Uncovering Opportunities with the Model Based Enterprise

51:14

SUMMARY KEYWORDS

data, model, people, drawing, build, part, geometry, engineering, tolerances, supplier, feedback loops, business, design, based, engineer, working, file, space, industries, unfurled

SPEAKERS

Jennifer Herron, Damon Pistulka

Damon Pistulka  00:05

All right, everyone, Welcome once again to the faces of business. I’m your host, Damon Pistulka. And with me today, I’ve got Jennifer Heron with action engineering. Welcome, Jennifer.

Jennifer Herron  00:17

Hi, Damon, thanks for having me.

Damon Pistulka  00:19

This, I’m so glad we could get get you here. It’s been a while it’s been a long time coming. Because I really, I’m really intrigued by your business now. And your your background, as we talk about uncovering opportunities with the model based enterprise or model based manufacturing. Because I think this is something that a lot of people are really considering now that it used to be relegated to much larger companies or really haven’t considered as how if they adopted the model base approach throughout the organization, how it can really streamline their business.

Jennifer Herron  01:01

Right? Yeah, yes. And it can.

Damon Pistulka  01:04

Awesome. Awesome. So let’s hear a little bit about your background, Jennifer, because I think I always like to do that. Because he and you got some cool job. And you’re not just

Jennifer Herron  01:14

working towards work experience? Yeah. Yeah. Well, we were, we were just chatting before this. And I went to Washington University in St. Louis. And that’s where my bachelor’s degree in mechanical engineering is from. I also have a little bit of a separate side of me, which is a performer side, I grew up dancing ballet, and then did jazz and modern and high school, and also did some musical theater stuff in high school. And then when I got to college, one of the reasons I chose washu was that I could do some little bit theater. And I also learned to do rhythm, tap dance, which is my absolute favorite still. And I still do it. And so I’m a little bit unique from that aspect.

But it was fun to be able to combine and mash up theater stuff with engineering. And I think I’ve been talking to my Dean of Engineering and to not doing some English classes, because I could do dances, my electives instead. So there you go. I’m a little clever that way. That’s awesome. Yeah. And then, you know, what I ended up doing is kind of my work, jobs. While I was at Wash U. I started working with a professor who was working on being principal investigator for some Mars missions. And this is back in the 90s.

So it’s early on in the days before, we have the big rover that we just put there now. And so I ended up as my first job working at Lockheed Martin here in Denver, Colorado. And I did several discovery missions, spacecraft related. There space stuff behind me. And yeah, and then I also did unmanned ground robotic design, also where we were putting together robots, you know, where we basically took an ATV and took it apart and automated it and so could drive itself. So yeah.

Damon Pistulka  03:25

Wow. That’s, that’s crazy. Because I mean, when you think about the critical nature of anything in space, it just basically can’t fail, or there has to be something that just takes over a backup. That’s right, though. Some sort of redundancy. Yeah. Yeah. Cuz it’s the it’s not a good result of something.

Jennifer Herron  03:43

There’s nobody there to fix it. Yeah. Yeah. Yes.

Damon Pistulka  03:47

So the kind of stuff that you were working on, was it man? Is it mainly unmanned kind of stuff?

Jennifer Herron  03:54

Yeah, unmanned. And did I did have a stent with both Orion which is a was a capsule, kind of modeled off of the old Apollo system. And then also, I worked on Dream Chaser, which is a lifting body for people as well. So the manned activities are obviously more serious from a criticality standpoint than the unmanned, the unmanned. You know, we were able to work redundancy and, you know, eventually if it failed, you know, kill anybody. Yeah. Yeah. So a little bit less critical than then the manned missions, but obviously, we still do it today. So,

Damon Pistulka  04:42

yeah, so thinking about designing space equipment. Yeah. What was, what was something that you go I never thought about this.

Jennifer Herron  04:57

about something that I designed. Yeah, you

Damon Pistulka  04:59

just like I would have never thought that I had to consider that.

Jennifer Herron  05:04

Yeah, that’s a good point, um probably the cleanliness of things. So, very early in my career, I ended up working on the Stardust mission. And the Genesis mission, both of them had a substance in it called arrow gel. And arrow gel is this kind of like baked out silicon something. And it was I used to have some sitting in my desk. But it since like crumbled and dissolved by now, but it was a clear foam. And but it was super, super dense.

So we would we unfurled, we called it the waffle grid, because it just looks like a waffle, we unfurled that and stuck it in the tail of a comet. And then we collected the space test, and then we brought it back in to the capsule, sealed it all up, and then the positive back in the desert, for pickup and analysis.

So I think what was most interesting there is, you know, as the as the rookie engineer on that was, okay, we have to seal that system up, move it around the country, so that we can get Aero gel populated, had to have nitrogen purge and things like that. So I had to keep it really, really clean. To leave Earth so that we weren’t putting contaminants out into space, and then say, Oh, look, well, we got, you know, yeah. Did you know they’re bees in space? Yeah. You can’t, you can’t have little bees like in your, in your in your air gel. So probably the cleanliness factor was most interesting. And, and there were some complex problems to solve in that aspect.

Damon Pistulka  06:52

Yeah, yeah. No doubt. And I mean, when you see the pictures of like, when they’re doing a telescope, it’s crazy. Yeah. You know, the cleanroom environments they have to do. But that makes sense. If you’re going to collect samples from space, you don’t want to contaminate like you said, with with a bee or a fly or specks of dust or

Jennifer Herron  07:09

whatever. It’s really specks of dust. Right? The bees gonna be pretty obvious. Yeah, then see

Damon Pistulka  07:15

that? So take that out. Yeah. So when you were doing that, before we got on you were talking about the you know, you’re obviously helping people with model based enterprise work and helping people do that. You started designing in solid models from the beginning? Yeah, from

Jennifer Herron  07:35

the get go? Yeah. Yeah, I know, people complain now. Oh, you know, that college kids don’t learn how to draft and I said, I didn’t learn how to draft and this is my 25th anniversary of graduating from, you know, with my bachelor’s degree. So, okay. So you know, we always made a model, and then you put that model gets projected onto the drawing, and then you’d add your dimensions. And what we advocate now is that, instead of that step of creating that 2d static drawing, leave it in the model, add your geometric tolerances, with a solid datum reference frame your geometric tolerances, to define the engineering requirements, so that it all fits together when you get back.

But then that conveys the information to the manufacturer, that allows them the flexibility, they need to make the part however, they’re going to make it one of the one of the things we get is, oh, we can’t use geometric tolerancing. Because it’s too expensive to build. Well, I can put, I can put a big profile tolerance on that stuff and say build this within, you know, a 10th of an inch. That’s pretty big. It’s a lot of flexibility. Yeah, and your part. So that’s what we’re doing is defining the mathematics of the tolerances in the 3d data set, so you can view it and see it. And then also other machines can read that information and interpret it.

Damon Pistulka  09:05

Yeah. Wow. That’s amazing. That’s amazing. Because I lived in the old world, where you took the 3d model, if you had, yeah, and you make that and you get the 2d. And that’s how you do the, the actual measurements and everything else, because you’re either on the model itself, measuring features and writing a number down basic right? And doing it or creating the drawings from the mile. But you’re saying that the dimensional data actually resides in the model itself? And there’s no not at rate the drawings?

Jennifer Herron  09:38

That’s right, you got it. Yeah. And then, you know, if you scan it with a scanner, or if you use a CMM tool, or whatever your methods are for inspection. Then you could just compare those two pieces of digital data together. And then there’s great software tools that allow you to visualize how they’re out of spec. And, you know, if you’re an automotive supplier, for instance, you’re building hundreds and hundreds and hundreds of parts.

And, and, and probably more. And so you can see how your machine tools are operating that that OEE the operational equipment effectiveness and, and make sure you’re hitting the mark every time. So there’s a lot, there’s a lot of opportunity, once you digitize the data solidly with mathematics that you know, it has machine readable information. Yeah, to capture the engineering requirements, so you could do lots of things. And in the fabrication step, and lots of things at the inspection step.

Damon Pistulka  10:44

So backing up to when you are starting and working on the space systems where they already doing this kind of stuff it then in that in that realm, or was it? Was it really going into the drawings? Like you’re like you’re talking?

Jennifer Herron  10:56

Yeah, you know what they mean? It’s really funny, you say that, because just today, we I, I grew up here, and I grew up with my job, you know, in here in Colorado, and I have been in Colorado for guest this is going on my 26th year. And I, I said, you know, we used to go to machine shops locally here all the time, because we built funky, weird parts, and we built one or two of them. So I and I did a lot of research and development work also. So we were always kind of able to talk to the machinists directly, which is a great way to grow up as a designer.

And pretty much 100% of the time, I gave them a model to start with, for the most part, and then you know, it’s still at that time, there were no annotations, where you could add, you know, the tolerances and things like that. So it’s still have to provide a drawing, but we were always seeding it right off of a model. Yeah. And then I even had a machinist teach me how to take that model out of a dx f file and then CNC directly from it.

So in fact, that that little it’s a little mercury capsule back there. I designed that and then popped the, the DSF file into the CNC machine and then machined out the Lexan. I don’t know how long ago probably 21 years ago, so yeah, I’ve been doing this for a while. But but the software tools, a CAD software tools are way better. Yeah, you know, easier to use. They’re, they’re more robust, they really are creating a lot of digital connections that give us traceability through that whole cycle so that we can start eliminating manual data entry steps.

Damon Pistulka  12:46

Yeah. Well, that’s, that’s what I that’s what I think is so amazing. And because, you know, honestly, I haven’t been in a technical role on a manufacturing, it’s been 15 plus years. And, you know, in that timeframe, I knew how to use the whatever it was the salt, I can’t even remember what the name of it was the one that that the Katia Yeah, I know how to use Katia enough to be dangerous, right?

I could pull up the model and measure stuff off. That’s about all I could, yeah, yeah. And, and, you know, and now the systems that you see, even from then until now are so much easier. And the integration between systems is so much better. I mean, and you couldn’t, you couldn’t really go, you could, but it was not just a boom, boom, to go from there into my CMM, or my measurement system, whatever I’m doing right, and then just measure right off the model. That was, like, almost unheard of. And, you know, we were building stuff for the F 20. twos. And so you know, it was all model base. Sure, everything was modeled based on it. But it was clunky, clunky.

Jennifer Herron  14:01

Yeah, I think it you know, clunky is a good way to say it. And, and I appreciate that you bring it up that you know, it was worse than it is today, because there’s still a whole lot of whining about the tools. Of course, there probably will always be whining about the tools, I suppose. But it is definitely there’s been a lot that’s happened in the last 15 years to evolve the technology. There’s just a lot of players in the space that are working really hard to bring the value of digital data and keep it all traceable, and hopefully make it less clunky. I’m all for less clunky, that should definitely be the end game.

Damon Pistulka  14:42

Because looking at it from a business perspective. Yeah. If when you get everything working together, and it’s not like I’ve got to convert this into that and then there’s some you know, and you really get it so it’s integrated. It’s got to be really pretty incredible. Well, to see to see a system like that working together. Yeah, in a manufacturing system manufacturing setting. So let’s talk a little bit about you know, so you were doing the space, the space design, you’re working for Lockheed Martin and such. And then what prompted you to form

Jennifer Herron  15:21

do something different?

Damon Pistulka  15:22

Yeah, yeah. What? Why did you decide, oh, I need to go out and, and teach people about model based manufacturing and becoming a model based enterprise?

Jennifer Herron  15:31

Well, clearly, it’s because I’m totally obsessed, but and that that is somewhat true. Yeah, that’s Yeah, it is a given, I’ve come to realize, actually, just recently, I said, You know what, I think I might be addicted to efficiency. And that’s officially a really good thing. And my business is perhaps not such a good mental health thing, to always try to be efficient all the time. But I definitely addicted to efficiency, and I loved modeling things and making the models efficient. And on top of that, I had a couple of different jobs in different places, and we changed cad tools.

So I mean, I started out life at the very, very beginning using Yuji unigraphics. Yeah. Then I learned ideas master series, then I learned what was pro engineers now creo, PTC, then I learned SolidWorks, I’m trying to get this all in the right chronological order. And then I learned nx. So all the tools really are exactly the same, they just have a couple different button clicks. And they have a couple different variations, and you know, what they can support and what their quirks are.

Yeah, we know, a lot of their quirks. So from all those experiences, I was, you know, I just found patterns in the way I was working and every single CAD system. And so I thought, Okay, this is an opportunity for me to sit down and categorize this information. And, and then share it with others, because it was it was a body, you know, a text document, that that was missing.

I really do believe in standards and standard working procedures. And, you know, again, sort of my efficiency, addiction. Yeah. And so I was always trying to build instructions and tell other people how to do it. So then that’s, that’s when I sat down and wrote my reuse your CAD book. Yep. And that first edition, was published in 2013. And then, this year, we published a second edition. That includes some not all of the other learning that I had in the in the last seven years. So yeah, yeah,

Damon Pistulka  18:04

yeah. So let’s talk a little bit about your book. You wrote your Okay, so what, what, why, Yeah, why? What’s the book help people figure out?

Jennifer Herron  18:13

Well, yeah, so again, totally obsessed, and I could see patterns and I could see instructions that if people would model things in a certain way, then we would be able to consume it or reuse it or, you know, if you got hit by a bus and other designer would be able to pick it up and, and use it because it was built in a standardized kind of, you know, sensical way.

So the first release of the book really focused on CAD modeling, large assembly modeling how to create assemblies that could be used in parts lists that could, you know, the individual piece parts could be consumed in machine tools, and, but primarily, was all built for, for designers to say, hey, designer here, you know, I’m leaving, I’m leaving today, I’m gonna hand this off to you, you finished working on what I’m working on. So it was primarily built for that. But what we learned in the last seven years is that there’s eight years really is there is a lot of benefit to the downstream consumers. If they’ve got that 3d model already, then they’re a step ahead of the game.

And they’re not trying to misinterpret anything coming off the drawing. Because what’s on the drawing is just 3d projections. And then you got to like unfold it and unfurl it in your head to create a 3d model. So we discovered there’s a lots and lots of benefits to those consumers of that 3d data. But that, that we’d have to present it in perhaps a different way than we’re used to looking at it as engineer because engineers, because we’re engineers, and we’re addicted to efficiency, and we know, we know way too much math, you know, stuff like that.

Damon Pistulka  20:20

Agreed? Yep. I’ll just go agreed on that part. Because if, if you if you don’t know an engineer, yeah, just hang around one for a while. Yeah, so random details. Yeah, little Yeah. People that are around me understand that very well. And we’re always fixing things. That’s the other thing truly is like a get it’s broken. I can’t walk away from it. It’s

20:47

not for you. Yeah, exactly. That’s right.

Damon Pistulka  20:51

Yeah, oh, you go down that hole a long ways, because that’s a that’s an ugly thing to try to break. But, uh, so you’re, you’re doing this now. And you’re helping help people do this? So. So what are some of the enlightening things that people really see when they go, Okay, we’re going to, we’re going all in on the model based enterprise, we’re gonna do this. So when, when they start to do this, what are some of the things that you see that they really benefit from,

Jennifer Herron  21:24

um, there’s two really, really big categories. And then there’s lots of things that can be derived from those big categories. But say, the first one is about eliminating waste. There’s a lot of waste in, in how many people touch a particular product and the documentation today, and, and some of that, is because, you know, we needed that for the drawing based methodology.

You know, I mean, they used to draw ships by hand. And then they used to have another person come in, redraw the ship to make a copy. I think those were things that that was the state of the art of the technology at the time. So we’re looking at eliminating waste. And this kind of brings me to my second topic, which is, we really want to help out the employees of your company by taking the tedious stuff off their to do list.

If it’s stuff that’s just oh, I’m just clicking and clicking and clicking or I’m, you know, manually transcribing from here to here, there’s a lot of copy paste from spreadsheet, the spreadsheet kind of activities, if we can build in that digital traceability, where they can trust that the data is maintained pedigree, throughout the transitions, whatever, whatever those transitions may be, then those people that you have doing all this ridiculous, manual labor can really use their carbon based brains for what they were intended for, which is solving complex problems.

So that that in and of itself, there’s about 25, different capabilities that we’ve come up with, in the model based space that help to persist accurate, trusted data from design through fabrication through inspection. And then oftentimes, there’s a supplier loop, right? You have a big supply chain of, of data and information exchange and, and what we want to do is create feedback loops through all those four kind of typically siloed areas within the manufacturing space. And if we start creating feedback loops, then we start to be able to improve our product in a much better way.

Damon Pistulka  23:54

Yeah. So when you talk about those, the eliminating the waste? What are a couple examples of that, that you see that that people go, wow, this is really impacted our business?

Jennifer Herron  24:07

Yeah, this is several years ago now. But we ran a basic pilot with an engineering organization that handed their data off to supplier. And one of the great things about this particular project that we ran was that we were able to be intimately involved in all of the all of the steps on both sides. And the reason why I say that’s important is because a lot of times people just throw their information over the wall to the supplier and say you do you deal, deal with it. You don’t always get the result that you want.

When you do that, especially in these kind of transition activities where you’re trying to, like I gave you a drawing yesterday, today, I’m going to give you a model Good luck, you know. So what we learned in that process in that data exchange, you know, that the data went out from Designed to to the fabricator, and then they pulled data back in because they were pulling first article inspection reports and they wanted to see all that feedback loop in that data. And so there was like, you know, digital models on one side where they engineered and then on the supplier side, they always they took, they often took that model, kind of like a step file or something like that.

And, and then they started playing around with the model and building tooling. Sometimes they built in process models and things like that. So looking at kind of that workflow and diagramming it up, we found as many as 20 to zero, manual data re entry of data through that process. Oh, that’s 20. Yeah. 2020 brains manually reentering data. And one of the common pain points with where people live today, even if they’re using a model, like a step model is their step model geometry doesn’t actually match the drawing. And now we’re in to their everybody’s in a pickle, the engineering side and the supplier side, all in a pickle.

So, so we took that, that manual data exchange and reduced it. And, and in the geometry case, in the in the, in the case of where we’re just representing the geometry of the product itself. And actually, I’ve got a visual aid for those who are. So if I take the geometry of this product itself, and I transfer it from the engineer to the supplier, and I run a verification and validation report, you’ll hear them called, and you say, Oh, you gave this part to me, and are you design this part in Nx, I translated it and now I have it in SolidWorks, I’m gonna run a comparison report to compare nx and SolidWorks.

And make sure that my geometry that I get is still is still good geometry, and that it matches the source. And that’s a really important thing at a base level is just to verify that geometry. And then what we’ve completely done is eliminated any manual data entry error that could occur in that cycle. And that’s what that’s one, that’s one piece, it’s one piece of information that sits on your drawing today.

There’s, there’s geometry, and that’s this. There, the annotations, the dimensions, the tolerances, the notes, the flag call outs, the material identification, they’re attributes, that that’s often information like the part number, the description of the part, you know, bracket number three, that’s my favorite name, Jennifer’s bracket number three. And, and so we have all that information on the drawing today. And we pull that that good stuff that we have on the drawing, we pull that back into the model and represent it digitally. And then that information gets used and reused across that, that supply chain chasm, which often is a chasm.

Damon Pistulka  28:10

Yeah. Well, because a lot of that stuff in the past was not included with the model. It was only on the drawings was only on the drawings, right or in some other communicated some. Right. Right. So you’re saying that that, yeah, I can see where that’s, that’s quite an advantage, if that’s all included with the model itself, because it is, as you said, there’s one source, right.

Jennifer Herron  28:35

There’s one source for the truth. Now, I’ll give you a little tip, don’t think that’s all coming in one file. It may be multiple files aggregated together. And if you want it in a single file, then you’re not paying attention to the future look at Big Data. This is an aggregation of data that we’re layering on in different ways. And the key is to keep it all connected together. So you may or may not be able to get that all in a single file that you sent. So that that’s something that it’s just the tip.

Damon Pistulka  29:11

No, but it’s a it’s a good valid point is because you’re really talking about managing data, not necessarily files. That’s right. And date is a model data or specifications. And you said it’s a call outs is dimensions, whatever it is, yeah. And it whether they are in the data file itself are not really is inconsequential, as long as you know what the data set is. That’s right comes in is connected together. And if I design it like this, and the next step in the process can use it like that, and keep the data together. And the next step in the process can keep the data together. That to me would be one of the more important things that you’d want to try to do.

Jennifer Herron  29:56

That’s right. That’s right and the hard transition for people Is to transition from, you know, that piece of paper, it’s really handy because it keeps everything kind of in a box. Yeah, keeps all your data in a box. But it’s also very limiting, right, we can’t link to other data that we might want to also see.

We just in the last two weeks, ran some user feedback, studies on a piece of data. And one of the biggest pieces of feedback was, oh, I want a link, I want a link to all the other pieces of data. And we had published out a single file to view which is, this is the thing that it’s like a 3d PDF, you can view a single file, but it’s not integrated into all the rest of the data. Because we took it out of its product lifecycle management system, or its data, you know, cloud, if you will, of information. So keeping the connectivity of the data is really important, important. And I mean, there’s a whole bunch of technology around that. So

Damon Pistulka  31:00

yeah, yeah. So this is just, it’s amazing to me, my brain is rolling here, right? million different directions. We could go with this. Yeah. But as you look at this, what are the exciting things that you see, you go, Wow, if we just if we fix this challenge, we are going to we are really going to change the game with model, the model based enterprise?

Jennifer Herron  31:27

Yeah, well, I know I’ll kind of keep focusing in on the quality loop, because I have a lot of quality friends that are in digital metrology. I’m a board member of the digital metrology standards Consortium. And, and they have definitely educated me and the impacts of how quality professionals have to the amount of time they’re spending, evaluating a drawing, so that they can prepare a quality plan that accurately inspects parts, to ensure that they’re going to meet their form fit and function requirements.

So working on a webinar that we’re going to deliver next Tuesday, and we’re talking about a 50% time savings in duration, because because you’re eliminating some huge manual entry steps. So 50% time savings is pretty, pretty big. And, you know, I want to caution people that this is not about oh, well, I can lay off 50% of my workforce. No think about it is your throughput is going to increase by 50%.

Damon Pistulka  32:49

So so you’re talking about quality, the quality, the throughput in a quality department. Yes, is. And I’m not talking about, you know, first already call getting something set up in the beginning, but you’re talking about as we go along, and production basis.

Jennifer Herron  33:08

Yeah, as you go along on a production basis, as you make changes to your parts, you’re so much better informed about how your parts were operating before because of this data, you’re aggregating and collecting and, and continuously feedback. I mean, it was a huge deal to me, because even when I built all this spacecraft stuff that did go to space and did work, so we’ll take that, but yeah, you know, I just throw it over the fence. And they made the part. I had no idea.

I had no idea if they were meeting the tolerance, positional tolerance to this whole that had painstakingly done all this ridiculous fastener, you know, tolerance stack up to make sure I had the right fastener size and all this kind of crap, right? Like, no feedback whatsoever. So I have no idea if I made a super expensive part, because I had too tight of tolerances. Because I didn’t really know how the part got made. Yeah. And so I that feedback loop to me from the inspector, is just it’s mind blowing.

I mean, I remember going, huh, what do you mean? What do you mean, you didn’t make that within 20,000? That’s the only way it’ll go together. You know, and I just, I think the feedback loops are really, really important. And there’s so much opportunity to leverage once you get the data authored digitally, in a standardized, repeatable mathematical way. And that’s, it’s harder than it seems to do that and have that, that back to you know, why did I write the book? Well, that’s why I wrote the book, and then I, you know, added some more learning on it.

Damon Pistulka  34:42

Yeah, that’s, I said, I’m sitting here thinking about this, you know, and when you need the book, because you want to start everybody designing the same way because yeah, if I’m going to communicate to three steps down the road, Yeah, and Damon designs differently than Jennifer does, then then Sue, then Dan. Yeah, I mean, that just blows everything out of the water that you wanted to do with sharing the data across all the places because they have to adjust to each person designing?

Jennifer Herron  35:18

Yep. Well, you know, if you have bad data, you’re gonna get bad results. So yeah, so you got to author good data? Yeah.

Damon Pistulka  35:27

Yeah, author good data. I’m gonna write that.

Jennifer Herron  35:31

That’s my, that’s my Texas grammar coming out?

Damon Pistulka  35:36

Well, it’s, it’s critical. I mean, when we talk about this, and we, we talk about the, the, the efficiencies, and we talk about things like, what you really gain from designing consistently. And we look at look to the future. I mean, the future is not us walking around in manufacturing with a bunch of paper drawings and measuring junk with calipers I mean, it’s, it’s not touching, it’s, it’s in the machines measuring, you know, all different kinds of things that are going to happen that that are well beyond this and out your, I think, anyway, you’re really doing is helping to lay the foundation for that? Well, yeah, with the with a book and getting people designing consistently. And

Jennifer Herron  36:24

and even though you do this for like, really complex geometry parts, where it really makes sense, because drawings are totally inadequate for complex geometry parts, even airfoils. I’m just like, really, this, we’re documenting this thing and 2d, really. So when you’ve got really, really complex parts, and geometry, this totally makes sense. Because your drawings are absolutely flawed. from the get go, I can guarantee if you give me a drawing today of a complex part, I will find something wrong with the drawing or misinterpret something, which is what’s really going on.

So but it doesn’t mean that if you have some washers that you do want to do a little spot checks with calipers, and get yourself submitted to digital calipers and just measure them right along and it’ll pop it into a spreadsheet for you. That’s still okay. Don’t change that business. Because there’s not a lot of value add with a lot of complex, you know, systems for a washer that has like, three things you’re gonna check. Right? You got an ID od thickness, right? Okay. You don’t change your business for that. And I just recently said, Well, I had had an executive say, Well, how are we going to? How are we going to deal with the data?

You know, if we still have these manual processes, I said, let’s just keep doing business the way you’re doing? No. Because that works, right? Yeah. So don’t change that part. And that’s the other thing, you don’t have to do a complete overhaul, you can really focus in on your complex systems. And build that digital traceability through there. And then, you know, once you’ve got that figured out, you know, some of the smaller piece parts shakeout and make sense.

Damon Pistulka  38:18

Yeah, so where do you see what industries? Do you really see? Are there any segments that you see that’s really coming in? Or, you know, I’ll ask some follow up questions. But

Jennifer Herron  38:32

yeah, this is always a hard one for me. Because it’s really all industries can benefit from this, because they make parts, you know, if you make a widget that is in three dimensions, you can pretty much value, you know, gain value from this. And they’re, you know, even if, if you’re building like a fabric like a cover for a car seat, or something to that effect, there’s still value to having some 3d data that is established and then reused. And then you know, you have to flat pattern it and stuff like that. And same thing goes for sheet metal, right?

Yeah, you’ve got sheet metal parts, that you flat pattern, well, the CAD tools are great at building sheet metal parts, and then flattening them out for you. And then you just go bang them out in the plasma cutter, you know, that’s, that’s, that’s a five value. So, so certain, I would say fabrication methods have advantage over some others. The most obvious if you 3d print anything, you must have a model. This is one of my favorite quotes from my friend Curtis Brown. You know, he’s like the, the, if you’re 3d printing, you have to document it in 3d. There is no other way. Right? Because you’ve got to feed that model into the 3d printer.

So, so that right off the bat, anyone who’s doing anything with a 3d printer, there’s value I think all industries now have 3d printers. I mean, I got one in my basement. So yeah. But we do see this in the high criticality industries. So as you pointed out, spacecraft got to work got a, you know, got to fit, that kind of thing. Automotive there, they’re looking at this so that they can increase their throughput because cost is such a big deal. Bottom line. So there’s another industry, medical is using it medical devices, I’ll say is using it.

Obviously, also, they’re doing all sorts of interesting things with materials and 3d printing. And I mean, so there’s so much value. Is it all? Do we hit geometry annotations, attributes, presentation states and the product structure in every single data set? And every single industry? Probably not. But people are finding value for geometry, I mean, that that’s kind of an easy one, right? My geometry should always be leveraged throughout the whole lifecycle of the part no matter what. So we do see a lot of this heavy in the aerospace and defense primarily because the criticality and the fact that they do have money to spend on first article inspection processes.

Damon Pistulka  41:19

Yeah, and when you have very high dollar components that you’re looking at the investment in just in some of it, especially if you’re trying to catch something, then do some more processes and a lot, a lot of times you get a lot of processes after that. So you take a pretty expensive alloy, you cast it, and then and then you have an expensive, more expensive piece of alloy that then gets machined and then get multiple processes after it and add more fabrication and whatever else. And you know, you can have one component that’s hundreds of 1000s of dollars. And you definitely that first article and the at each point, you’re in process kind of stuff, too. Is critical. Right? Absolutely.

Yeah. It’s so interesting that to listen to you talk about this, because the uses are mind boggling. Why don’t even know what they all are yet. Right? Yeah. Right? Well, that’s the kind of thing cuz you’re like, you’re like, I don’t I don’t know, the right metaphor for it. But you’re like standing at this big open field. And you’re like, what direction? Can we go? Yeah, because all the directions. Yeah, that makes sense. Some are more obvious than the others. But there’s so many ways. And I’m sure that you uncovered new reasons, new benefits, new things that that you go, Wow, this really will make a difference in this application.

Jennifer Herron  42:51

Yeah. And it’s a constant conversation about what the little benefits are. You know, it’s, it is there’s a lot of opportunity out there. Yeah. And my job is to help people get their data, digital, machine readable in without limiting. So that sort of that future opportunity that we don’t know about? So I do. I do have a crystal ball here. So I use this occasionally, because sometimes I don’t

Damon Pistulka  43:26

know. Yeah, there you go. I don’t yet know people ask me stuff. I’ll just look at my Chris. Hey, girl.

Jennifer Herron  43:34

Hey. I’ll send you a link.

Damon Pistulka  43:38

That’s awesome. Yeah. Great, Jennifer. Well, you know, this. So you, let’s, let’s just talk a little bit about how you’re typically helping companies, you know, a little more specific about when action engineering goes in, and you’re helping these companies what are you typically doing with them?

Jennifer Herron  43:58

Well, our goal is to get people to create and then use and then reuse, and automate their 3d CAD data. And we’re specifically doing that in that design, fabrication inspection space. So from engineering, you know, to supplier for original designer to supplier in many cases. But we’re trying to do that in a way where we are trusting the data as it moves from left to write in its lifecycle. And so, some of the things we do are at the very beginning, we just help them kick off and build an executive pitch, like, you know, what is this?

What are the benefits around this? And we have social scientists and organizational change management people that that come in, and work with companies to help them see what The benefits are for their company. And then we marry that with our technical expertise around CAD systems, and what it means to author model based definition data. So we oftentimes build a proof of concept for them. So we go, Okay, give me your drawings. And we get a drawing, and we convert that into model based definition. And then we show them the kinds of things you can do with it.

So because that’s kind of the hard part, if you get into this space, you’re going to spend about two years Dorking around with learning the technology and, and stuff like that. And we think you should be able to do that faster. So we like to bring our expertise, we kind of kickstart that for you. And then we move you into, Okay, now let’s be very specific about your downstream activities.

We want those consumers to adopt what you’re going to author. So let’s make sure we understand who’s taking the next step after lease engineering, because engineers are easy, I mean, we can convince them of this all day long, because, you know, they can already sort of see the future, you know, based on their training that they’ve had. So, but if you take it on, into a shop floor, there’s a little bit more hesitancy around this 3d data. And what does it mean?

Yeah, so. So we call that our consumer adoption strategy, then we do a kickoff workshop and build a team. And then we’re, they’re kind of like, coaches, like, track coaches, just to make sure you, you know, you’re, you’re up on your sprint game or up in your long, you know, your long haul runs, and there to keep you on track with figuring out pilots and stuff like that?

Damon Pistulka  46:48

Well, it’s it is a because, because now I’m sitting here thinking about it, as you’re talking about it, we’re talking about a change that affects the heart of a lot of operations. Yeah. You know, in manufacturing, about component data, whether it’s drawings, whether it’s, you know, scratch it on a yellow pad, you know, that that data around the components and the assembly and everything that they build, there’s the heart of there.

So you’re really teaching them how to change their thinking their practices around that. And it does take not just laying it out, like you said in the first phase, but then you have to show them, and then probably prove that it works through the process for them, to help them do that. And then in the end, it is, as you said, coaching and helping over the long term to ensure that it doesn’t just go back to Oh, well, it’s not working so great here. So we’re going to go back to this.

Yeah. And pretty soon that the workarounds are as big as the you know, as the system was, before you started, if you don’t really get the habits in green to go, this is how it needs to be done. If we need to change it has to stay along these kind of lines, so that we can use the data all the way through. Right? Wow. Yeah.

I have learned a ton. I tell you what, I just I hope that if people listening are, as in golf and golf than this has this is, you know, coming from a business that I said we had to use model based design information to program to do other things. But we really didn’t use this, you know, there are so many pieces of paper that were associated with that it was, you know, I can’t, I can’t and like I said, you had to get you had to get enough dangerous to pull that paper kind of information off the models, because you couldn’t really just use the models.

Jennifer Herron  48:51

Right. And I think this allows us an opportunity to simplify some of that complexity that has kind of blossomed out of a drawing based culture. Yeah. And that’s a little tricky to kind of put that back in the box, if you will. But sometimes with all that drawing based processes that we had to establish, because the technology was Where was that? We’re not really sure why we’re doing all that stuff. So we end up doing a lot of current, you know, current process mapping, and then future process mapping, so that you can see the difference and see where the simplification can occur.

Damon Pistulka  49:28

Yeah, yeah. Wow. It’s so cool. It’s so cool.

Jennifer Herron  49:32

It’s not boring. No, no, it’s constant challenges all the time, both people and technology. So yeah,

Damon Pistulka  49:38

it is it is the kind of fun problem to solve. Yeah, yeah. No doubt, no doubt. Yep. Well, Jennifer, thanks so much for being here today. I just I guess appreciate the they were able to stop by and share this with us. And if people want to get ahold of you, go to the what’s the best way go to the action engineering website. Reach out. on LinkedIn, what are some of the places?

Jennifer Herron  50:02

LinkedIn is a great place to find me? I’m Jennifer Heron. He are Oh, in Golden Colorado, I probably is when it comes up as Yeah. And it’s action hyphen, engineering Comm. And there’s a, there’s a Contact Us form and you can get ahold of us there.

Damon Pistulka  50:20

Awesome. Awesome. Well, thanks so much for being here today, Jennifer, and thank you everyone for listening again, questions. Oh, again, I was just a pleasure. It was a pleasure I am so I’m so I feel so fortunate that we were able to do this. So I don’t even know what I was going to say. Other than Thank you.

You’re welcome. And we will be back again on Thursday with another show with some more interesting people talking about business and manufacturing and not I don’t know they’re going to watch a lot to live up to after the enterprise discussion day because it’s an it’s, it’s really intriguing to me and I love that love the subject. So thanks so much for sharing today. Welcome. And we will be back again. Thanks, everyone for joining us.