Being an Engineer
Being an Engineer
S6E46 Rick James | ANSYS & Engineering Simulation
Rick James is the Chief Executive Officer at SimuTech Group, North America’s largest ANSYS Elite Channel Partner. With a 25+ year career at the intersection of mechanical and electrical engineering, he has spearheaded multi-million dollar projects, FEA analyses, drop testing, and reliability-driven design efforts in industries from semiconductors to medical devices.
Holding a Doctor of Engineering in Engineering Management and both BSME and MSME degrees from Southern Methodist University, Rick blends deep technical expertise with strategic insight. He began his career at Texas Instruments, tackling IC packaging and structural analysis, progressing through leadership roles at Sulzer, and later heading consulting services at SimuTech.
At SimuTech, Rick leads a multidisciplinary team offering simulation and physical testing services across a vast range of disciplines—including structural, thermal, fluids, RF/electromagnetics, optics, VR/AR, and probabilistic design—to “solve the unsolvable.” He is passionate about simulation-driven innovation, the rise of digital twins, and elevating engineering through mentoring and workflow optimization.
His thought leadership extends to speaking engagements on fracture mechanics, predictive maintenance, and digital twin methodologies. Rick also serves on Southern Methodist University’s Mechanical Engineering Industrial Advisory Board, shaping the future of engineering education.
LINKS:
Guest LinkedIn: https://www.linkedin.com/in/richardjames/
Guest website: https://simutechgroup.com/
Aaron Moncur, host
About Being An Engineer
The Being An Engineer podcast is a repository for industry knowledge and a tool through which engineers learn about and connect with relevant companies, technologies, people resources, and opportunities. We feature successful mechanical engineers and interview engineers who are passionate about their work and who made a great impact on the engineering community.
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Rick. Hello and welcome to another exciting episode of The being an engineer podcast today we have Rick James, the CEO of Simutech Group, a seasoned engineer with over 25 years of experience in mechanical and electrical design. Under his leadership, SimuTech Group has become the number one ANSYS partner in North America, helping companies across a variety of industries tackle complex engineering challenges through simulation driven product development and design optimization, covering disciplines from FEA and CFD to optics and electromechanics. Rick holds a doctor of engineering in Engineering Management from Southern Methodist University, where he currently contributes to the Industrial Advisory Board. Today, he joins us to discuss leading technical teams, driving innovation with simulation and shaping the future of simulation in engineering. Rick, thank you so much for joining us today.
Rick James:Thank you for having me. I'm excited to dive in and talk about all these fun topics.
Aaron Moncur:Yeah, let's let's nerd out. Okay, so first question I ask everyone is, what made you decide to become an engineer?
Rick James:Well, I don't. I didn't, I don't think I actually knew exactly what engineers did as a kid, but I had two grandfathers in rural Oklahoma that built a lot of things, and so I didn't know any different. I built my own go kart when I was seventh grade. And then, you know, two strokes, centrifugal force clutch and, you know, piece of oak for the break. I mean, it was pretty, pretty low tech, but my parents encouraged me to build stuff, so I had a three story for it in the back of the house that was taller than our regular house. It had a fire pit fireplace and trap doors and ceiling fans and electrical outlets, and it was ugly as anything. Sounds amazing. Yeah, it was like 11 or so. And I think when you don't know, as a kid, you don't know what is appropriate socially, or I didn't know it was inappropriate to build, not build a three story for it. So it was, I remember my parents said it's time to take it down. And I was like, You're right, oh, wow,
Aaron Moncur:along with that, huh? Yeah, it didn't tear part of your soul out to bring down this three story tree house.
Rick James:I think it's because I it was such a patchwork of there was a I grew up in San Antonio, Texas, and did a lot of new homes going in. And so I would literally attach a rope to my huffy bike and haul lumber to my house. So it was always this, like, perpetual, you know, oh, I found some more plywood I can build a new level or something. So I think it was always a patchwork. And, you know, like, said it served its purpose. And so I think it wasn't until, really, like, shop in seventh grade, where I started getting metal or other things, and, like, not sure I was really that good at it. I just enjoyed it. I mean, that's different. I think a lot of people are like, and I was building model rockets that were, you know, within 10 feet accuracy on launch. And it just wasn't me. I was a little more sloppy, but I had fun doing it. So I think that was, you know, and I really thought I wanted to build houses, so architecture was really the route I wanted to go. And I was good at math. You're good enough at math. I wasn't the world's best student. And I remember talking to the dean at University of Texas, because I was going to play football at UT, thinking about that at the time, and he was pretty a lot of contempt towards the athletic department, and told me that it would probably take seven years to get a bachelor's degree like what? So I kind of said all civil engineering at SMU, and two weeks before school started, they canceled civil engineering and said you're now mechanical. And I'd signed a letter of intent to run track, so I was kind of locked into the school, and said, I guess I'll go with it. Didn't know much. And I recall my sophomore year finally taking heat transfer, and this ray of light came down from heaven, and God said you were meant to be a mechanical engineer, like heat transfer and so like statics and dynamics and which, you know, you could be like on the structural side of civil but I was just like, I'm where I belong. I love this stuff. So journey there between building forts and going to school.
Aaron Moncur:But that's that's super interesting. I have a similar story, not the three story tree house. I didn't have that level of skills in my fort building back then, but when I started college, I was in the manufacturing engineering major, and honestly, I didn't know a lot about engineering at the time anyway, like I really didn't know what the difference was between manufacturing and mechanical engineering. So anyway. I was in, I got a scholarship to be in the manufacturing engineering department. So, oh, great. I'll do that, you know. And then a year in, it got canceled that major and so the default was mechanical engineering after that, I don't know. Okay, great, mechanical I guess I'll do that then.
Rick James:Yeah, that is one of those. There was a long controversy at SMU, not worth talking about, but it was one of those. I think I ended up graduated only six other people. It was very, very small school. But, you know, the department, I should say the school is larger, so, yeah. Anyways, it's interesting how schools kind of mess with people that way, you know, career, career paths and things.
Aaron Moncur:So, yeah, yeah. It reminds me of the airlines these days. I feel like every time I get on, I try to get on a flight, like, half a day before they tell me it's three hours later and, you know, just oh, all the schedules get messed up. Anyway, I'm getting sidetracked. So Rick, you are the CEO SimuTech Group right now. Can you tell us a little bit about what is SimuTech and a little bit of the history? How did, how did CB tech come to be?
Unknown:So, I am the CEO. So SimuTech started, I guess, kind of formally, really is STI out of Rochester. So that was the kind of the origins. And then through STI, Ken Lally, kind of the the founder of SimuTech, really is the course of seven or eight acquisitions which really brought together not just with Rochester team, but the Seattle, the West Coast, and then you kind of go around geographically and get a lot of different and some of that was just representative of the ANSYS channel partner network at the time, which was a lot of small players. And Ken had the vision of really seeing at the time, there's a product called multi physics, which really kind of was the the premier product and the ANSYS product line of fluid structure, electromagnetics, you know, single license. It was like, how do you, how do you really cover that much like you, you can't, you got to scale to cover the product line. Just technically. How do you mean, I'm a hack and CFD, or at least I was, you know, I had the undergrad class, and I loved it, but, you know this, I'm not, not an expert at it. So I think there's kind of successive story of looking at, hey, here's this small group of engineers that do a really good job of covering, like, the core finite element, and they're pretty good at these other things and, like, not, let's actually expand and grow. And I think that same, that same methodology occurred. We just finished a merger with ozen engineering and primary, primarily West Coast operations with the other across North America. But man, the talent we grabbed with that was pretty incredible. So just amount of optics and electrical and RF. So this is one of these things that we keep getting bigger, and that's trying to keep up with the ANSYS product line as they expand. So I think ultimately that is to serve customers. I mean, it's one thing to get big, but to know the why and the why is you want to stand in front of executives and explain to them, Hey, why did you do this? And it's like, Well, ultimately it's serve you better. You know the it's one thing to have one expert and explicit drop or ballistics or something, and now I have three, and that's just small numbers on an absolute scale, but in terms of ability to serve a customer, that that gets significantly better. So that's, that's kind of a quick version, I guess, of the acquisition path of how we get to we're about 220 employees right now. Oh, wow, that's big, yeah, and that's spread across, I don't know if we have half in offices and half out of their house. So it's, it's definitely, you know, when I started very in office culture. So that's, that's been a big shift, much like every other company, and then the world probably post covid, but that there's definitely a culture to manage, an office culture and a non office culture, but I think that that's that common thread of really around ANSYS, but also around just doing really cool projects, whether that's related to the pre sales environment, the application engineering or the true just consulting or and there's obviously workflow development. That's kind of a hybrid between those two, but that's that common thread that really drove all the acquisitions and the talent and really that, you know, there's territory, there's a business side of that, but, but those are kind of the the core parts of bringing SimuTech together again, starting really in 2000 so we're kind of that 25 year mark as a company which which is meaningful, maybe more to us than our customers. You know, we don't spout that too much, but
Aaron Moncur:congratulations, that's an incredible journey, and sounds like a lot more to come. Is SimuTech Group primarily focused on ANSYS. Are maybe exclusively focused on ANSYS, or are there other simulation platforms that that you consult on, that you're experts on as well?
Unknown:We are all ANSYS. We've taken an approach, if you go back maybe even 20 years, we were looking at alternatives. We thought we need to broaden from ANSYS, and we want to be a CAE provider. So we had a whole lot of different alternatives, and what we found was a lot of those are getting acquired by other OEMs, like, you know, Siemens, Fe safe, or, you know, whatever, you know, good name off. A whole bunch that I got trained in went through the process, and then as soon as another OEM buys them, like, Man flush all that effort down the toilet just for competitive reasons with ANSYS. So I think it became easier for us to tell answers, hey, we're all in with you guys, and we want to be your number one partner, not just North America, but the world. And that's that's an aspirational statement. We got to earn it. From the business side, the competitive side, it's not just technical competence, but I think that's kind of the key elements for us, is just that's allowed us to focus. You think about, well, there's a lot of system level tools out there. Should we be doing this? So I think some are even like MATLAB, like, look, it's a super, I won't say generic, but I say general tool that you can use. Like, we don't, we have, we don't have to sell it or resell it or advocate for it to be experts in it, just like SolidWorks or Creo or any of the CAD tool. So I think there's a lot of tools that were, I'd use the term little loosely, experts in like, really good. But you know, we're not, we're not actually advocating. We're certainly not trying to help their bottom line. I think it's more like an engineering an engineering workload sort of thing. So that's, I think, even politically, with enhances, I'm sure less I'm listening eventually. But you know, we we value that partnership and that relationship, and we want them to know that, hey, this is you're our you're our, one and only. You know, when we're not going to go split, they don't have to worry about the competitive side or any of that. They're all in with us, I believe, and we kind of share that with them too.
Aaron Moncur:So yeah, I used to listen to a lot of like, personal development type talks and coaching and things like that. There's this guy, Brian Tracy, back in the day, and I still remember his formula was for success was to put all your eggs in one basket and then watch that basket. It sounds like that's the approach that SimuTech has taken, and it's worked out pretty well.
Rick James:It Yeah, that's a hadn't forgot that about Brian Tracy, but that certainly is true. And I think, I think that the benefits of that, you know, especially when you look at partnership, those, those are something I didn't necessarily foresee at the time and again. This wasn't my uni lateral decision or anything like that, but I do recall going to other partners not to be nameless partners, their conference and their channel meetings and thinking they do not know physics. Oh, this is, this is not right. This is not how you treat a channel like all these other things. So I'll give answers some props. They certainly run a good channel program, and that made it easier to want to stay in and actually aspire. You know, one point we were, we were kind of the bottom. I think we actually had to have the political, internal political will to to grow and aspire to be number one through organic and acquisition. So and again, number one is, it's just a number. But I think again, back to scale, those are those things that truly have meaning, that we see being able to handle our customer stats, and you have these things that are more customer centric and not just nerd capability stuff, which I like also, but yeah, that's just kind of how we look at running the business and taking a long view of sharing our customers success Truly. We call an emotional paycheck, being able to watch, you know, our largest customer, launch rockets, and be able to know that you played this really small, small part of that. I mean, small but, but hey, that's, that's one of those buy ins that you get. And it doesn't be a rocket. It can be a turbo machinery blade that you help shave off point 1% because you optimize some, you know, safety, back end, turbulence, cavitation, problem, whatever. And to know that, hey, that's going to be in service for 30 years, the amount of carbon you saved is huge. That's a cool feeling. Yeah, so I think there's, there's a there's this part, again, I think of the engineer personality, they can typically understand that, hey, that is those are two different things, like watching a rocket launch and then watching, you know, knowing you can't even see it, you just intellectually know, I feel really good about that. And I think I try to espouse that, hey, look, this is in our in our world, in our semi tech world, that engineering and every employee needs to take all. Ownership, not ownership, but it feel, feel that emotional paycheck, like, Hey, this is, this is why, this is like, our purpose. This is why we're here. Yeah, things that you can see and things you can't see. And they both matter.
Aaron Moncur:How, how has acceptance of simulation, whether it's FEA or CFD or something else, how has acceptance of the market changed over the years. You know, I don't know 2030, years from now, what was it like then, and how? What's the dynamic in the market now?
Rick James:Yeah, that's, I mean, I think probably 10 different engineers having 10 different opinions, but you'll get one of those 10 here. I think what I saw early, early my career. So prior to Simi Tech, I worked at Texas Instruments, and then I worked at Sulzer in the heart valves division. So I used to help design heart valves and manufacturing equipment. And what I saw the and again, not to go down certain names, I saw a lot of companies that really saw simulation as a validation of a product development process that was done at the end of the Gantt chart, so to speak. And it was planned at the end of the Gantt chart and and they put the other smart guys and gals out with tape around their glasses in the back room and hit him, maybe down in the basement, and, hey, what's the answer? You know, we're about ready to ship the product. What's simulation say? Does it say it's good? We got any problems? And there's this kind of, like proverbial nerd, you know, the negative side of nerd, before nerd was cool, sort of thing that. So let's just say that that that, to me, is what I kind of, what I experienced, what I saw, let's say, 30 years ago. Unfortunately, we still see that now, and that's one of the things that I like to do, just doing kind of not even a technical assessment, but just like super high upfront workflows where show me in your Gantt chart, where, where simulation take place, and you can see the best companies that are like, Oh yeah, the top of that V diagram, we're in the system configuration, and we're we're up here, doing system architecture. We can flow down from there, and we're doing the high level and maybe not even model based engineering. But just like, you know, the upfront stuff, even if it's linear, even if it's simple, for all that, you just see that that's those are companies that run really good engineering product development workflows, and we still have companies that tend to put it at the end, and I feel like those are, they're still getting value from it. And I it's a little hard, you know, as somebody in my role, to say that's bad, I can say that it's there's probably room to improve. It's not just a diplomatic statement, but I think it's the most honest statement I could say. I don't, we don't we don't tell customers how to develop their products. We enable workflow and and tools. That's kind of the philosophical approach to kind of our role at semi tech. But now, if we're invited in, which we are many times that customers we we have close to 2500 active customers right now. So it's our scale is big in our influence, which we take as a heavy responsibility. It's a big responsibility and a big that we want to give good advice and we want to help customers. Again, we're not there to tell customers how to develop their products. I've made that mistake many times, where I've been side eyed like a little too excited to go tell them how to change the barometer of their drop test polymer shape, and I was not there. You know, I was uninvited into that, and I did not know it until an hour into realizing, why am I the only one talking plenty of mistakes I've made in my career,
Aaron Moncur:but that's Next time bring up a few pictures of your three story tree house to provide some clout, right? Like I know what I'm talking about. I did with this 11 years old.
Rick James:I know, I know that's funny. I even had concrete floors
Aaron Moncur:fireplace and, yeah, how about the tools in simulation? I mean, has it the core functional functionality. Has it more or less stayed the same over the past few decades, or have there been, like, pretty significant, substantial changes and improvements in the capability of the software?
Rick James:I think you know, there's certainly the core physics across the product line, not just like core mechanical FEA, but certainly CFD and the signal integrity antenna, RF, you know, the whole even optics. You know from photonics optics, you kind of keep expanding the breadth and depth of the physics so but if I can't take one of those, even look at FEA, the one that I'm most associated with, I mean, FEA, I learned mid 90s, non linear, non linear. Three forms. Non linear. Turns on. How you count up, but they'll say three. I don't think that that said there's been certainly improvements. But, I mean, that's that's been around 30 years, so from that perspective, there's not a huge difference. Oh. Think the difference is really integration with what we say is multiple physics and multi physics. So there's plenty of customers that they have a really strong structures team, and they have a really strong thermal team, which could be fluid, could be the structural side, conduction or conduction, and then, and then the fluid side. And they have these. So that's kind of multiple then multi physics, again, in my terminology, is where maybe you're actually code coupling. I'm doing fluid structure interaction or flow induced vibration, merging those. So I think that that, and even that's been around for 20 years. So I think it's just this perpetual integration of how those those physics talk to each other. And that platform not just like doing scalar functions of like, hey, this parameter is four and pass it back and forth and some ASCII text, like, but actually doing full field coupling. That's still pretty that's still pretty cool. And I'd say it's pretty cutting edge. Again, again. It's been over a really long period of time. We don't see a whole lot of customers doing that, and then you have this tier of customers that are just truly high end, and they don't do it because it's cool. They do it because they need it, right? You're able to make less assumptions on your boundary conditions, let's say on the structural side, if you're really got a couple of fluid system driving it, or even on the antenna side, if you're doing consumer electronics. And people used to do antennas a lot. And guess what? Some of those antennas, they crank out some serious heat. So you used to be maybe they would get, like, a handheld convection coefficient, or just five wasps per, you know, centimeter square, whatever, sort of flocks. And they would go and now why do that? You can actually map those direct fields on those non spatially varying fields. Again, that's always been available in the last, let's say, 1020, years. I think the ease of use of setting up again in your so now it's maybe a workflow, workflow, workflow. I mean, that's maybe the summary point here before that was like a two week project to go, couple it up, and now that's maybe a little more drag and drop, and I and again, I'm also speaking of the answers platform, so admitting that there's certainly other platforms and they have, you know, the big, other big guys have their levels of integration, but at least from my perspective, seeing a single platform one of the Leading, the leading one as it's developed over the last couple decades. Really, integration and speed has been as well as core physics, but integration speed have been the real key.
Aaron Moncur:Yeah, you mentioned workflow, if it was up to you, if, if 100% of your customers came to you and said, Rick, how do we incorporate ANSYS? What you tell us, what's the workflow? What do you think the ideal workflow is?
Rick James:Man, I just got the question on Thursday from a customer up in Seattle. Yeah, I think that part of it is one way of viewing. It is, well, benchmarking your workflow now show the science of better if your workflow now takes you two weeks to get a good answer that you feel good about, or validated, or whatever you know, not the physical test side, but on the simulation side, is 10% improvement. Is that good enough? A 10x improvement? So I think there's kind of like setting setting a realistic expectation that's that's unique to every company, is like, hey, what's, what's a reasonable improvement, if I kind of move to the method, certainly, I think one of the methods for workflow, the how they do that, I think there is really the the, let's Say, prevalence, the explosion of Python, of just like even nested Python, and you're just like Python within Python within Python, and calling each other. And it's really powerful. And I think ANSYS has a great roadmap in that, with integrating Python into every one of the product lines, just so Really descriptible. Everything's not a GUI pic and it's just something that you, you stay within that GUI, and you you insert and you click buttons and you get an answer, and you print screen or whatever, and you have your answer. But I think again, looking at from an architecture perspective, being able to have individual software tools that actually can code couple, not just in that multi physics example, but actually looking at from a system perspective, where you you can go pull these scalar values out, and you can go do some put that to a reduced order model, put these in the real time system. So there's things like that that you can do once you have that core system. That's more, I wouldn't say something besides Python. It's not coming to me ASCII or something simplified tax base, so it's just so much power on power in that
Aaron Moncur:Where are engineering teams using simulation today that they weren't 2030, years ago?
Rick James:Who you know? I think certainly, if I look at the development tools, many. And RF has been around. You know, simulation and RF has been around that long. So I think it's tricky in the sense that, what is it the prevalence or the quantity? Because it's still amazing to me how many people shun simulation for build and test, which, which I'd love to talk more about. And I have huge, huge respect, and I think that you need physical test in a product development workflow. And that's certainly my personal experience outside of the simulation space, you got to have that combo, but, but I don't, I don't have a great answer for you, honestly, because it seems like it's, you know, I could look at where ANSYS is really invested technology. But even if you go, like, explicit dynamics and like less stuff's been around, you go back, go back in the early days, and it might have been like, or even NASTRAN like, you go pull out of NASA and say, well, it was mogul again, you know, sort of old school, and yet that's that's still around. What happened? I don't know. You got like, 1,000,000x more people using it. It's become embedded in the workflow of so many different companies. So I don't know. I think that I probably give you a pretty, pretty weak answer there.
Aaron Moncur:But, well, let me ask you about this. You mentioned that there is some aversion to using simulation. And of course, you're sounds like you're recommending both physical hardware testing in conjunction with simulation. Why? Why do you think that there this aversion still remains, like, what's the I don't know, the mindset or the hurdles that engineering teams are not overcoming.
Unknown:Yeah, I mean, there's, there's plenty of people out there that have made a big business decision based on faulty simulation data, and those memories are long, so so I'll, I will acknowledge that that anytime you have something that was key to making a bad decision that you trusted, that trusted violated, even if that trust was should have been put into an engineer or a culture or a workflow or These other things, but to put it into a technology, to me, is is misplaced. And I I even had a professor telling me that I was undergrad, and he was ragging on FEA because he saw a spoke on a bicycle on the bottom one, and FEA said it was intention. And everybody knows that bicycle spokes aren't intention. And I remember thinking, so, so therefore the conclusion, therefore FEA is wrong. And I remember thinking unless it was pretensioned, really tight. I was thinking depends, but I'm, like, trying not to defend the technology, but just like, kind of a natural challenger. And I was thinking, or unless it was pretensioned and you did a two load step and you pre shrunk, you know, like so I think that you're never going to convince that professor that finite element is a valid tool and could be used in the workplace and commercial. It's great for academics. So I think that people have their independent biases. And I think that to some degree. Look, the value of the value of simulation is really economics. It's kind of a personal opinion about unless you're a national lab or government agency or school, like, where you're really you're probably not driving economic driven. Maybe you have other goals. I mean, the government does. They're not. The goal isn't to optimize profits. So, so I think that's kind of if you're going to use this, and if build and test is a better route, and a lot of people believe that the physics are so complex you couldn't even possibly handle this. And I think, yeah, maybe, maybe you're right, but I think also it could shed insight. And I think, I think if you look at a simulation is something to tell you the exact right answer, or to tell you you have a three by three matrix of design. And I heard this example of somebody doing White Sands Missile test, and they were doing a three by three matrix, and they used an explosive dynamics tool to go essentially eliminate the worst for contenders. It was a million dollars a test, so they weren't getting it wasn't a simulation or test. Example, it was a hey, how do I optimize my financial situation using simulation that I'm still going to make it based on physical tests. So I think that a lot of people tend to have a binary kind of, is it this or that, and where possible, I hope that myself, or anybody else at SimuTech would bring people along and dive a little deeper. You know, use curiosity to understand and make it, make it not so not confrontational, but so better word than binary, but so stark. Like, is it this or that? And hey, like these. Off each other, and like a really good simulation tool has validated test data. And that's that's invaluable, that makes, that makes the simulation so much more valuable, even when you're starting looking at, you know, downstream stuff, you know, digital twin, IIoT, those sorts of methodologies, or, I should really say, mindsets, but that's kind of an approach that I think we kind of espouse, that we have to be invited into, that that's not something we just go, like preach from the hills, but I think that, I think it's certainly when we're invited in. I think that's a pretty common approach that we'll take on simulation versus test? Yeah,
Aaron Moncur:let's talk about AI and simulation. Obviously, AI is, like, this huge thing. Now everyone's using it for different purposes, and it's, it's starting to make its way into more and more engineering, right? There aren't a ton of, like, in my opinion, really powerful, meaningful AI tools yet, but they are starting to creep in, for sure, into engineering. How is AI changing simulation? And you know, like, maybe five years from now? How do you think simulation is going to what's it going to be like? Ai powered,
Rick James:yeah, that's a great question. I'm, I'm really, kind of not on the sidelines, but I'm, I'm really curious too. I think, you know, we've done, certainly, a lot of research with, like, the earlier comments about the within the SS product line, even, kind of the product line of what they're looking to do in 2026 but I think in the broader question that the real, the real way that I see it right now is just in chatbot that I think, you know, being able to use it for tech support or standards or I think there's kind of some the perimeter of simulation That's just kind of, you know, maybe check my scripts. We're talking about Python scripts being able to take that. I kind of, maybe that's a secondary kind of thing of maybe what you're looking at or asking about, you know, the way we see the AI is not so much on what it does, but what problem does it solve? And we had a customer say, hey, we'd like to, we've got these assemblies, we've modeled our whole system with ANSYS, and we'd like to do some derivatives, but we'd like it to design itself. Can it do that? And I remember thinking that this first level, like, what? And then I thought, You know what? That's actually a great aspirational statement, that if you, if you take something that's doing generic here, but like, yeah, you got a 10 foot design, I want to make a 15 foot. And all those components, of sub components, like, they just scale themselves, all based on requirements, either, you know, at the component level or, or, can I make it level? Like, there's a lot of things, I think that. So again, that's a super abstract I get. But I thought that was a good thing when I think about, what can ai do? So I think what we do, what we lot of customers, like, hey, I want these benefits of AI right now. We try to push them towards parametric optimization. And again, that kind of you have to predefine the space, you know, very radius, or material property, or, you know, something along those lines. And then there's the discrete number of solves that goes out and and I think part of that is that the AI landscape really is, there's a it's new. It's really new. So I think we're super excited about it. We've got our toes in it. We're working with ANSYS and doing some of their benchmarking, and we're waiting to feel better about the full benefits, like the production worthiness of that. But I think it's interesting when you think about, well, what, what is it that AI in AI will do the parametric optimization, won't a lot of it's I think if I can build this database, I can keep building this database. Let's say I don't know, automotive, trucks, yeah, we get this database of trucks, and I just keep doing iteration after iteration and small variants. And I keep building this database, and I keep training it, pretty soon, in that class of problems, I can just refer back and get an answer that, let's say, with, you know, within 10% 5% or whatever, that sort of correction, if you want that upfront design. But again, if you're a lot of design is not, you know, 3% accurate. I'm looking for something that's directionally accurate, but it's something better than directionally accurate. So I think that's where AI is going to take. That being able to have this, you know, call it machine learning, call it whatever buzzword you want, but being able to have this database that you can keep referring to and keep doing super fast analysis. So speed, speed is always. King. But I think, you know, answers, did a survey of their users. It's probably been over 10 years now, what's the one reason? What's the one feature that you need answers to be, no matter what is, it changes over the years, and think it was somewhere like 86% of the people that has to be the right answer. So, and I think that's also kind of the, that's the, that's the, those are our peeps that, you know, there's, there's designers of my first job was with PTC out of school, and they had all these like rules of thumb. And there was, you know, designers are paid to be right and analysts are paid to not be wrong, which is kind of like a double negative, but, but I think it kind of illustrates some of that, that if you're going to do simulation, you have to care about the right answer, and if the right answer doesn't matter, then why are you? Why are you? Why are you trying? So I do think that there's an element of like, how can you ensure accuracy? And even maybe, maybe. The other way of asking it is, say, what accuracy do you need in order to make a decision? Because the fact of a simulation is the stress is four versus five. What do you need to make a decision? So I think if you work backwards from not just meeting a requirement, which actually maybe that is a decision, but, but I'm saying at the kind of the totality of a product development workflow is usually to to develop a qualified product that meets certain quality specs, that moves to manufacturing or it moves to a derivative. So I think that having that, how does AI help you make decisions? Yeah, I think that's the, that's the real key, and, yeah, how exactly the workflows are going to work out? I'd say it's a little new right now. There's plenty of, plenty of things you can call AI, and maybe I'm taking too narrow of a definition, like I said, there's, there's there's AI with, like, chat bots and helping in that. And there's certainly agentic that can do things that are really cool too. But if I really get to the simulation driven AI, I think it's going to be really interesting how AI can make decisions with engineers, and maybe for engineers. And that's, I think we're in front of that. Like, it's a little hard in five years to me, seems like a thick fog. You know? Yeah, I think everything's changing so fast. Oh, yeah, big time. So I think that it'd be interesting to see what happens in the early 26 with that.
Aaron Moncur:Can you think of a story that you can share where a success story, right, where the application was just perfect for simulation, and your team was able to save a company a lot of money or time, but like, what's, what's a great example of a big win using simulation?
Rick James:Yeah, I'll be a little generic with the customer, but it was a pretty advanced aerospace application, and the users are really good in terms of, like, the methodologies were sound, they're accurate, they're well trained. They had good hardware. And quite simply, we went in and looked and using Python and just automated. It took their process down from four days to a couple hours. Wow. And in some of that, you know, the four days parts that was maybe from them, so maybe they're helping us out on our metrics, but, but it was definitely, definitely a lot of individual decisions, and a lot of like human handing off to other humans. So I think if you really broke down that Python script, it really encapsulated a lot of their decision making that I think, was a verbal process. And actually be able to put that into, I don't code. You encode a certain level of decision. And some of that had to do with looking at multiple load steps, like in a fatigue fracture domain. So a lot of times you're doing cycle counting. And I've got lots of different I've got a few different models I'm pulling from. I've got to accumulate those cycles to get, like, what's the remaining life of this product? Those are scriptable, scriptable methods, I should say. So I think that. Again, I think if there's a common thread there, even to earlier commentary, commentaries are really about Python and automation. It's just that is so pervasive right now for us,
Aaron Moncur:for engineers out there listening to this who maybe don't have any experience, maybe a little of exposure, but they've never used answers or simulation in general, but they're really interested in at least dipping their toe in the water and getting some experience what's, what's a good way to get started that that's, you know, not, not too overwhelming, but how do you just get started?
Rick James:Good one. You know, I think if you're working for a company, I define the find the people in that department and go, go tell them, hey, I think what you do is cool. I'd love to learn more. Can I shout at you? There's certainly that element, maybe, if you're a student, I didn't, I don't think I was so grad school that I took any classes on finite element. I think just, you know, strength of materials, you know, mechanical engineering stuff, just knowing mechanics overall, just really good fundamental sound theory. I think just. Being able to there's coursework kind of angle, but maybe that's a little too obvious. I think there's certainly downloading the student versions of answers. Yeah, there's demo models in there. There's things you can take. There's there's a whole lot of free resources online. ANSYS does a really nice job focus a little bit more on the learning side, not teaching you how to get trained on the product, but actually just the overall learning that ANSYS has out there that coupled with short term trials of the product. But yeah, there's other other software that can do that too. So I think part of that's just playing with it like I think the other thing is having a problem to solve. It's one thing to get in and like, I'd like to rotate this really cool animation. And that's really cool. I think if you're like, Hey, I'd really like to build a go kart out of wood, you know, can't Can I do it? You're having a problem to solve. I tried making a brisket smoker out of wood. I thought, you know, could I, could I do it? So I actually started mulling that inside of CFX, just to see if I could get, like, the optimal smoke, you know, into my brisket, because as a Texan that, you know, you got to get the brisket right. So I it actually worked out it didn't burn it down. And part of the part of the trick there wasn't the thermal, but actually the smoke. Try, where's the smoke go? Where's where does that flow? So I actually did fully model. I've done a couple different smokers with CFD, but I was trying to solve a specific problem. Now, again, I was already pretty good at CFD when I was doing this, but I think for new people, it'd be really cool that way. It gives you a little more of a goal and actually a little more satisfaction. Maybe importantly, if you're looking for a job, or it's a junior project or something like that, you have a great story to tell. Hey, yeah, I modeled this. If you've seen it on YouTube, where it's really cool at the Lego Formula One that smashes in the walls, and then they modeled it with explicit dynamics and watch that, and they see the parallel between the real and the simulated. So I think just having a specific problem to solve would be a really great place to solve whatever the physics, and there's plenty of tools out there and plenty of learning. It's just a matter of having the background, the gumption, the discipline and asking for help the right person. So those are kind of the keys. But, yeah, great. I'd love for people to get out there, because it's, it's a simulation, I think is it's not just that. It's a key part of any, any modern, modern product development process. But the younger you start, the more that gets into your mindset, the easier that is to let that be second nature when you are developing a product. Is not even a simulation, but just like capturing the essence of a product before you design it, so that you can play with it virtually. And do you know, 10 times 10,000 times more iterations before you get the physical test? So I'm a fan boy. I
Aaron Moncur:love your smoker example. I hope your marketing team got some good pictures and video of that and used it. That's such a great practical and fun use for simulation.
Rick James:I did, I did want to with the thermal wool on the inside of a green egg, and I have thermal imaging of that. So I do, I do believe in in my own empirical data as well.
Aaron Moncur:So nice, nice. All right. Well, I just have, I think, just one more question, and then we'll kind of wrap things up here. I've never really used simulation, but I worked at a company where there was a whole simulation department. It was engineering services company here in the Southwest, and there was a pretty substantial simulation department. So I was exposed to it a lot, and there were people I talked to who are using it every single day, and I remember that at least then, this was probably 1520, years ago, to run ANSYS or any simulation program effectively, you really needed, like, a very powerful computing machine. Is that still the case? Or are there like cloud applications now that will do a lot of that number crunching, processing horsepower for you, and maybe the computer you're on driving doesn't need to be as powerful as it used to be.
Unknown:Yeah, so there's, there's a ton of options. I think, I think the ultimate question really comes almost like, well, if you're a business and you're making an investment in simulation software, what ratio would be hardware? That's one way of looking at it. Yeah. I think there's also the certain, certain mindsets are like, well, computers are cheaper than humans. Just mesh vomit, you know, like throw tons of mesh, or don't spend much time cleaning the geometry up, just throw it to the cluster and let it do, do its thing. There's certainly some people that have that mentality. Sometimes the opposite. You spend a ton of time in the mesh just to get it so the solve time is really, really small. Obviously. GPU and cloud. So that's kind of the landscape. A lot of it has to do with OPEX capex. A lot of if companies are really tied on capex, that maybe not in a support group. Usually support groups that we see tend to have a decent budget for capex, but a lot of product groups they they're really limped on capex, but they have a ton of OpEx. So if they need to go blow 5000$10,000 a month on cloud computing, that's a green light for them. And so they might have a high end laptop with, you know, good amount of RAM. And for good, for pre processing, post processing, report writing, but all the heavy lifting, and actually maybe for some front end solves, just to prove, to see, is it going to converge. And, you know, they take 15 minutes just to kind of kick it off a little bit. And once it's good, they crank it over to the cloud or on site, on prem server, we tend to do a lot. We have a really healthy install within SimuTech. But we also use the cloud. There's a certain point where, just, we're not going to design for Max peak loading. So, you know, we try to stay connected with top few providers. And just, you know, whatever our percentage is, sometimes it's 3% of max, sometimes 20% on any one and that a lot of times too, customers come to us and say, we really want to this. We need to expedite this. And we're like, this, and we're like, well, great, this is our option. We're go to this cloud. And even if that's ITAR or government again, we were cmmc Level Two certified. So if there are some pretty, pretty strict requirements for government contracting, that's something where we do. And obviously computer environment has to go with that. So GPs are the ones that get a lot of questions about, I love GPUs. I love the premise of them. There's, certainly, there's a class of applications that they're epic for, the on on chip or, you know, on GPU RAM tends to be sometimes a limitation. And I know that's being able to couple those together and get those GPUs together and extend that effective RAM. That's that's a key carry a lot of the hardware people are spending time on. So again, I think we're pretty our role in terms of having this heterogeneous network of what our customers use and what we use internally, we try to match that. And yeah, we see the everything, everything just keeps getting more of so we'll see. We'll see how that goes when you look at Nvidia and their stratospheric rise. But yeah, it just keeps looking good for them.
Aaron Moncur:Well, terrific. Rick, thank you so much for being here with us today and sharing about simulation and how engineers are using it and can use it and will be using it in the future. Is there anything else that you'd like to touch on before we wrap it up today?
Rick James:Now I think that, you know, I think for me personally, one of the things that I love about simulation is being able to have impact, even in the role we have now on on product development workflow, and being able to know that you're the simulation. You're truly, truly having a piece of our customer success, and being able to look at that from every industry, whether it's photolithography equipment for semiconductors across the board. But I think just when I think about an engineering profession, when I think about being able to have impact and be able to drive optimal products. Simulation, it's not the only way, but it's a phenomenal way. I've been in professions where careers or jobs, sorry, that really simulation was secondary, and I kept feeling like this is simulation really should be a part of every product development workflow. So I'm an advocate for the industry, but I look forward to any sort of feedback that you guys have. There's certainly excitement I have for helping people develop in their
Aaron Moncur:career. Terrific. Well, along those lines, how can people get in touch with you and or simutech group,
Rick James:SimuTech Group you got that one, right? That's our website. Certainly go there. But I'd love to connect with anybody. The easiest way is go search Rick James and SimuTech, I think there's only one lots of Rick James's out there. Only Rick James SimuTech, so feel free. I'd love to connect with you guys and send me a comment. Tell me what you loved or interested or what you'd like to do with your career. And love to see if there's any way I could help
Aaron Moncur:Wonderful Rick. Thank you so much for being on the show today.
Rick James:Thank you.
Aaron Moncur:I'm Aaron Moncur, founder of pipeline design and engineering. If you liked what you heard today, please share the episode to learn how your team can leverage our team's expertise developing advanced manufacturing processes, automated machines and custom fixtures, complemented with product design and R D services. Visit us at Team Python. Line.us to join a vibrant community of engineers online visit the wave. Dot, engineer, thank you for listening.
