this episode provides a realistic, actionable guide to adopting AI on the factory floor.

In this episode: 
00:00 - Introduction: Cutting Through the AI Hype in Manufacturing 
04:30 - Real-World Applications: Machine Learning in Automotive & Aerospace
11:15 - Overcoming Data Silos & Preparing Shop-Floor Infrastructure 
18:40 - AI in Quality Control, Predictive Maintenance & Toolpath Optimization
26:10 - Upskilling the Workforce: Human-in-the-Loop Automation 
34:25 - First Steps for Implementing AI in Precision Machining

Thanks for listening!

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Transcript

Speaker - Voiceover 0:01

Welcome to the All Axis podcast from the Experts at Tebis. Each episode we'll talk about technology topics, trends, or solutions that manufacturers need to know, and today's rapidly evolving time. Sit back, enjoy the discussion, and let us know what you think.

Speaker 1 - Michael Thiessen 0:20

Hello, my friends. Welcome to the All Axis Podcast. I am your host, Michael Thiessen, and uh I always say the same thing. As usual, we'll talk about very, very important items um every single time that we we get together. And uh and it's always interesting. And of course, what is today in in everybody's mind is what are we doing with this artificial intelligence? How are we gonna utilize it in our daily lives? If you have not yet dabbled with it, it's about darn time that you do. I'll that's all what I can say. But uh AI is everywhere, and this this particular technology has gone leaps and bounds from when it started just a short time ago to where it is now. And of course, these kind of topics, especially in the manufacturing world, um, we kind of need to figure out of how it can be utilized and how it should be utilized. And of course, in my small little brain, I don't have all the answers. So we are always looking for individuals that can help us with these topics. And uh today is no difference. We have a wonderful guest that is very hard to get because he's traveling all over the place. And uh this particular guest has been familiar with this topic since probably around 2011. He's worked with multiple companies in about, I would guess, 55 countries or more to become faster and more stable and to utilize these kinds of technologies throughout their manufacturing. He's been also featured in Forbes and Entrepreneur and other areas, as well as has he has a best-selling book series and has founded several companies, also including Approyo, uh, which is a private global uh technology firm focusing on IT management and cloud migrations. And on top of it, is uh I would I would call it an expert in AI. Well, he's also familiar with our industry, with the automotive industry, as well as with the aerospace industry. So it was more than fitting to have this gentleman on. And who am I talking about? It is Chris Carter. So, Chris, without any further ado, welcome to the podcast. And I'm really glad that we had you on the show.

Speaker 2 - Chris Carter 2:46

Michael, I appreciate it. Um, I grew up in this industry. I my father owned the company that did the work with automotives and worked with the aerospace. So I'm I am so happy to join in and help add any light I can to this dark subject.

Speaker 1 - Michael Thiessen 3:01

It definitely is, I wouldn't call it dark, but it's more like dark magic that is happening. But uh this AI, I mean, you have now put your life pretty much onto it and saying, you know what, I need to be more knowledgeable about this, and you really dug down deep. So this AI really came to surface, what about uh two years ago, a year ago?

Speaker 2 - Chris Carter 3:23

It seems like very short time. About three years ago, it really came out when they started to put this cute little wrapper around it, what used to be machine learning, and now it's become artificial intelligence and AI. And open AI really went to the went out there with Chat GPT, and then all of a sudden Cloud came out, and then Perplexity, and then Microsoft was working on it, then Google was doing something with it, and then all of a sudden Meta and Facebook, and now it now it's everywhere. There's hundreds, if not thousands, of applications using it.

Speaker 1 - Michael Thiessen 3:53

And it it's almost every single turn nowadays that at least that I have, if that is hiring people, going through resumes, you can go now, you can almost identify some of these resumes that came in that are AI produced, or documents that children write nowadays when they uh when they are in school, uh, which is AI produced and which ones not. And every turn, I mean, yeah, I even dabbled in trying to make myself more younger and fresher looking and utilizing some AI tools to do this. And it's it's stunningly amazing of how real those pictures can look like, even though you have never been in those locations before.

Speaker 2 - Chris Carter 4:36

Yes, as a matter of fact, you and I were talking when you did your new profile picture. And uh I didn't realize who you were when I just got on this uh podcast a couple minutes ago. You look a little bit more mature than you did in your profile picture we talked about.

Speaker 1 - Michael Thiessen 4:49

Well, thank you. Mature is the right word. I'm glad you didn't go with wiser. But let me let me now turn this into the manufacturing side. So, of course, the private side, we can kind of see how AI can be useful in so many different ways. But in the manufacturing side, where we do a lot of hands-on manufacturing, a lot of machine manufacturing, how can AI be utilized in that particular industry?

Speaker 2 - Chris Carter 5:14

That's a great question because again, I make reference to this was the old machine learning. I'm using AI activities to understand logs, to understand punch press machines, to understand CADs and CAMs and activities that need to be utilized in a day-to-day basis. I do a lot with a company called SAP, which is a big ERP manufacturer. And if you look in the manufacturing world, and I'm here in Wisconsin and we're considered the Rust Belt. These companies are using tools like SAP, and then they're using their AI-based tools to help them with the manufacturing side. And it goes not only the manufacturing, but then you start looking at your warehousing and your logistics and your distribution and how you're using it from the shop floor all the way out to out the door and in the door with products and solutions and being able to understand what you're going to bring in, how you're going to bring it in, when you're going to bring it in. And then you flip that a little bit, and there's these bots that are out there that everybody's talking about. I got to have my own bot or I got to do a bot. Well, these manufacturing uh applications now build in bots so people can ask questions, and you can literally ask questions of it before you're utilizing materials or after you're putting it into the different systems. And so it's now encompassing the manufacturing realm to be able to give them information and help with data while that data is being processed and while it's in flight in real time. And so, you know, when I, my father had his punch press manufacturing company in poor Washington, Wisconsin at KMC Stampions, we had nothing like that. I would, I came home from college and I'm still working off of Excel spreadsheets and documentation, not have to do that anymore when he sold the firm because we started that process of the machine learning and gathering those log files and when things were breaking, especially for maintenance and/or customer support. Well, that's a huge capability for us in the manufacturing world.

Speaker 1 - Michael Thiessen 7:16

All right. As my as you're talking, my mind is kind of spinning. And I I could see several ways that I think AI and manufacturing could be extremely important. Predictability, just thinking about that. Thinking, okay, how can I manufacture certain items? And when do you think I should start this? Or anything like this, or even uh on just questions, simple questions such as, hey, what kind of feeds and speeds should I be utilizing on this machine, on this material? Give me that information.

Speaker 2 - Chris Carter 7:48

Yes. And take that one step further. Now you're putting that information in. What if I change these speeds and feeds? When will I have to do maintenance on that die? When will I have to do maintenance on the machine? And you watch the tracking mechanism on that. Each one of those questions has an answer that leads to another question for another component within not only the AI, but within the manufacturing concept itself. And it just starts to, we call it stair stepping. I start to stair step up the questions until I get to the point of no return sometimes.

Speaker 1 - Michael Thiessen 8:23

So is it valid to say when you deal with AI, especially in the manufacturing world? And now it's not so much about you knowing this, but knowing what to ask or how to ask it and ask multiple different items in order to get this.

Speaker 2 - Chris Carter 8:38

Absolutely correct. And there's a great book by a gentleman by the name of Geoff Wolf, GEO F F W O L F. And he talks about talking to your AI and asking it to ask you questions to get better responses and get better answers between each other. And in the manufacturing world, if you ask your AI, it's just going to spit out one thing. But if you start asking, hey, ask me three questions based around this type of a die with these speeds and this feed and these type of distribution activities. What will happen when I need to do X, Y, or Z? And it starts to ask you a question. Then you have to think a little bit and you have to answer that question. And then you've given it the answer that you know is logically and educated. It's a whole different game there, Michael. It changes the dynamics because now you are truly helping your AI to help you and your company to succeed with the items that you may not have even thought about and it may never have thought about because it wasn't taking your responses until you asked it.

Speaker 1 - Michael Thiessen 9:41

But what if you really break down AI to its rarest form? It's all about data, documents, Excel sheets, whatever you have that you have put into this machine or into on the internet that now they're there. And now AI just utilizes whatever has been written once and now is applying this. So if I'm gonna make this in the simplest form, I wrote an article about cooking, and it's not that I know how to cook, but I put an article out there of how to cook certain things. Now AI utilizes this to answer a question for you. Now, how do you discern now if that is if this is right or this is wrong? Because obviously it only utilizes what is out there and then gives you the answer for that.

Speaker 2 - Chris Carter 10:27

That's a great question. And we call that hallucinating. So I tell organizations all the time as I'm going throughout the world, and I'm very fortunate to speak to them, you need bigger, better, faster, stronger human beings in order to utilize bigger, better, faster, stronger AI strategy. And we as the human are the end stop. We need to know is this correct? Is this not correct? Is it partially correct? Is it 99% correct? But we as the humans, as we start feeding our AI, uh large language models, LLMs, that data, and it can be one source or it could be millions of pieces of sources, we have to be the end person to say, you know what, AI, I need you to look at this, this, and this. I believe that this is incorrect, but I also believe that based upon your hypotheses, this is not correct. And I would like you to evaluate that. Where did you get that information? How did you ascertain that? Those are the questions that we continue to ask. I always have my Google Gemini up, and my wife calls it my BFF at work. And literally, we have those questions. I will look at something as the human and I will say, Hey, Gemini, where did you really get that from? Because I do not believe that is accurate information. Can you state your source? And so I have that conversation just as you and I are having a conversation. And it's very important for individuals to remember you are the bigger, better, faster, stronger human being in this relationship. Use the tool to work with you, but don't consider it to be the Bible in any way, shape, or form. Have it work with you, not against you.

Speaker 1 - Michael Thiessen 12:10

Right. I I always find it very amusing when I utilize AI and I ask questions and it gives me an answer back. And I'm going, hmm, this is not quite correct. I don't think it is. And then you ask the question back, well, what about this? And then when I get the response, it makes me laugh. And it usually goes like, hmm, I've never thought of it that way. But yes, you're correct. I'm going, oh, I got you stumped. Way to go.

Speaker 2 - Chris Carter 12:34

It is great when you do that. I love doing that to Gemini. It is so much fun because they will come up with jokes and humor. And that's why I always ask them, state your source. Where did you get that source from? And if you go through that process, you can have a great time.

Speaker 1 - Michael Thiessen 12:50

So, some of the dangers that we're running into with this AI, or some of the, I would say, myths that I hear a lot from the manufacturers and the operators that, oh, this AI is going to replace me. What is the answer to that?

Speaker 2 - Chris Carter 13:05

No. No. You need bigger, better, faster, stronger human beings in order to use those tools. I get so frustrated when I'm at universities and these young people say, Oh, I don't, I'm not needed because AI is replacing anything that I'll do. No. At the end of the day, AI needs us to feed it that information, to review that information, and to make the final decisions of it. What it will do is it will make us as human beings bump up a level in our capabilities and our skills. Now, the bottom layer of individuals who maybe that's all they want to do is maybe they're code monkeys like I used to be. Maybe they're just uh straight on, basic individuals who don't have any inclination of growing themselves and making themselves bigger, better, faster, stronger. Those are the people that are going to kind of get wiped away. And I wrote an article of the top 10 jobs that are going to be displaced and they're going to be replaced by AI. And people looked at that and I said, Well, most of that's automated now. You just automate that process with your AI agent and build upon that. And you grow that level. You need to be able to understand how to put together prompts, how to run LLMs, how to do SLMs. You need to upgrade yourself another level, and you'll be okie dokie.

Speaker 1 - Michael Thiessen 14:27

So, kind of your messages go along with this AI because it can make you stronger individuals. It can actually make you more intelligent in your decision making if you are a manufacturer or if you're a machine operator. By having this AI, it'll make you more a more efficient. Because at the end of the day, that's exactly what every manufacturer wants to be: more efficient in their production. Absolutely. Yes, you're not going to be you your tools may change or your the ways how to do it may change, but it's probably not going to replace you, or your intellect, if I can say it that way, may be used in different ways. That it's not just okay, screwing in the screw in this way, but now it's actually giving you a tool like a screw gun where you can do this a lot faster because now you can do more of the same things than what before you couldn't be doing it.

Speaker 2 - Chris Carter 15:23

So, you know, I I equate back to my father's manufacturing organization. You know, when they first started out, they didn't have any punch press machines, they didn't have any of the bigger dies, they had smaller dies. Um they had to do a lot of manual processes. Well, as they started to grow and the organization grew and they got in new clients, they brought in newer machines, they got in newer dies and punch press machines. It's the same thing if you look at how when Mr. Ford created the assembly line, you know, people were doing everything manually. Then all of a sudden it became a little bit less, and then it became more computer. And now it's you look at these organizations and they're utilizing the tools that have grown over the years. And it's just another tool. The human needs to be involved. And will it be involved uh 100% of the time? No, because once you code in a machine and you do things, you'll have an individual stepping back a little bit. But it's that same kind of concept in my mind, and that's why I think it's perfect for the manufacturing realm. And I wish my father was not retired and didn't sell the company so I could go in there and literally change everything for him.

Speaker 1 - Michael Thiessen 16:28

So would you say that the scare or the angst is the one of the biggest misconceptions about integrating AI, or is there other factors where people are saying I'm not gonna use AI?

Speaker 2 - Chris Carter 16:41

Oh, it is definitely that is the number one angst. No matter where I go, what I talk to, everybody wants to go, is is my job safe? Well, yes and no. Your job as it is now is probably not safe. But all you need to do is tweak your mindset and get up a level, and you are gonna be golden because you're the one feeding it those LLMs and that data. You're the one that's grabbing the log files from the system and putting them into the systems and reviewing those at the end. The system knows how to do things, but it doesn't know what things to do it with. And so that's where I say to the humans all the time just upgrade yourself.

Speaker 1 - Michael Thiessen 17:20

What do you say to these individuals that have such a, I'm gonna call it fear, not fear of being replaced, but more or less the fear of let me say it this way. When scanning technology came out, um, and this is not too long ago, about 10, 15 years ago when scanning technology really, really went, people were excited about this because now I can reproduce my broken dyes and I can utilize it for good. But then also came another level to this where I could say, you know what? I can utilize scanning technology to copy, and I can make somebody else's job or somebody else's part my own job because I copied it and I changed it a little bit here and there, and now all of a sudden it's this new part, but it utilizes all the same characteristics as the old. With AI, when do you know you you run into this fear of it can be utilized not just for good, as we're talking about manufacturing, but also on the opposite side?

Speaker 2 - Chris Carter 18:20

Oh, yes, it can be used for evil and bring in the evil laugh right there. Um, there are bad actors out there in the world that will steal concepts and philosophies, everything down to the small language model of different prompts and different activities out there. Um, and that's again why I tell people it's important to be the human who's educated in that bigger, better, faster, stronger process because you're going to look and grab things, and hopefully you've got a good head on your shoulders and not that type of individual that's going to steal from some other organization or steal some of their CAD/CAMs or uh activities around there, and be able to utilize those in a manner that are legal and are trademarked and activities. I always say, especially in manufacturing, you know, my father was very, very tight on making sure that no part that they ever did looked anywhere near someone else's part. If somebody did that, that was theirs, unless somebody brought their own information to us. And so you gotta look back at the human side of that. Sure, there's going to be people that are gonna do that, but is are those the people you're hiring? Are those the people you're working with? You are the human in that factor. Make the right decisions to benefit the world ahead of you.

Speaker 1 - Michael Thiessen 19:35

Yeah, with anything in the world, it can be used for good or evil, and uh it's all what you can make out of it is is really the key. Yeah, but it's it's it's definitely something that you we need to think about. And we, of course, we see it all the time in the news about the uh the need or the desire for more control or oversight over that particular topic. And I think there's a valid point that yes, maybe there needs to be some control over it, but of course, the more red tape you put on top of it, the more you stifle innovation and kind of reduce the uh innovations to it. So it has to be very carefully done.

Speaker 2 - Chris Carter 20:11

You make a great point. There is a a woman from the EU, excuse me. Um, she is their global um fairness advocate or some terminology that uh they've come up with over there in regards to not only AI, but competition. So the Googles and the Chromes and all this stuff. They're worried about if you put brakes on these type of initiatives, you're gonna slow down and China's gonna advance over us. If you do this, then this is gonna happen over us. We need to be able to be as fast and as efficient as we can be. And she made a comment that uh I just kind of startled at. And in her mind, in the EU, they're fine with putting brakes on so your competitor can catch up to you. I thought that well, that doesn't make sense if I'm going to market first. I'm hoping to be the first to market, the first to win, the first activity. And uh it was a very poor statement on her um account, and especially in manufacturing. I I know my father made his people made some things that were first to market uh back in the and you look at uh I know the people over at Dutchland Plastics and they worked on the Yetis, and they were the first ones to get those Yetis coolers out there, and it was fantastic stuff. Well, it took a year plus for everybody else to figure out and catch up. So now you've got the market, you've got a process, and the only way that they could catch up was from a cost standpoint. And so I I'm not a fan of stifling innovation in any way, shape, or form. I'm continuously trying to innovate, and I hope others still continue to innovate and just keep moving that knowledge forward, but don't steal what you're building on. Right. Innovate and utilize your bigger, better, stronger mind for the future.

Speaker 1 - Michael Thiessen 21:55

It it needs to be natural. I mean, to slow down some uh somebody. When they come up with an idea or a thought process, it's almost like you're running a marathon and you're winning, and all of a sudden you realize, oh, you know what? I'm just going to slow down so that the entire world can catch up to me and then I'm going to try again. I mean, this is just idiotic. But maybe she had some other point and brought that up. But no, slowing down so everybody, the world can catch up. I understand maybe the logic where it could go because now you have everybody on the same platform, you can exchange ideas and thoughts, and therefore you become better. But no, there's something to be said on trying to be the first. It's it's a race. And if I look at that, of course, when I think of AI, I mean, two countries really come to mind when I think of AI. It could be the US and China. And so, of course, these two world powers they go back and forth. A lot of the Chinese, they have a lot of technology over there. So, how much is that being influenced in terms of the technology that they're having versus what we do? And how how how do we see it?

Speaker 2 - Chris Carter 23:03

Oh, I I know how I see it, and other technologists who are in this space see it. The interesting thing is we in the United States throw NVIDIA chips and throw more horsepower at everything. In China, they don't get the best chips. So, what they're doing is they're working on their LLMs and their SLMs to be able to move faster. And it's quite interesting to see the two powers. There's actually three Chinese-based organizations out in Palo Alto right now, and all three of them are using open source capabilities to be able to get their LLMs to run faster than the NVIDIA chips and the capabilities by just throwing hardware at it. And we in the United States, we are going to have to start getting into that. And I've tried to talk this through with other executives. We need to do this. We cannot keep throwing horsepower at it and data centers at it because we just can't build them fast enough. We can't deploy them. You've got backlash now in regards to cities and waters and electricity, plus the fact that we have horrible grid that we still got to fix. You've got a common denominator here. The SLMs and the LLMs are so easy to be able to work on. Look at what they're doing. And so you see companies here in the United States are using those LLMs and SLMs and they're benefiting from them. Um, there's a group of them in the Palo Alto area and Silicon Valley that are expanding throughout the United States, but they've already started in China and they are just at some point, they are literally eating our breakfast and kicking us out the door and saying, nah, you don't get your breakfast anymore because of some of the things that they've designed, because we've not given them those good chips.

Speaker 1 - Michael Thiessen 24:47

So now if we incorporate the art of artificial intelligence with some of the robotics capability, now all of a sudden you have a humanoid kind of robot that can think and even speak to some extent. Are we getting close to like the terminator end times or or or am I on the wrong track on this one?

Speaker 2 - Chris Carter 25:09

Well, uh, the terminator was in 2026. If you go back to the movie, it was 2026. It's interesting because you got the dogs and you've got the human or the machines, and you look at some of those and you just think, what are they going to be able to do? I don't necessarily go back to Terminator, even though I love that movie, and I think that it could be if we don't be careful. But I go back to the movie with Will Smith in regards to everybody's got it their own robot, and it helps them and it does things with them and it supports them. They have conversations with them. Um, I go back to that movie and I think now there's a concept, but then you have to be careful about how's, what's, and whys. And so you look at the tools between Elon and his robots, and then you've got uh, I believe it's General Dynamics and their dogs and their robots, and you've got others that are going out there. It's funny, I was uh I was in Las Vegas and one of the AI-based gyro chopters were copters were there, and it cost $24,000. You can fly anywhere you want to within a it was uh, I think it was a 45-minute grouping before you had to charge your battery, and it literally did it in an AI-based format where all you did was put in your coordinates, documented it, and away you could go. Those things are now happening and will continue to get better and better. Look at Lucid just signed a contract for 40,000 trucks, and they are going to be all AI-based autonomous vehicles that are going to go out and they're gonna go against the robo taxis and everybody else. These things are coming in. Zooks were everywhere in Las Vegas. I must have seen about a hundred of them, probably the same ones, but they've expanded it and they're all over the place. That's all AI-based autonomous vehicles going out, and yeah, it's pretty cool.

Speaker 1 - Michael Thiessen 27:00

So I think you're more adventurous than I am. I've not yet been in one of those autonomous cars and let me have the robot or the computer drive me around. I don't know if I want to do this yet. Have you already sat in those and have you been chauffeured around?

Speaker 2 - Chris Carter 27:17

I have no problem with it. The first time I was a little bit uh okay, let's see how it does in Vegas traffic, because Vegas traffic is Vegas traffic. Yeah, the second time I was fine. Now I if I'm at resort worlds, I pick one up and I have it take me to the main strip. If it's if I'm in one of the locations and I just pull up my Zook app, which one's near me? Okay, I can do it, let's do it. I think it is fun to be actually honest.

Speaker 1 - Michael Thiessen 27:43

Well, at least you don't have to tip, so that's good then. But let me let me come back to the manufacturing side here again because we kind of got off track on this, because but it's very important to know. So the leaders, the managers of these dyes and mold shops, yeah, how should they look at AI and how should they approach to uh embrace the AI? And how does a manager kind of spill the beans to their employees that, hey, we're gonna utilize AI now for X, Y, and Z kind of operations?

Speaker 2 - Chris Carter 28:10

So I will answer that second part first. Uh, I think they should be very upfront and honest with every employer that they have. I tend to be that way. I think it's important. Guys and gals, we're gonna utilize this because we want to make sure that we are optimizing our dyes, especially in a punch press operations. You know, I not only with my father, but I did some work at a little toilet manufacturer called Kohler. Um, great people. They also need to do maintenance and support on massive dyes. We all know these multi-ton dyes. Harley Davidson's doing those same things. Use those activities and start there. Being able to understand from a log and how much you're using and how much you're putting through it, and if you could go faster, slower, if you could put more. Those things are so beneficial. And at the end of the day, you're still gonna have the maintenance staff in regards to those dies that are gonna have to go in there and make sure that they're taken care of. So you're not getting rid of their jobs and you're really not pushing them to be AI centric. What you're doing is you're optimizing those machines and those dyes for the most precise capabilities and timeline. Because you and I know from a timeline, you go over the time of maintenance on activities, you've got a really good chance of breaking a two-ton die. And once you do that, you are so much trouble. So it really helps them. And if you've got somebody that is your champion with that in that department, that's the person you go to right away and say, Look, I want you to start looking at this and investigating and seeing how we do these. When do you come in and stop the die and decide it's time for shutdown? How do you do that process when we've got multiple orders? You know, they've been building plastic resin chairs at the facility for the last, let's see, it's May March, March now, it's March. So they're shipping those off to the Home Depots and everywhere else then the world. And now all of a sudden, that die is probably going to go out, get get get maintenance because they've probably done their run for the entire order for the season. And how many more could they have done? How much faster could they have done it? Could they have gone to another product and done planters and moved in that machine? So it's all those things. And once you have that champion that really wants to learn that stuff, that's when things go because then you're that person's training others, and it's the champion, then it's training, and then it's the go forward strategy with it. I think it's a huge win for any organization that has that capability behind them.

Speaker 1 - Michael Thiessen 30:38

Well, it's interesting to see the multifaceted use of how AI can be used because uh a few episodes ago we had an individual on that utilized AI in metrology, looking at shapes, looking at items that come on the conveyor belt to see which one are damaged, which one have not been fully processed, or maybe the tool broke or something like that. So it's rather interesting in how AI can be utilized. And it almost seems like that for many, many years we've been saying that if you're not automating, you're falling behind. And you need to do this. Now it seems like the new slogan is if you don't use AI in your production world, you're falling behind. Is that the correct statement?

Speaker 2 - Chris Carter 31:22

Yes, yes, 100%. So um, you know, you talk about you just talked about them because I actually listened to that and followed that podcast as well. And I thought it was so cool because not only is it being done from the parts that are coming on the conveyor belts, but I look at it in other organizations and other industries, such as um the food industry. When they're picking products and there's these ugly vegetables or ugly fruits, they get slit into a different area just based upon what the scan says from an AI perspective. And that's going to a different area to be sold as a different means. And it's the same thing with parts. And I know DMAX uses it. I know Ford and GM are using those kind of capabilities to find flanges and so where does a company start?

Speaker 1 - Michael Thiessen 32:07

If I'm a manufacturer and I've not dug into this entire AI world, yes, maybe I've used Chat GPT once or twice, but for my manufacturing operations, where should a company start and what should they look at?

Speaker 2 - Chris Carter 32:19

Well, first find somebody that is knowledgeable in your industry and ecosystem from a technology standpoint. You know, if you want to call Michael or if you want to call myself or somebody else, that's great. Start a conversation because remember, the tool you got to make sure you match up the correct ROI solution with the right tools, with the right needs and the right capability within your organization. And then find that champion inside that particular individual and those organizations. And then you've got to be able to take and understand what is it truly going to be and how is it truly going to be within your organization to provide some type of support and mechanism around that? So it starts with doing your research first. You can't just jump in and I've, I want this tool and I think I'm gonna do this. Do your research first, make sure that research is right, bring in somebody that can help you from a third-party company or within your organization and start that process. It's not a quick process, it is not a one-day meeting or one-day workshop. You got to put some meat around a bone of what you truly believe. Customer service, is it gonna be your manufacturing? Is it gonna be your robots that you're working on? What is the true piece that you would like to start with? And only do one at a time. Do not try to boil the ocean. Uh, there it's interesting. I've there's an organization I we work with that literally they started multiple processes, and the same champion was doing like five or six of them.

Speaker 1 - Michael Thiessen 33:49

I'm like, what are you doing? You're gonna kill yourself. You probably have seen this now so many times because you're you're assisting some of these individuals. What are some of the challenges that they need to overcome and some of the roadblocks that they're running themselves into? And what do they do about it to get over them?

Speaker 2 - Chris Carter 34:05

Uh so some of the things that you that is people just don't understand it. They don't understand what the AI is, why it's a benefit to their organization, what it's we're an old school manufacturing firm. We don't need any of that newfangled AI stuff. No, Dad, actually, we do. If we're not gonna be left behind, we need to do this. And I make that comment based upon my father and I's conversations. So, not only do you need to find the right people and get them convinced, you got to find budget for it, you got to find uh the data for it, what are the machines, what are the learning processes you're gonna go through, what are the systems you're gonna use in order to benefit your organization? And what's your outcome? What do you want to see? Do you want to see a cost reduction? Do you want to see a time reduction? Do you want to see a human reduction? And if you don't know, you don't know. Those are great things to find out and learn. Well, let's see how much time it takes. Let's see how many people it takes to do these jobs with and without. Let's find out what it's gonna cost us at the end of the day. Is it gonna be a positive or a negative on our bottom line and our budget? How are we gonna get it from that budget? So there's all those steps in there that need to be taken. But at the end of the day, it's small POC, ROI-based. Um, I like to say make it an ROI-based POC. Don't just do it to do it.

Speaker 1 - Michael Thiessen 35:24

As we're winding now down with with some of the these thoughts that we have in here, uh, Approyo, the company that you have, is this something that you can assist companies with or advise companies? Is this something that you could offer to individuals that are currently listening to us and saying, you know what, I've never dabbled with it, but where do I get this information?

Speaker 2 - Chris Carter 35:45

Absolutely, we can. Uh, the organization can. I can personally. I like to meet with people and have coffee or a bourbon. And if anybody's got questions, my time is always available to individuals to help them learn and to support them with their growth as well as their company's growth. So the company at the end of the day, yes, they can help. But me also at the end of the day, I can help gain a little give them a little knowledge to support them in the right direction that they're going to.

Speaker 1 - Michael Thiessen 36:12

You had me with bourbon, not so much with coffee, but hey, um, I'll be calling you about my AI thing.

Speaker 2 - Chris Carter 36:17

It's my morning and my night. I got to do one of each.

Speaker 1 - Michael Thiessen 36:20

What could you advise some of the listeners as we're coming out towards the end of it? What should they do and what should they do first?

Speaker 2 - Chris Carter 36:27

Yeah, first thing to do is find me on LinkedIn and just ask questions. I'll answer any questions anytime, even without the coffee and bourbon. Second, activities out there, do your research. Use your Google Gemini. Go use Google, get some information about. I've got this question. Can you help me with it? It's amazing what Google will do for you. And remember, at the end of the day, you're not in this alone. There are myself and hundreds of other people that are out there that are willing to help. Sometimes there's costs involved, sometimes there's not costs involved. Sometimes it's just that bourbon, as I made reference. But again, at the end of the day, help yourself by starting with the activities of learning what you're looking for. And you don't have to just know it all. You know, I tend to verbally vomit into my Google Gemini all the time. And then we have that conversation back and forth, like I made reference. Those things are great. You will learn a lot by having that conversation between you and your Google or you and your Gemini. And uh, those are great places to start.

Speaker 1 - Michael Thiessen 37:31

Well, awesome. Chris, it was a real pleasure. I mean, I almost feel like I've talked to my AI bot. Any final thoughts that you have or any final comment that you want to get out that you have not yet done so?

Speaker 2 - Chris Carter 37:44

Uh I would literally like to say there's an old Nike commercial that says just do it. Just do it. Do not be afraid. Do not be afraid to try. This is the reason why you started a company. This is why the reason that you went to that employer to get a position with that company, take information, learn information, and just try because you will find out you will become very successful very quickly by trying those.

Speaker 1 - Michael Thiessen 38:09

Awesome. Chris, thank you again for being on the podcast. Uh really appreciate it. And to all of you listeners, do what Chris said. Just do it. Get involved in these artificial intelligence talks. Look at your own company, make yourself a bullet point list of what you're trying to achieve, and then maybe ask the questions of how can you improve certain things with AI? Not everything can be solved utilizing artificial intelligence. There's something to be said about your natural intelligence, but you can add to it by utilizing these bots, these agents, and asking these questions. Utilize AI in your personal world. Uh, not I'm not saying that go out and make pictures of yourself and upload it, but ask questions to Gemini or anything like that, and use it for good. Make it so that it helps you in your daily job and making you more efficient, more productive, so that you can get more done. Because we all know there's not enough hours in the day to manufacture the goods. So utilize it for good. And yes, automation is necessary and you need to do this, but AI is equally important that you need to look into that as well to make your company successful and also to make sure that tomorrow your company will live another day. So it was very enlightening to kind of see as we're going through this entire timeline here of how AI can be utilized. And this is now, I think, the third or fourth uh individual that we've talked about AIs with. Make sure that you're on top of it and on board with all of this. Uh, thank you all for listening to uh on this episode. And and thank you for listening to the All AAxis Podcast. And we hope you enjoyed today's episode. Don't forget to subscribe to us on Spotify, on Apple Music, or wherever you can find us. We're almost everywhere. Uh, feel free to share the episode within your network. If you liked what we had to say, leave us a review. We'd love to hear from you. We love your feedback. Contact us if you have an idea and you want to pitch it and see if it would be good to be on the All Axis podcast. Contact us. We'd be happy to bring your knowledge to all of the listeners out there. So, for more updates, follow us on Instagram as well as on LinkedIn. And as always say, keep shaping the future of manufacturing and stay active and ask the questions. Thanks a lot for listening. We'll see you next time. Bye-bye.

Speaker - Voiceover 40:35

Thank you for joining this episode of All Axis. Please leave a comment or review with your feedback or what you'd like to hear in future episodes. To learn more about manufacturing technology solutions and Tebis's capabilities, visit our website at Tebis. That's T E B I S dot com.