NPC Downloads & Brochures

WEBVTT

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Hi everyone, and welcome.

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Thanks for joining us for this informal,
but what we hope you'll find is

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informative webinar on industrial CT
scanning.

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I'm Victoria Rusman,
Creative Marketing Manager and now

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Pretech.

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I'm joined today by three talented minds
from our team.

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First off, we have Dave Nelson,
owner of NEL Pretech.

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He started this company over 30 years ago
before CT scanning was cool.

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We also have Mike Heim, Director of CT.

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He is an encyclopedia of knowledge when
it comes to X-rays and material behavior.

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And then we have Carter Aldridge,
CT specialist,

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who I'm pretty sure love solving complex
challenges using CT scanning.

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One note before we begin,
if any questions come up throughout the

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webinar,
go ahead and drop those in the chat.

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We'll hang on to them and we will answer
all of them during the Q&A at the end.

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With that said,
let's get into it and explore CT scanning.

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Dave, you're up.

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Hey again, thank you, Victoria.

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And my name is Dave Nelson,
owner and President Nel Pretix since 1993.

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I'd like to thank everyone here for
joining us for our very first webinar on

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3D scanning with a focus on CT scanning.

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It's a nice alternative to our lunch and
learn format.

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So if that's something that interests you,
that's a an event where we can come out,

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provide lunch,
and deep dive into some of these topics.

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Also, since this is introductory,
if anyone wants to deep dive into the

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topics,
we will take questions at the end of

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course,
and we can also visit with folks offline

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as well.

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So we've got an agenda today that
introduces that introduces our company,

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talks about what is CT scanning and how
it works and deals with some of the very

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important topics that'll help you engage
us for better outcomes, right resolutions,

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accuracy and some of the deliverables
that we offer.

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Everything that you're going to hear
today is geared at improving throughput.

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So kind of keep that in the back of your
mind as we introduce some of the various

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topics.

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The whole idea is to get your product to
market faster, recognize issues faster,

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solve problems faster and that has
brought us a few case studies.

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Unfortunately due to the NDA nature of
our arrangements with clients,

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we can't actually put product up here and
talk about specific issues with our

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customer.

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But we have two case studies that were
pretty dramatic in.

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In one,
we were able to reduce the timeline of

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from initial,
initial development to launch by about

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seven months.

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And we brought CT scanning to bear on
that project.

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And what it allowed us to do was
visualize the initial condition of the

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the mold, the tool,
the part and then start developing

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measurement routines in the backgrounds
while the customer without solving

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problems and and you know,
making adjustments to the molds in the

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process.

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And so by the time they were ready to
launch their product,

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we had all that measurement in place and
that executed in a matter of minutes and

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that resulted in in an enormous time
saving and got their product to market.

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I was told in the in the area of about
$60 million that they were able to

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accelerate.

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We had a major medical OEM come to us
with 20 different tools being managed by

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one person and we ended up launching that
in about 16-18 weeks, 20 weeks.

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And you know,
ended up saving that company millions of

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dollars in the process.

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And as a result,
they went ahead and integrated the CT

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scan process into every area of the
organization, R&D, quality,

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various engineers.

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So let me move right on and just kind of
introduce who we are before we get into

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CT scanning.

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So we are, I talk about my people,
my process and my platform when I

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introduce ourselves.

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So we are coming from a metrology
background since 1993.

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That's how we grew up.

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So we have years and years of metrology
experience.

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Everybody that we hired for since the
beginning has engineering backgrounds,

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engineering degrees and our CT group
comes from physics background with

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advanced degrees in physics as well as
engineering.

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And we have a variety of software
expertise from, you know,

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CAD software to measurement software to
reverse engineering software and so forth.

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And So what does that mean for you guys
that are going to engage you?

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So it means you're going to have this
high level collaboration.

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And I say collaboration because my
customers are bringing their expertise to

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the table.

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We're bringing ours and we're discussing
project details,

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problems and possible outcomes.

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And it's just builds a lot more
confidence, you know, in the outcome.

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So we're trying to solve problems
together.

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That's what that's what that is.

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So process we're creditized.

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So IC17-O25,
and I know there's a lot to that,

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but I generally highlight three different
things that have been transformative in

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the process of getting a credit.

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We have to define our measurement
uncertainty.

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It's something we define,
we test for and we publish and we need to

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have low enough measurement uncertainties
to to handle some of the precise

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tolerances that customers bring to us.

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Contract review.

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It's real simple.

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We go through,
it's a box we check and we review every

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aspect of your project to make sure that
we have the capacity and the capabilities

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and the technical know how to deliver
what it is that you're asking us to

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deliver, right.

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So that's important because we don't want
to have you go through the trouble of

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issuing purchase orders and,
and sending us parts and then finding out

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later that there's, there's,
there's some kind of shortcoming.

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Final inspection is real important.

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In the early days of our company, we had,
we're producing test reports that were

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laden with errors from time to time,
right?

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So that's just the nature of dealing with
the mass quantity of data.

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And we've really cleaned that up by
making sure that every test report that

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goes out is signed not just by the person
who did it,

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but it's been fully reviewed by a second
person.

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And that eliminates everything from
simple typos that might cause an,

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an aggravation at some point in the
process to identifying inconsistencies in

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the data that warrants some kind of
recheck.

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So those three things have been very
transformative to us.

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And again,
what that means to you is that you're

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going to,
you're going to have a better assurance

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of accuracy.

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You're going to have more reliable
results,

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you're going to have more confidence in
the data.

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And that's not to say we don't make
mistakes.

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We are humans.

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We still make mistakes.

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It's just that we have a,
a mature process in place that mitigates

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a lot of that risk.

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Then we talk about our platforms now,
which it's starting to get interesting

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now, right.

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So we have traditional measurement
platforms like CMM and vision systems,

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but we also use structured light or blue
light.

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That's a technology that digitizes a part
in all its surfaces,

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but it is limited by line of sight.

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So it's not going to be able to get
necessarily down into deep recesses.

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There could be reflectivity issues and
but the the uncertainties are,

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are comparable to other scan technologies
and you know for the right applications

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can be cheaper and more accurate.

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Computed tomography CT scanning is what
we're really talking about today.

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And this is an X-ray based technology
that scans your part,

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creates a digital representation of that,
but has the advantage of not being

1696136f-7f81-4d48-ad13-c8f4ebace18e-2
00:08:36.047 --> 00:08:37.640
limited by line of sight.

dad537d4-4d77-4e80-9156-8bd4f39ca23a-0
00:08:38.160 --> 00:08:41.520
So we can see internal to the material.

04706bd5-cdfd-47c3-bead-5dee642b7bad-0
00:08:41.520 --> 00:08:45.440
We can see assembly engagements,
things that are hidden from the eye.

bf04fccc-d8d9-4e59-9285-1e6f19b9a2c9-0
00:08:45.920 --> 00:08:53.185
And we can perform a whole host of post
scan services which include basic

bf04fccc-d8d9-4e59-9285-1e6f19b9a2c9-1
00:08:53.185 --> 00:08:57.800
metrology, material analysis,
defect porosity.

7495e053-8470-4e3b-9f2e-89d2f09fcebc-0
00:08:58.040 --> 00:09:06.260
We can overlay the digitized version of
your part onto another part or to CAD

7495e053-8470-4e3b-9f2e-89d2f09fcebc-1
00:09:06.260 --> 00:09:14.796
model and get a visual idea of how your
part is performing or how close it is to

7495e053-8470-4e3b-9f2e-89d2f09fcebc-2
00:09:14.796 --> 00:09:15.640
nominal.

86e7cd61-bdde-49aa-bbb7-f7caff610ed4-0
00:09:16.960 --> 00:09:24.060
And so the benefits to you in acquiring
full digitized scan data is that you're

86e7cd61-bdde-49aa-bbb7-f7caff610ed4-1
00:09:24.060 --> 00:09:29.118
going to be able to visualize the
condition of the part,

86e7cd61-bdde-49aa-bbb7-f7caff610ed4-2
00:09:29.118 --> 00:09:34.000
you're going to be able to make decisions
much faster.

c9815926-9b95-4ad7-ab70-cd9ebfa28058-0
00:09:34.160 --> 00:09:37.483
That information can be disseminated out
to everyone in the organization,

c9815926-9b95-4ad7-ab70-cd9ebfa28058-1
00:09:37.483 --> 00:09:40.716
so they can all be looking at it
concurrently from their from their own

c9815926-9b95-4ad7-ab70-cd9ebfa28058-2
00:09:40.716 --> 00:09:41.480
job perspectives.

bc6f8cd9-7e10-484d-a15d-cd6f61ecb820-0
00:09:41.960 --> 00:09:46.040
That's a huge advantage in the digital
world.

9d470f9c-2e5c-4961-9035-c03362fe0c2b-0
00:09:46.080 --> 00:09:50.440
We can take measurements on the fly,
We can make changes on the fly.

31a02b1e-ea6a-49fb-8200-81e240c2e8c0-0
00:09:51.160 --> 00:09:52.920
It executes much faster.

550cf041-563a-4837-a258-8ba2363ae3f6-0
00:09:53.240 --> 00:09:58.223
Any measurement routine that we have will
typically execute in seconds,

550cf041-563a-4837-a258-8ba2363ae3f6-1
00:09:58.223 --> 00:10:01.892
not hours or,
or days like a traditional measurement

550cf041-563a-4837-a258-8ba2363ae3f6-2
00:10:01.892 --> 00:10:03.000
equipment would.

9b838492-b89f-4b2d-a155-fac6f93b8365-0
00:10:05.120 --> 00:10:07.560
So now we get into the fun part.

f12232e3-8a90-4078-a560-91c78ad70b67-0
00:10:07.600 --> 00:10:11.335
So I'm going to turn it over at this
point to Carter Aldridge,

f12232e3-8a90-4078-a560-91c78ad70b67-1
00:10:11.335 --> 00:10:14.240
who's going to introduce the CT
technology soon.

2efd8f7e-90ca-4d5e-8ac7-af861ba85ae6-0
00:10:15.040 --> 00:10:17.662
Like Dave said,
my name is Carter Aldridge and I'm going

2efd8f7e-90ca-4d5e-8ac7-af861ba85ae6-1
00:10:17.662 --> 00:10:20.699
to be your guide on the,
the science portion of this this webinar

2efd8f7e-90ca-4d5e-8ac7-af861ba85ae6-2
00:10:20.699 --> 00:10:21.160
right now.

f23e14e5-9593-405e-8ab5-744a72ea97ee-0
00:10:21.160 --> 00:10:25.920
So, you know, computer tomography or CT,
it's been used in the medical industry

f23e14e5-9593-405e-8ab5-744a72ea97ee-1
00:10:25.920 --> 00:10:30.382
for decades at this point and it's
starting to come over to the industrial

f23e14e5-9593-405e-8ab5-744a72ea97ee-2
00:10:30.382 --> 00:10:30.680
side.

29732739-1cdb-40c5-936f-2469f4f6fdd9-0
00:10:30.960 --> 00:10:31.960
And you know what it is?

93911568-8766-46b2-8fd1-ab699e5e5a4c-0
00:10:31.960 --> 00:10:33.600
It's an X-ray based technology.

72ecc8b3-f42c-4e68-a7d6-7c1cc18c56df-0
00:10:34.320 --> 00:10:38.094
And the kind of the key thing is it's
going to be non destructive as well as

72ecc8b3-f42c-4e68-a7d6-7c1cc18c56df-1
00:10:38.094 --> 00:10:41.280
providing full 3D images of both internal
and external features.

83b889a5-3e12-4077-afa6-7e3325127ce3-0
00:10:42.320 --> 00:10:43.960
And what do we use it for?

e55cc85a-d14c-40c6-bbed-60f55e7ba58a-0
00:10:43.960 --> 00:10:46.240
We can use it for pretty much anything.

3719c272-a518-4416-87ec-ef6f16b38b4d-0
00:10:46.320 --> 00:10:49.248
That's kind of the,
the really unique advantage of this this

3719c272-a518-4416-87ec-ef6f16b38b4d-1
00:10:49.248 --> 00:10:52.800
technology is that if there's an
application you think it could be useful

3719c272-a518-4416-87ec-ef6f16b38b4d-2
00:10:52.800 --> 00:10:55.056
for,
it probably can or we'll find a way to do

3719c272-a518-4416-87ec-ef6f16b38b4d-3
00:10:55.056 --> 00:10:55.200
it.

bc4790b4-3d96-48e6-8196-1ef30dd0316f-0
00:10:56.680 --> 00:10:59.400
But how it actually works is in most
machines,

bc4790b4-3d96-48e6-8196-1ef30dd0316f-1
00:10:59.400 --> 00:11:01.600
this is going to be the typical setup.

3535251a-2f82-4eae-b6d0-1ee2cc0e1e8d-0
00:11:01.600 --> 00:11:03.560
There's going to be some sort of X-ray
source.

6df61b77-b470-42fb-b166-578931f830ed-0
00:11:03.840 --> 00:11:06.920
That source is going to emit a cone
shaped beam of X-rays.

d00f75d3-33c1-43f5-91d3-d05f8867b963-0
00:11:07.200 --> 00:11:12.011
They're going to pass through whatever
the object that's being inspected is,

d00f75d3-33c1-43f5-91d3-d05f8867b963-1
00:11:12.011 --> 00:11:16.948
and then they're going to land on a flat
panel detector and that part is gonna

d00f75d3-33c1-43f5-91d3-d05f8867b963-2
00:11:16.948 --> 00:11:20.760
rotate 360° while the detector captures
thousands of images.

e716ee77-78cf-4749-ac2d-569d1e89269e-0
00:11:20.760 --> 00:11:22.957
You know,
just like if you've ever broken a bone

e716ee77-78cf-4749-ac2d-569d1e89269e-1
00:11:22.957 --> 00:11:25.962
and had to get an X-ray,
it's capturing thousands and thousands of

e716ee77-78cf-4749-ac2d-569d1e89269e-2
00:11:25.962 --> 00:11:26.680
those 2D X-rays.

2030da9d-2103-4c8a-85d9-e5da33ae11ab-0
00:11:27.160 --> 00:11:31.825
And the software that can then go back
and kind of compile all that into a full

2030da9d-2103-4c8a-85d9-e5da33ae11ab-1
00:11:31.825 --> 00:11:34.799
3D volume,
how we can achieve a greater resolution

2030da9d-2103-4c8a-85d9-e5da33ae11ab-2
00:11:34.799 --> 00:11:39.232
through magnification is by moving that
object either further away from the

2030da9d-2103-4c8a-85d9-e5da33ae11ab-3
00:11:39.232 --> 00:11:41.040
source or closer to the source.

0e9c2950-4303-4a51-987d-a1e770386644-0
00:11:41.600 --> 00:11:43.540
You can kind of think of it as if,
you know, as a kid,

0e9c2950-4303-4a51-987d-a1e770386644-1
00:11:43.540 --> 00:11:46.186
you're at the movie theater and you
wanted to put your hand up in front of

0e9c2950-4303-4a51-987d-a1e770386644-2
00:11:46.186 --> 00:11:46.680
the projector.

c8b759f6-0b8e-4a14-a7f9-9eecb3b76d6c-0
00:11:46.880 --> 00:11:49.440
You know,
your hand's only several inches long.

9e89d375-90af-483a-a81e-fe0a6fa78ae6-0
00:11:49.440 --> 00:11:53.111
But if you put it in front of that
projector really close, it's going to be,

9e89d375-90af-483a-a81e-fe0a6fa78ae6-1
00:11:53.111 --> 00:11:57.021
you know, 20 feet on that big, you know,
movie screen at the end of the the movie

9e89d375-90af-483a-a81e-fe0a6fa78ae6-2
00:11:57.021 --> 00:11:57.880
theater you're at.

4101b3ee-840a-49d6-92b1-32b48faca07c-0
00:12:00.240 --> 00:12:02.889
But you know,
resolution is obviously going to be a

4101b3ee-840a-49d6-92b1-32b48faca07c-1
00:12:02.889 --> 00:12:03.960
very important thing.

325af350-996f-4880-9b5f-35568253f8ff-0
00:12:03.960 --> 00:12:07.240
It's going to determine the smallest
feature that you can see on the part.

37cd121a-6ccf-4d86-943e-f723d793f366-0
00:12:07.880 --> 00:12:11.593
And where we start to see this fall apart
first is going to be on very small

37cd121a-6ccf-4d86-943e-f723d793f366-1
00:12:11.593 --> 00:12:13.040
features and very small radii.

360fb5af-2532-4dcc-9454-1def22a34e9c-0
00:12:13.520 --> 00:12:15.562
So as you can see in the bottom right
there,

360fb5af-2532-4dcc-9454-1def22a34e9c-1
00:12:15.562 --> 00:12:19.102
we have a nominal CAD image of this part
and it's kind of got this, you know,

360fb5af-2532-4dcc-9454-1def22a34e9c-2
00:12:19.102 --> 00:12:20.600
perfect cubic grid pattern on it.

835f6cea-e51f-4e1f-83f7-3abed746f1ad-0
00:12:21.120 --> 00:12:23.240
But in the image above that is the CT
data.

6881fa3a-7806-4a1a-9e8e-3d57c8b0822c-0
00:12:23.240 --> 00:12:26.554
And you can see that if we kind of lower
that resolution,

6881fa3a-7806-4a1a-9e8e-3d57c8b0822c-1
00:12:26.554 --> 00:12:29.240
those sharp edges start to become rounded
off.

2c824c9c-7aa6-45f6-b1db-1c8d89dbc0b5-0
00:12:29.280 --> 00:12:34.040
And that's simply just because we're not
picking up enough data points or voxels.

c7700131-58cf-4fc4-987e-503e4f8477ee-0
00:12:34.040 --> 00:12:37.800
You can think of them as as 3D pixels
that the machine captures.

11cf2b64-10c6-466d-8c87-298c00932617-0
00:12:39.160 --> 00:12:43.409
And we can counteract that by increasing
the resolution by, like I said,

11cf2b64-10c6-466d-8c87-298c00932617-1
00:12:43.409 --> 00:12:45.680
moving that part closer to the emitter.

b5801de8-020a-4a38-8869-f65fc757289a-0
00:12:45.680 --> 00:12:48.960
So that's casting a bigger shadow,
if you will, on the detector.

50e21edd-3711-44f4-8358-5e4ec08c671a-0
00:12:49.560 --> 00:12:52.720
But by moving it closer,
we're going to be narrowing our field of

50e21edd-3711-44f4-8358-5e4ec08c671a-1
00:12:52.720 --> 00:12:52.960
view.

46c12495-eb4a-4c3f-aa11-684cbb209f58-0
00:12:52.960 --> 00:12:57.062
So we're going to be able to pick up less
of an entire part, you know,

46c12495-eb4a-4c3f-aa11-684cbb209f58-1
00:12:57.062 --> 00:13:01.337
So we might have to just look at a
certain area of interest or balance it

46c12495-eb4a-4c3f-aa11-684cbb209f58-2
00:13:01.337 --> 00:13:04.631
out with, you know,
maybe a little bit lower resolution,

46c12495-eb4a-4c3f-aa11-684cbb209f58-3
00:13:04.631 --> 00:13:09.253
but then we can capture the whole part in,
in a single scan and kind of to help

46c12495-eb4a-4c3f-aa11-684cbb209f58-4
00:13:09.253 --> 00:13:10.120
visualize this.

21fc4e81-47ff-4550-a184-c0d337e892ed-0
00:13:10.600 --> 00:13:13.840
That flat panel detector, like I said,
has a, is a set grid on it.

a1e805ee-e6fe-4143-8561-c4fc838df17d-0
00:13:13.880 --> 00:13:15.880
You know, it's got a set pixel grid on it.

37f69ef1-9533-4f2c-9d55-d743bc95b056-0
00:13:16.360 --> 00:13:19.900
And so in the left image, you know,
we can get high magnification by taking

37f69ef1-9533-4f2c-9d55-d743bc95b056-1
00:13:19.900 --> 00:13:20.320
our logo.

66779b82-188f-436d-b4ea-923885b2638e-0
00:13:20.320 --> 00:13:24.157
We're putting it very close to the
emitter so that we're getting a big

66779b82-188f-436d-b4ea-923885b2638e-1
00:13:24.157 --> 00:13:25.400
shadow on the detector.

3a1325ba-b8fa-4267-9656-1dadb84eebe4-0
00:13:25.720 --> 00:13:30.003
All of the data of the logo is being
spread out among lots and lots and lots

3a1325ba-b8fa-4267-9656-1dadb84eebe4-1
00:13:30.003 --> 00:13:30.560
of pixels.

3331d8f5-5f4e-4cd5-9873-17e023a9ab45-0
00:13:30.800 --> 00:13:33.588
It's going to be very, very,
very crisp when it comes to the data

3331d8f5-5f4e-4cd5-9873-17e023a9ab45-1
00:13:33.588 --> 00:13:34.560
that's being collected.

8e94b022-51c2-48c2-83c3-935d2cdeaadb-0
00:13:35.160 --> 00:13:38.425
But conversely, in that right image,
the low magnification one,

8e94b022-51c2-48c2-83c3-935d2cdeaadb-1
00:13:38.425 --> 00:13:40.160
we've moved the logo further away.

3f2ef2df-da34-4d8e-bb69-fd09d6b2e54d-0
00:13:40.160 --> 00:13:41.640
We can now see the entire logo.

a06a36da-19ce-42e4-90fd-194069f3dd78-0
00:13:41.640 --> 00:13:45.831
Nothing's cut off or cropped or anything,
but instead of being essentially spread

a06a36da-19ce-42e4-90fd-194069f3dd78-1
00:13:45.831 --> 00:13:49.153
across the whole grid,
now we're only on about looks like, what,

a06a36da-19ce-42e4-90fd-194069f3dd78-2
00:13:49.153 --> 00:13:49.920
8 pixels there.

3e4f4cdc-ae17-4e8d-bdec-a334b90312b0-0
00:13:50.080 --> 00:13:54.200
So we're going to be picking up a lot
less crisp data from that scan.

ecbe9363-5870-4b85-aa2d-2f02807a58f5-0
00:13:57.840 --> 00:14:02.785
So optimizing resolution becomes a really,
really important part of properly CT

ecbe9363-5870-4b85-aa2d-2f02807a58f5-1
00:14:02.785 --> 00:14:03.960
scanning an object.

e1fd879c-56ce-4f16-bd6e-dd439be082bc-0
00:14:04.520 --> 00:14:06.243
You know,
obviously knee jerk reaction people,

e1fd879c-56ce-4f16-bd6e-dd439be082bc-1
00:14:06.243 --> 00:14:08.480
you ask them, you know,
what kind of resolution do you want?

07704e38-914f-41eb-ba42-e2219488ee68-0
00:14:08.480 --> 00:14:10.893
They want, I want the best, you know,
and sure,

07704e38-914f-41eb-ba42-e2219488ee68-1
00:14:10.893 --> 00:14:14.565
I might be able to scan something at a,
at a very, very high resolution,

07704e38-914f-41eb-ba42-e2219488ee68-2
00:14:14.565 --> 00:14:18.487
but I'm only going to be picking up,
you know, maybe an inch by an inch area,

07704e38-914f-41eb-ba42-e2219488ee68-3
00:14:18.487 --> 00:14:22.359
which if you have a 10 inch part is not
not going to be good enough for you.

4fad2af7-06ef-4465-90ba-1a91f3e4067d-0
00:14:23.720 --> 00:14:28.561
So we try and and counteract people
overestimating how much resolution they

4fad2af7-06ef-4465-90ba-1a91f3e4067d-1
00:14:28.561 --> 00:14:28.880
need.

a51e673f-f780-4e2a-b797-68e8f433c038-0
00:14:29.920 --> 00:14:33.228
And additionally,
the closer the object is to the source,

a51e673f-f780-4e2a-b797-68e8f433c038-1
00:14:33.228 --> 00:14:37.562
the less power the machine can use,
which can start to increase things like

a51e673f-f780-4e2a-b797-68e8f433c038-2
00:14:37.562 --> 00:14:40.928
X-ray artifacting,
which is kind of you can think of like,

a51e673f-f780-4e2a-b797-68e8f433c038-3
00:14:40.928 --> 00:14:42.240
you know, stack on ATV.

9ac9b2c5-dcb3-4c28-9d02-4bac2683133b-0
00:14:42.240 --> 00:14:45.120
It's, it's noise in the image we had.

02f8d214-f3b7-4258-8911-9ae9b181c7cc-0
00:14:45.120 --> 00:14:47.600
Also, like I said,
it lowers that field of view.

d548a1ea-1fd0-4611-9bb8-e6c354cc8403-0
00:14:47.920 --> 00:14:51.520
So we're picking up a much smaller area
than we might need to pick up.

3345aad5-ea11-43c6-9161-bb06d0a12c22-0
00:14:51.920 --> 00:14:55.842
And also conversely, you know,
if if I do have to do a small area and I

3345aad5-ea11-43c6-9161-bb06d0a12c22-1
00:14:55.842 --> 00:14:59.165
have to do several scans together to
capture an entire part,

3345aad5-ea11-43c6-9161-bb06d0a12c22-2
00:14:59.165 --> 00:15:00.800
that's going to drive up cost.

1bdefcb2-44a5-4b58-8142-1c3ee4033081-0
00:15:03.160 --> 00:15:06.638
We do always like to take take a
consultative approach and kind of work

1bdefcb2-44a5-4b58-8142-1c3ee4033081-1
00:15:06.638 --> 00:15:10.213
with you to figure out what will best
suit your needs for each individual

1bdefcb2-44a5-4b58-8142-1c3ee4033081-2
00:15:10.213 --> 00:15:10.600
project.

91006cd2-3746-417a-9dee-7aaac7580eb0-0
00:15:12.400 --> 00:15:14.632
Now,
kind of some examples of this resolution

91006cd2-3746-417a-9dee-7aaac7580eb0-1
00:15:14.632 --> 00:15:16.040
stuff that I'm talking about.

d9acd2dc-1a44-436d-9911-d35c6c80b291-0
00:15:16.440 --> 00:15:19.120
I just grabbed a brass air Chuck out of
our back shop.

f82f7631-0b98-4e2c-aa0d-5447aa843b69-0
00:15:19.480 --> 00:15:20.440
It's a pretty common tool.

9898a52f-982c-4b02-8c3e-3d34d0c1fbaa-0
00:15:20.440 --> 00:15:24.883
Everybody knows what it is,
but so we're gonna look at some of the 2D

9898a52f-982c-4b02-8c3e-3d34d0c1fbaa-1
00:15:24.883 --> 00:15:30.025
X-rays here and let's say we wanted to
look at how these threads are interacting

9898a52f-982c-4b02-8c3e-3d34d0c1fbaa-2
00:15:30.025 --> 00:15:34.341
at the tip of the Chuck at a,
You'll see it says 25 microns for the

9898a52f-982c-4b02-8c3e-3d34d0c1fbaa-3
00:15:34.341 --> 00:15:35.040
resolution.

e06ebac0-bc32-49e4-8fcb-8746e6cc73b6-0
00:15:35.400 --> 00:15:37.600
And this is kind of an inverse thing.

9de2927f-323e-4a9a-ae8b-a7e9f00967ee-0
00:15:37.600 --> 00:15:41.880
The higher the resolution,
the lower the Micron size will be.

618edf97-c532-4c74-9eec-945d84aec796-0
00:15:41.880 --> 00:15:46.828
Basically this means that we're using
smaller and smaller cubes to quantifies

618edf97-c532-4c74-9eec-945d84aec796-1
00:15:46.828 --> 00:15:47.400
the data.

92e61f9b-7567-4b25-9d9c-b68ecdfec660-0
00:15:47.640 --> 00:15:49.782
But as you can see at this low resolution,
you know,

92e61f9b-7567-4b25-9d9c-b68ecdfec660-1
00:15:49.782 --> 00:15:51.480
we see nice crisp lines along the threads.

47505fb0-4b3d-4321-a16f-3cefebac280b-0
00:15:51.480 --> 00:15:52.920
We can see how they're interacting.

41530c2d-e169-4f1e-a75e-05a336c3667e-0
00:15:53.160 --> 00:15:56.379
But as we move that part away and get a
lower and lower resolution,

41530c2d-e169-4f1e-a75e-05a336c3667e-1
00:15:56.379 --> 00:15:57.800
we're starting to get fuzzier.

9b430419-16b5-4cea-9ceb-ba96f3bab6bc-0
00:15:57.800 --> 00:15:59.600
Those sharp edges are becoming rounded.

7f2125f5-ceab-4880-8b1f-1b9fae3acee7-0
00:15:59.840 --> 00:16:03.608
And you know, at something, you know,
at triple the, the triple the voxel size,

7f2125f5-ceab-4880-8b1f-1b9fae3acee7-1
00:16:03.608 --> 00:16:07.423
we're not really seeing what we needed to
see if we were trying to look at those

7f2125f5-ceab-4880-8b1f-1b9fae3acee7-2
00:16:07.423 --> 00:16:07.799
threads.

a73e3162-a472-416b-b097-2d7d2ae6bbde-0
00:16:09.800 --> 00:16:12.997
But also now not just a metal part,
but plastic,

a73e3162-a472-416b-b097-2d7d2ae6bbde-1
00:16:12.997 --> 00:16:18.086
we can kind of see how the resolution
effects those small features that I was

a73e3162-a472-416b-b097-2d7d2ae6bbde-2
00:16:18.086 --> 00:16:19.000
talking about.

31943cde-054d-481a-b1f8-cd88e030ca4a-0
00:16:19.000 --> 00:16:22.689
So we're going to look at the surface of
this little toy tank and at that high

31943cde-054d-481a-b1f8-cd88e030ca4a-1
00:16:22.689 --> 00:16:25.445
resolution, you know,
we can see this kind of little these

31943cde-054d-481a-b1f8-cd88e030ca4a-2
00:16:25.445 --> 00:16:27.359
little features on the bottom side there.

9b81aba5-bc0f-4ab5-aee7-1137b480f933-0
00:16:27.560 --> 00:16:29.603
You know,
we can see all of the the curves and

9b81aba5-bc0f-4ab5-aee7-1137b480f933-1
00:16:29.603 --> 00:16:31.560
radii and all the little bumps and all
that.

cb184c1f-e9f4-4cd9-9b55-22c901b38ecf-0
00:16:31.960 --> 00:16:36.238
And as we increase that voxel size,
you can see that that little, you know,

cb184c1f-e9f4-4cd9-9b55-22c901b38ecf-1
00:16:36.238 --> 00:16:40.798
Griebel on the side there is going to get
more and more kind of just uniform and

cb184c1f-e9f4-4cd9-9b55-22c901b38ecf-2
00:16:40.798 --> 00:16:44.120
just a BLOB instead of crisp like it was
at the beginning.

5a41ad8c-19a0-46bc-8d1e-0b6eb3d4d9ae-0
00:16:44.840 --> 00:16:49.361
We're also seeing as we move further away
from the detector,

5a41ad8c-19a0-46bc-8d1e-0b6eb3d4d9ae-1
00:16:49.361 --> 00:16:52.920
it allows the the contrast to kind of
equalize.

0db3ae83-dff6-4883-8f68-8f34c40da9d6-0
00:16:52.920 --> 00:16:56.603
So you'll see that the side of the tank
is getting smoother as we get further

0db3ae83-dff6-4883-8f68-8f34c40da9d6-1
00:16:56.603 --> 00:16:56.840
away.

147130d5-2cb9-4e32-afc0-b4a45c34a11b-0
00:16:56.840 --> 00:16:58.907
It's because we were able to use a little
bit more power,

147130d5-2cb9-4e32-afc0-b4a45c34a11b-1
00:16:58.907 --> 00:17:01.759
get a little bit better signal to noise
ratio and it's going to help smooth all

147130d5-2cb9-4e32-afc0-b4a45c34a11b-2
00:17:01.759 --> 00:17:02.080
that out.

06ba7fe2-5550-481a-bba6-67ea897bffc6-0
00:17:04.760 --> 00:17:08.435
But like any technology,
TT does have its limitations,

06ba7fe2-5550-481a-bba6-67ea897bffc6-1
00:17:08.435 --> 00:17:10.440
that mainly being artefacting.

70da9e7b-4db8-448f-b12d-1687896a1a61-0
00:17:11.160 --> 00:17:12.880
There's several different types of
artifacting.

9aa4181a-1f03-44be-8254-cce9281e87b7-0
00:17:13.120 --> 00:17:14.800
One of them is going to be extinction.

17509a17-33eb-408f-ab90-fcc67cdca13d-0
00:17:14.920 --> 00:17:18.504
And that's where the X-ray beam ends up
being absorbed by the material and not

17509a17-33eb-408f-ab90-fcc67cdca13d-1
00:17:18.504 --> 00:17:21.000
making it all the way through to the,
to the detector.

2d7fbdb2-a872-4515-a9f7-64e97b91d245-0
00:17:21.680 --> 00:17:24.155
And so, you know, you think X-rays,
what's the thing that's going to limit

2d7fbdb2-a872-4515-a9f7-64e97b91d245-1
00:17:24.155 --> 00:17:24.320
that?

5bae6cbf-25a8-41d2-9517-67805f2ed664-0
00:17:24.320 --> 00:17:25.920
The first thing that popped into our
heads was lead.

d19934da-a4f6-44ba-87c1-99c41765ee16-0
00:17:26.240 --> 00:17:28.760
So we, we CT scanned this,
this bullet here.

adae688d-1908-4105-a425-cf9c6a19c4a4-0
00:17:28.960 --> 00:17:32.261
And as you can see in that bottom left
corner, we got this, this little,

adae688d-1908-4105-a425-cf9c6a19c4a4-1
00:17:32.261 --> 00:17:34.387
you know,
black patch where we know that there

adae688d-1908-4105-a425-cf9c6a19c4a4-2
00:17:34.387 --> 00:17:37.282
should be material there,
but because the lead is absorbing the

adae688d-1908-4105-a425-cf9c6a19c4a4-3
00:17:37.282 --> 00:17:39.453
X-rays,
they're not making the detector and the

adae688d-1908-4105-a425-cf9c6a19c4a4-4
00:17:39.453 --> 00:17:41.760
machine doesn't know that there's
something there.

d810a639-9c95-474e-86a0-567ec1137d4a-0
00:17:43.600 --> 00:17:46.280
Another type of artifacting that we see
is called beam hardening.

7d035a05-47cd-48c1-87b1-6a3fbb30bc9c-0
00:17:46.760 --> 00:17:50.280
We typically see this with higher density
materials in this sample.

38bfeebe-467d-4707-9870-2157a151ff22-0
00:17:50.280 --> 00:17:53.160
You know,
you can see how it's kind of bright

38bfeebe-467d-4707-9870-2157a151ff22-1
00:17:53.160 --> 00:17:58.044
around the edge and then fades to a
darker grey in the middle and kind of has

38bfeebe-467d-4707-9870-2157a151ff22-2
00:17:58.044 --> 00:18:02.240
this undulating, I guess I'll say a,
a colour or colour intensity.

ec73df01-1b4a-4e3e-8957-6a79c94ce42c-0
00:18:02.840 --> 00:18:07.594
And that's because as the X-ray beams hit
that surface, the way that they scatter,

ec73df01-1b4a-4e3e-8957-6a79c94ce42c-1
00:18:07.594 --> 00:18:11.890
the machine thinks that there's a
apparent higher density on the edge of a

ec73df01-1b4a-4e3e-8957-6a79c94ce42c-2
00:18:11.890 --> 00:18:14.640
material when it's actually a uniform
material.

ac4dc527-5522-4f1e-9556-3b5cec5ea1b2-0
00:18:17.120 --> 00:18:19.640
Some more examples of the extinction.

b80a0e65-7017-48e6-a17a-4e22d5a88b12-0
00:18:19.640 --> 00:18:22.480
You can see these dark Gray areas in this
part here.

c2ec1795-ac73-47b9-9d56-3e2348a7ecba-0
00:18:22.680 --> 00:18:24.160
This part is all made of the same
material.

a25ca1fb-81b4-4a93-b01e-63bfba9f305a-0
00:18:24.160 --> 00:18:26.280
It should all be that same grace Gray
scale value.

5179f60d-cd79-4eed-af16-bf70198915fc-0
00:18:26.760 --> 00:18:29.720
But we're getting some extinction and
we're seeing those big shadows.

0deba890-2c96-4ce3-9f6f-69decae8c635-0
00:18:30.240 --> 00:18:32.560
Here's a little bit kind of a zoomed in
image of that.

29b522a9-4f26-46fc-9093-c60719d53cc5-0
00:18:34.320 --> 00:18:38.480
And this last one is going to be what's
called scattered radiation.

35e99140-b4d8-4467-916f-0248131ac096-0
00:18:39.040 --> 00:18:43.318
You can see in kind of these large dark
areas, those should be air,

35e99140-b4d8-4467-916f-0248131ac096-1
00:18:43.318 --> 00:18:44.640
they should be black.

6b24ddf3-9f91-4790-8a9f-c6b3f2717ddb-0
00:18:45.440 --> 00:18:48.948
But when that beam hits material,
sometimes it doesn't continue on its

6b24ddf3-9f91-4790-8a9f-c6b3f2717ddb-1
00:18:48.948 --> 00:18:49.640
straight path.

b286192c-3b10-4537-8cd6-cedbca0d4bff-0
00:18:49.840 --> 00:18:50.720
It scatters.

df6474bf-7aa5-45dd-aa26-b9cf054a950a-0
00:18:51.080 --> 00:18:54.326
And so it's being picked up by a
different area on the detector than the

df6474bf-7aa5-45dd-aa26-b9cf054a950a-1
00:18:54.326 --> 00:18:57.084
beam originally, you know,
came from or what material it went

df6474bf-7aa5-45dd-aa26-b9cf054a950a-2
00:18:57.084 --> 00:18:57.440
through.

d2d0b19e-c1a3-4ffb-8ec2-8f022c6e787a-0
00:18:57.720 --> 00:19:00.600
And so it shows up as this sort of fuzzy
snowy effect.

4bb007f9-47f3-4460-b2b2-2137e320a982-0
00:19:01.800 --> 00:19:05.484
There are ways to counteract all of these
artifacting examples,

4bb007f9-47f3-4460-b2b2-2137e320a982-1
00:19:05.484 --> 00:19:10.147
whether that's through how the parts are
fixtured in the machine to minimize the

4bb007f9-47f3-4460-b2b2-2137e320a982-2
00:19:10.147 --> 00:19:13.658
path length through the material so
there's less deflection,

4bb007f9-47f3-4460-b2b2-2137e320a982-3
00:19:13.658 --> 00:19:17.285
whether that's using different pre
filters or energy settings,

4bb007f9-47f3-4460-b2b2-2137e320a982-4
00:19:17.285 --> 00:19:21.200
whether it's using some software after
the fact to help counteract.

356b65cb-8155-4595-a1ea-a579edeb5b85-0
00:19:21.760 --> 00:19:26.120
What we're seeing next is going to be
accuracy.

791d6f4b-f215-4308-8ddf-d093ae5c3e3b-0
00:19:26.400 --> 00:19:30.272
When CT first came on to the field,
we had some customers that, you know,

791d6f4b-f215-4308-8ddf-d093ae5c3e3b-1
00:19:30.272 --> 00:19:34.353
wanted to see how it compared to like a
traditional CMM system that they were

791d6f4b-f215-4308-8ddf-d093ae5c3e3b-2
00:19:34.353 --> 00:19:36.080
used to getting the results from.

e8a301aa-8039-41b3-9cfa-2fa3b1c00f8c-0
00:19:36.600 --> 00:19:41.265
And to be a little bit nitpicky here in
our laboratory, you know, accuracy,

e8a301aa-8039-41b3-9cfa-2fa3b1c00f8c-1
00:19:41.265 --> 00:19:42.800
it doesn't have a number.

ea92fd1b-b7bb-4307-a655-58031dbf3645-0
00:19:42.800 --> 00:19:44.120
There's no unit for accuracy.

b467fc81-e3b3-41ad-a40c-c29b6fb446a8-0
00:19:44.120 --> 00:19:47.840
I can't point at ACM and go that has five
accuracy.

51aaf811-1bbc-4553-afbd-539038b10945-0
00:19:47.840 --> 00:19:49.040
That just doesn't make sense.

34a90fe2-f713-4874-a81f-e0686b13a9a7-0
00:19:49.480 --> 00:19:52.391
But what I can say is that it has a
certain uncertainty,

34a90fe2-f713-4874-a81f-e0686b13a9a7-1
00:19:52.391 --> 00:19:53.720
A measurement uncertainty.

95199eb0-71ec-437f-97c8-df6d88ef9db4-0
00:19:54.280 --> 00:19:58.167
That means that whatever the measured
value that the machine spits out,

95199eb0-71ec-437f-97c8-df6d88ef9db4-1
00:19:58.167 --> 00:20:01.946
plus or minus a set amount,
the true value of that measurement has to

95199eb0-71ec-437f-97c8-df6d88ef9db4-2
00:20:01.946 --> 00:20:03.080
lie within that band.

07aa3c85-d02a-43ea-ab19-399d2d284071-0
00:20:04.600 --> 00:20:07.205
So,
and by looking at the uncertainty values,

07aa3c85-d02a-43ea-ab19-399d2d284071-1
00:20:07.205 --> 00:20:11.340
I can say that a certain device or
machine is more accurate than another

07aa3c85-d02a-43ea-ab19-399d2d284071-2
00:20:11.340 --> 00:20:12.359
device or machine.

96c20bc8-75fd-4bdd-8bd3-45640afc8033-0
00:20:13.480 --> 00:20:17.773
But uncertainty is just kind of a
mathematical way of addressing any

96c20bc8-75fd-4bdd-8bd3-45640afc8033-1
00:20:17.773 --> 00:20:20.200
possible error from from a measurement.

3f6e7f3b-9a86-4692-be29-a3a6fdc49217-0
00:20:22.240 --> 00:20:23.200
And as you can see.

5aa41f80-2770-4efc-81db-3869633a1286-0
00:20:23.600 --> 00:20:28.442
The posted values that we've we've that
we say for our CT machines are they're

5aa41f80-2770-4efc-81db-3869633a1286-1
00:20:28.442 --> 00:20:33.040
accurate than most of the CMMS that we
actually have in our lab right now.

ca3d696e-5fb2-4ea6-a6cd-fe7d721d4a65-0
00:20:33.040 --> 00:20:36.520
They're sitting at 5.
3 and 9 micro or sorry, 5.3 and 7.3.

decd40fd-f388-4b5f-b476-34fcc126f7a1-0
00:20:36.520 --> 00:20:37.480
You've changed that recently.

e2324f99-6955-4d6f-8611-901a6f134523-0
00:20:37.480 --> 00:20:42.604
It's gotten better microns and you know,
kind of a quick visualization of that,

e2324f99-6955-4d6f-8611-901a6f134523-1
00:20:42.604 --> 00:20:46.320
the CT is going to have a,
a smaller band of uncertainty.

1f3fe6a9-cf41-446e-bc2e-eaf0e94c28f1-0
00:20:46.320 --> 00:20:50.095
That means that that value is going to
fall within the a tighter tolerance than

1f3fe6a9-cf41-446e-bc2e-eaf0e94c28f1-1
00:20:50.095 --> 00:20:52.360
the CMM because it has a,
a larger uncertainty.

44eb60a3-d398-42a8-bb0f-489a28a35339-0
00:20:54.320 --> 00:20:57.137
And the kind of neat thing about CT is
you can actually,

44eb60a3-d398-42a8-bb0f-489a28a35339-1
00:20:57.137 --> 00:20:58.720
there's a visualization of that.

7d8ecce7-1899-4d7c-9849-b979e6bdd366-0
00:20:58.960 --> 00:21:02.880
So each individual voxel has its own
uncertainty applied to it.

c7942671-012c-4a75-9442-7b4bdfa76568-0
00:21:03.320 --> 00:21:06.114
So as you can see on the surface of the
scan,

c7942671-012c-4a75-9442-7b4bdfa76568-1
00:21:06.114 --> 00:21:09.760
it's kind of got this stippled orange
peel type appearance.

09054684-2746-423e-9699-5de666f59659-0
00:21:10.200 --> 00:21:14.360
And that's because two adjacent voxels
have different uncertainty.

24581a4c-fa37-4543-91be-f4f51468d797-0
00:21:14.360 --> 00:21:16.680
So 1 might be on the lower end,
1 might be on the higher end.

0436a559-75cd-4123-bee5-4f9a09754530-0
00:21:16.680 --> 00:21:19.880
And so you see this this bumpiness across
the surface.

198a60c0-72be-43e1-b05e-26b0980e52bf-0
00:21:20.680 --> 00:21:22.960
This does not affect accuracy in any way.

e95e9b1b-78e7-40b9-839c-d3a4cb18c44e-0
00:21:22.960 --> 00:21:26.000
It's just a visualization of that
uncertainty.

139013b5-eb9a-4a13-815a-da9ecadb5bd7-0
00:21:28.560 --> 00:21:30.560
And you know,
we wanted to kind of prove this out.

5af85387-602c-4650-b61d-49d9df3de08b-0
00:21:30.560 --> 00:21:32.240
So I'll quickly kind of dive into this.

a182f5fd-c4a3-47d5-9d5d-e7f3c750d74f-0
00:21:32.240 --> 00:21:35.513
This is a bit more of in the weeds nerd
math stuff,

a182f5fd-c4a3-47d5-9d5d-e7f3c750d74f-1
00:21:35.513 --> 00:21:39.480
but the machine comes with a what's
called a cupcake artifact.

eb406e30-fb9e-4d33-8c76-ba7b08febee7-0
00:21:39.480 --> 00:21:43.721
It's just helped to calibrate the machine,
but it's a bunch of Ruby tip style,

eb406e30-fb9e-4d33-8c76-ba7b08febee7-1
00:21:43.721 --> 00:21:47.748
I like you would see on an CMM and
they're set up in a certain pattern and

eb406e30-fb9e-4d33-8c76-ba7b08febee7-2
00:21:47.748 --> 00:21:51.400
we have known distances between the
center of all of those spheres.

3f4c5f3f-beb8-4d92-8a81-6c2680d95770-0
00:21:52.600 --> 00:21:55.281
And so we took those,
we measured them on CT and kind of found

3f4c5f3f-beb8-4d92-8a81-6c2680d95770-1
00:21:55.281 --> 00:21:57.920
the difference of all of those
measurements from the nominal.

65dcce33-2c3b-42c7-bec9-e48bcae22e91-0
00:21:58.440 --> 00:22:02.841
And as you can see by the graph,
another quick visualization, all of those,

65dcce33-2c3b-42c7-bec9-e48bcae22e91-1
00:22:02.841 --> 00:22:06.952
both the CMM and CT falling well,
well within their posted uncertainty

65dcce33-2c3b-42c7-bec9-e48bcae22e91-2
00:22:06.952 --> 00:22:09.790
values,
which would be that top green and purple

65dcce33-2c3b-42c7-bec9-e48bcae22e91-3
00:22:09.790 --> 00:22:10.079
line.

0075cd10-b980-4b3b-82ca-e7275b8d4b97-0
00:22:11.320 --> 00:22:13.800
But we also wanted to do it on something
that was a little less uniform.

2acd484e-2905-4091-a240-20734e0b0406-0
00:22:13.800 --> 00:22:16.804
So we took some parts,
kind of ran the same thing,

2acd484e-2905-4091-a240-20734e0b0406-1
00:22:16.804 --> 00:22:20.691
picked a couple dimensions off of the
print, you know, same deal,

2acd484e-2905-4091-a240-20734e0b0406-2
00:22:20.691 --> 00:22:25.227
ran a bunch of times and we're still
falling within those posted uncertainty

2acd484e-2905-4091-a240-20734e0b0406-3
00:22:25.227 --> 00:22:25.640
values.

b2421c63-f937-4a23-826a-7e5e686945ba-0
00:22:25.640 --> 00:22:29.145
There's a bit more variation just because
there are parts there that are, you know,

b2421c63-f937-4a23-826a-7e5e686945ba-1
00:22:29.145 --> 00:22:31.148
coming from different cavities within the
tool,

b2421c63-f937-4a23-826a-7e5e686945ba-2
00:22:31.148 --> 00:22:34.403
They're coming from different processes,
you know, each part, you know, well,

b2421c63-f937-4a23-826a-7e5e686945ba-3
00:22:34.403 --> 00:22:37.200
you want to want, you know,
want plastic to cool at the same rate.

68f03371-8fbd-438b-b15a-65c1b88a2efc-0
00:22:37.200 --> 00:22:39.640
There are minimal differences between
part to part to part.

a9fea6c5-7b2d-4f73-b0d5-cd2aa951cadf-0
00:22:42.240 --> 00:22:46.505
And lastly, we know again,
we're just trying to compare the CT and

a9fea6c5-7b2d-4f73-b0d5-cd2aa951cadf-1
00:22:46.505 --> 00:22:46.760
CMM.

8b470917-ab8a-4441-a8ed-8c5c3052d9cb-0
00:22:46.760 --> 00:22:48.240
So we're looking at some more of that
data.

d4b00168-a0ce-4101-8203-fcc0d7dfb5be-0
00:22:50.000 --> 00:22:51.600
But what does all this mean to you?

d59abf08-8eb0-41a9-a818-b29405268c83-0
00:22:51.640 --> 00:22:54.076
You know,
we want to assure you that the

d59abf08-8eb0-41a9-a818-b29405268c83-1
00:22:54.076 --> 00:22:58.829
measurements and the volumes and things
that you're getting out of CT are going

d59abf08-8eb0-41a9-a818-b29405268c83-2
00:22:58.829 --> 00:23:01.800
to be just as accurate as traditional
technology.

8ea75856-b888-496f-bccd-0f923b5fa5bf-0
00:23:02.680 --> 00:23:05.828
And we want you to have confidence to,
to make changes and make decisions based

8ea75856-b888-496f-bccd-0f923b5fa5bf-1
00:23:05.828 --> 00:23:07.600
on the information that we're providing
you.

31425ac3-ab95-4142-a4de-1e0f39f54bca-0
00:23:07.600 --> 00:23:10.024
We don't want you,
we don't want you to have any doubt,

31425ac3-ab95-4142-a4de-1e0f39f54bca-1
00:23:10.024 --> 00:23:12.146
you know,
from the information that we're giving

31425ac3-ab95-4142-a4de-1e0f39f54bca-2
00:23:12.146 --> 00:23:12.320
you.

76fde05f-6369-45aa-ab7a-237560cc5904-0
00:23:15.000 --> 00:23:18.022
But now that I've talked about how you
actually acquire, you know,

76fde05f-6369-45aa-ab7a-237560cc5904-1
00:23:18.022 --> 00:23:21.360
a 3T data set at the end of the day,
what you know, what are you getting?

ed17f80c-fa1c-4656-9173-1d53806fa01c-0
00:23:22.240 --> 00:23:27.589
And like I said, there's, it's so,
so there's so many different ways you can

ed17f80c-fa1c-4656-9173-1d53806fa01c-1
00:23:27.589 --> 00:23:28.840
utilize this data.

26b7f996-14eb-48d6-a209-166cba1f50a5-0
00:23:29.800 --> 00:23:32.920
Kind of the first one that we do often is
going to be St.

e05fbff8-a457-4401-a6ba-97b95ade88a1-0
00:23:32.920 --> 00:23:33.160
LS.

1f1f119f-dc1f-4751-8956-790f917c4076-0
00:23:33.160 --> 00:23:35.280
It's going to be a surface ramp of the
volume.

734e5f29-1c96-4643-9db4-286c6b9115ab-0
00:23:35.920 --> 00:23:38.560
This can then be used to do reverse
engineering.

dfa9ae1a-65ff-4602-9ff9-256024c13e53-0
00:23:38.560 --> 00:23:43.074
We can take that into a software and
start building out perfect parametric CAD

dfa9ae1a-65ff-4602-9ff9-256024c13e53-1
00:23:43.074 --> 00:23:44.160
models off of that.

e8e16da0-2df7-467f-999b-02e7dd8d566e-0
00:23:44.160 --> 00:23:48.275
We've had clients that have obtained
tools either through an acquisition or a

e8e16da0-2df7-467f-999b-02e7dd8d566e-1
00:23:48.275 --> 00:23:51.600
merger or something like that,
that were pre digitized prints.

00e970b5-756b-4c98-a27a-5660129f62b8-0
00:23:51.600 --> 00:23:55.051
They don't have any CAD models,
but we can take the physical parts and

00e970b5-756b-4c98-a27a-5660129f62b8-1
00:23:55.051 --> 00:23:57.920
help them build up their library of all
of their products.

b434ad79-b56a-441b-b738-b822912a2922-0
00:23:58.760 --> 00:24:01.480
And we can also take those and do first
article inspections.

e748df90-d812-4291-8189-30cb54322833-0
00:24:01.480 --> 00:24:04.350
You know,
you can check all the dimensions on

e748df90-d812-4291-8189-30cb54322833-1
00:24:04.350 --> 00:24:08.843
prints for you, case studies,
all that kind of stuff into the more kind

e748df90-d812-4291-8189-30cb54322833-2
00:24:08.843 --> 00:24:10.840
of unique things that CT can do.

d53b5b1b-b99c-4645-94a9-15ae01b7bbd7-0
00:24:10.840 --> 00:24:12.960
That's going to be porosity analysis.

b8e559c3-3470-4087-8972-a8ae504e4399-0
00:24:12.960 --> 00:24:14.520
You'll see that in the bottom right image.

9f34e580-d7bc-4f81-ae6a-7fdc6e481ec2-0
00:24:14.720 --> 00:24:17.400
And that's just simply looking for voids
within a part.

14ba37f6-f113-4432-99f1-fdfdb5676f9d-0
00:24:17.720 --> 00:24:21.102
We had a little toy cinder block,
like 3D printed cinder block that we

14ba37f6-f113-4432-99f1-fdfdb5676f9d-1
00:24:21.102 --> 00:24:21.960
checked for voids.

23be748f-23ba-4b40-9326-8b6dfbf536aa-0
00:24:22.440 --> 00:24:24.680
We can do things like wall thickness
analysis.

0383b794-5736-4a15-a6f8-81ab8389af47-0
00:24:24.680 --> 00:24:28.155
We can do things like assembly failure,
finite element analysis,

0383b794-5736-4a15-a6f8-81ab8389af47-1
00:24:28.155 --> 00:24:30.240
flaw detection is going to be very big.

2d0ff0ee-11ff-4cc5-9247-b7dbe4014242-0
00:24:30.480 --> 00:24:31.480
We do a lot of things.

f12fd569-f6b1-4058-867f-c6f98920326c-0
00:24:31.480 --> 00:24:35.473
You can see on the left bottom there we
do a lot of like crack detection and

f12fd569-f6b1-4058-867f-c6f98920326c-1
00:24:35.473 --> 00:24:38.170
things like that,
as well as in the top left as how

f12fd569-f6b1-4058-867f-c6f98920326c-2
00:24:38.170 --> 00:24:40.920
different things are interacting within
an assembly.

80e90ff8-11f0-43f4-bd1b-cc73a614c30a-0
00:24:43.680 --> 00:24:45.960
Another big market for us is going to be
colour mapping.

3750da69-5e86-488d-95d9-f11bef259c58-0
00:24:46.120 --> 00:24:49.800
This is just really helps with visual
visualizing what's going on with the part.

25c984d5-fce1-40bb-b9dc-f5c2e90366d9-0
00:24:50.280 --> 00:24:54.230
We can take that 3D volume that we've
scanned and we can either overlay it on a

25c984d5-fce1-40bb-b9dc-f5c2e90366d9-1
00:24:54.230 --> 00:24:57.440
perfect CAD model or we can even do
cavity to cavity comparison.

53628e4c-bd74-4520-b257-ed19cc4a63bc-0
00:24:57.440 --> 00:25:02.875
If we're trying to look at something like
how something ages or wears over use over

53628e4c-bd74-4520-b257-ed19cc4a63bc-1
00:25:02.875 --> 00:25:05.723
time,
some kind of more niche unique things

53628e4c-bd74-4520-b257-ed19cc4a63bc-2
00:25:05.723 --> 00:25:09.799
that we're able to do is going to be
fiber composite analysis.

6026029f-adb6-40f0-9e6c-46884c661007-0
00:25:10.080 --> 00:25:15.970
It's very handy for fiber Rep cable or
fiberglass inside of a plastic injection

6026029f-adb6-40f0-9e6c-46884c661007-1
00:25:15.970 --> 00:25:16.560
molding.

99239c04-2977-42b1-942f-ce0c67b54a1f-0
00:25:16.920 --> 00:25:21.482
It's just looking at how all of the
fibers are oriented within a certain

99239c04-2977-42b1-942f-ce0c67b54a1f-1
00:25:21.482 --> 00:25:21.920
sample.

7d24897c-fab7-452f-99ca-08ae0bc07b8e-0
00:25:23.400 --> 00:25:25.200
We can also do foam and powder analysis.

fd2fef89-8dfa-4549-bf1f-43eac87b403e-0
00:25:25.200 --> 00:25:27.520
These are kind of yin and Yang of each
other.

b7d2b947-5aa3-4a47-8d37-1ee44968ca82-0
00:25:27.680 --> 00:25:29.815
The powder,
we're going to be looking at the

b7d2b947-5aa3-4a47-8d37-1ee44968ca82-1
00:25:29.815 --> 00:25:32.520
distribution and size of the granules
within the powder.

0021edcc-d73e-43bb-8014-6f499435ece3-0
00:25:33.120 --> 00:25:37.870
And then conversely the foam we're going
to be looking at the size and shape of

0021edcc-d73e-43bb-8014-6f499435ece3-1
00:25:37.870 --> 00:25:40.720
the the struts or the air gaps within the
foam.

8e60b01d-b761-4f6a-98b9-b20396269293-0
00:25:40.760 --> 00:25:44.003
I guess this,
so this my BGL viewer software,

8e60b01d-b761-4f6a-98b9-b20396269293-1
00:25:44.003 --> 00:25:49.291
something that we provide to you,
volume graphics is what we use for a lot

8e60b01d-b761-4f6a-98b9-b20396269293-2
00:25:49.291 --> 00:25:54.156
of those colour mapping as well as the
flaw detection, the assembly,

8e60b01d-b761-4f6a-98b9-b20396269293-3
00:25:54.156 --> 00:25:57.399
interaction analysis,
all that kind of stuff.

2a093677-683f-4305-bdbe-3779c77a6c5c-0
00:25:57.800 --> 00:26:01.726
It takes the 3D volume,
it's going to display it in three

2a093677-683f-4305-bdbe-3779c77a6c5c-1
00:26:01.726 --> 00:26:03.080
orthogonal 2D views.

30101689-3df0-462e-9e70-4f3b35adc387-0
00:26:03.280 --> 00:26:08.180
We can also set that up to be one of them
to be a rotational view if the parts you

30101689-3df0-462e-9e70-4f3b35adc387-1
00:26:08.180 --> 00:26:10.777
know,
diametrically symmetric as well as it

30101689-3df0-462e-9e70-4f3b35adc387-2
00:26:10.777 --> 00:26:13.080
provides a 3D view in the bottom right.

89a22ee2-1824-4486-92e4-8b28808432bc-0
00:26:13.240 --> 00:26:17.860
But this is just a very handy way of
visualizing the 3D data that allows you

89a22ee2-1824-4486-92e4-8b28808432bc-1
00:26:17.860 --> 00:26:21.520
to have your own time, you know,
parse through these slices,

89a22ee2-1824-4486-92e4-8b28808432bc-2
00:26:21.520 --> 00:26:25.300
look at things you know,
and make decisions on your own rather

89a22ee2-1824-4486-92e4-8b28808432bc-3
00:26:25.300 --> 00:26:30.280
than just when you're immediately on a,
a web meeting with us going over the data.

e56043a2-ef06-49da-b708-2982d9e3e875-0
00:26:33.720 --> 00:26:36.249
So some of the benefits of these
deliverables,

e56043a2-ef06-49da-b708-2982d9e3e875-1
00:26:36.249 --> 00:26:38.240
it's visualization is the main thing.

c933c7a0-062b-4be0-942d-042f3eb3d7ec-0
00:26:38.600 --> 00:26:40.600
It allows you to see what is going on.

0a22e6e4-dd7a-478e-9104-b30bf380996b-0
00:26:41.320 --> 00:26:43.598
You know, as engineers and kind of R&
D people,

0a22e6e4-dd7a-478e-9104-b30bf380996b-1
00:26:43.598 --> 00:26:45.920
we're used to dealing with numbers on a
spreadsheet.

57081840-5995-4453-84ce-b684631181d5-0
00:26:46.200 --> 00:26:49.183
But being able to take, you know,
a color map and say, look,

57081840-5995-4453-84ce-b684631181d5-1
00:26:49.183 --> 00:26:52.069
this part is warped here to people who
aren't as you know,

57081840-5995-4453-84ce-b684631181d5-2
00:26:52.069 --> 00:26:54.320
deep into the science part of it like we
are.

06f38fee-af45-4836-9941-8cfa814cd86e-0
00:26:54.600 --> 00:26:56.576
It's,
it's much more intuitive to understand

06f38fee-af45-4836-9941-8cfa814cd86e-1
00:26:56.576 --> 00:26:59.694
what is going on versus saying, you know,
this diameter is this value,

06f38fee-af45-4836-9941-8cfa814cd86e-2
00:26:59.694 --> 00:27:00.880
this length is this length.

c6056252-2eaa-43c6-8f4d-584457728f27-0
00:27:02.000 --> 00:27:03.960
Another thing is these are permanent
records.

d25b27a0-ed65-4660-bca0-8d192f1563b7-0
00:27:03.960 --> 00:27:07.451
We've had companies that, you know,
they upgrade all the computers in their,

d25b27a0-ed65-4660-bca0-8d192f1563b7-1
00:27:07.451 --> 00:27:11.215
in their department and they realize that
they've deleted the data that we've sent

d25b27a0-ed65-4660-bca0-8d192f1563b7-2
00:27:11.215 --> 00:27:11.760
them before.

117bb0fa-dc25-4f3f-b418-2fe16796aade-0
00:27:12.000 --> 00:27:13.760
You know,
we hang on to this data indefinitely.

d084538a-616e-4d20-8904-7f0385b7a447-0
00:27:13.760 --> 00:27:17.529
You can always come back to us and we're
more than happy to re provide the, the,

d084538a-616e-4d20-8904-7f0385b7a447-1
00:27:17.529 --> 00:27:21.160
the data that we've captured for you or
the analysis that we've done for you.

32145b80-a171-41f0-a59c-90807de0db6e-0
00:27:21.960 --> 00:27:24.702
And like Dave said,
this just really just accelerates your

32145b80-a171-41f0-a59c-90807de0db6e-1
00:27:24.702 --> 00:27:25.400
time to market.

3585304d-7381-44a4-b971-6628c8155f86-0
00:27:25.400 --> 00:27:28.080
You know,
it's all about helping you help yourself.

a20a170a-19fb-43cf-8f2b-75602ec0b5c4-0
00:27:30.880 --> 00:27:33.469
One of the last things that we do is
going to be those first article

a20a170a-19fb-43cf-8f2b-75602ec0b5c4-1
00:27:33.469 --> 00:27:33.920
inspections.

c663a917-3e6f-4cab-8028-c28082800ced-0
00:27:35.240 --> 00:27:41.336
What you're seeing right here is this
software used to be our main 3D analysis

c663a917-3e6f-4cab-8028-c28082800ced-1
00:27:41.336 --> 00:27:43.960
software for dimensional analysis.

6d08f5d2-d8c9-4a10-9123-60833fb2e36e-0
00:27:44.120 --> 00:27:46.840
And this was based on old CMM data.

88936149-243b-459b-be33-10e34ca134f7-0
00:27:46.840 --> 00:27:48.520
It was not data, sorry, software.

1c9d00c9-4c0b-4347-b827-eb627a0a9a84-0
00:27:48.520 --> 00:27:50.000
It was the CMM program first.

cee4809a-ba58-42bc-b5f2-6b5e8e241629-0
00:27:50.680 --> 00:27:54.641
So much like ACMM,
it's taking discrete points, you know,

cee4809a-ba58-42bc-b5f2-6b5e8e241629-1
00:27:54.641 --> 00:27:59.560
individual points on ACT surface,
but at a much, much accelerated rate.

6e6a6d73-b3c7-47ba-9f99-a6a88fc205c6-0
00:27:59.560 --> 00:28:01.642
You know,
I think this program has about 80

6e6a6d73-b3c7-47ba-9f99-a6a88fc205c6-1
00:28:01.642 --> 00:28:02.920
something dimensions in it.

35b268ec-62d3-404b-b391-abb85ddfc287-0
00:28:03.640 --> 00:28:05.320
You can see it running here in real time.

10dcc50e-71fe-48c5-91e9-7d767f420a68-0
00:28:05.640 --> 00:28:09.804
This is something that if I was to put
this on a physical CMM that would take

10dcc50e-71fe-48c5-91e9-7d767f420a68-1
00:28:09.804 --> 00:28:13.915
upwards of at least 1/2 hour per part
just because there might be, you know,

10dcc50e-71fe-48c5-91e9-7d767f420a68-2
00:28:13.915 --> 00:28:18.239
I might have to change the probe head,
I might have to change the orientation of

10dcc50e-71fe-48c5-91e9-7d767f420a68-3
00:28:18.239 --> 00:28:18.720
the part.

2cf58bba-5616-48e2-9c56-d74c4157c697-0
00:28:18.720 --> 00:28:22.203
I'm going to have to do make sure I'm,
I'm doing a lot of clearance moves so

2cf58bba-5616-48e2-9c56-d74c4157c697-1
00:28:22.203 --> 00:28:24.240
that the probe isn't smashing into the
part.

08ebc298-34d5-4f2a-b9cd-8397db6d28ea-0
00:28:25.160 --> 00:28:27.560
But with the CT data, you know,
everything's digital.

768986a5-02c6-44b1-bfb3-f039d0cd90f0-0
00:28:27.560 --> 00:28:30.162
There is no, you know, interaction with,
with, you know,

768986a5-02c6-44b1-bfb3-f039d0cd90f0-1
00:28:30.162 --> 00:28:33.815
needing to worry about how to something
moves around something or anything like

768986a5-02c6-44b1-bfb3-f039d0cd90f0-2
00:28:33.815 --> 00:28:36.098
that or,
or flipping apart so they can get access

768986a5-02c6-44b1-bfb3-f039d0cd90f0-3
00:28:36.098 --> 00:28:37.240
to different sides of it.

6b7d8e46-31e7-4cef-b975-348f39bba9b0-0
00:28:38.640 --> 00:28:41.440
Now we've moved on to mainly using Zeiss
inspect,

6b7d8e46-31e7-4cef-b975-348f39bba9b0-1
00:28:41.440 --> 00:28:45.080
which is previously known as go and very,
very similar software.

957327f7-330b-4757-ad8b-c647f076a944-0
00:28:45.080 --> 00:28:49.160
But instead of doing the discrete points,
we're now looking at entire surfaces.

ce448382-a37f-4775-b4d4-6def80355f06-0
00:28:49.400 --> 00:28:53.440
And instead of doing a part of the time,
we're doing multiple parts at a time.

30fb4818-d198-45ff-99d4-59aed2831e84-0
00:28:53.440 --> 00:28:57.400
And it's just increasing the speed at
which which things can be done.

f55b015e-1ecf-4a5f-a2cd-572dae20e163-0
00:28:59.840 --> 00:29:02.240
But at the end of the day, you know,
what does this all mean for you?

68cabae8-5a8b-4c61-ae20-304f386b1960-0
00:29:03.360 --> 00:29:07.210
You know, we here at Now Pre Tech,
we helped use our people processing

68cabae8-5a8b-4c61-ae20-304f386b1960-1
00:29:07.210 --> 00:29:11.493
platform, that power of visualization,
as well as all the deliverables that CT

68cabae8-5a8b-4c61-ae20-304f386b1960-2
00:29:11.493 --> 00:29:15.723
can provide to help you fully integrate
this into your workflow to save time,

68cabae8-5a8b-4c61-ae20-304f386b1960-3
00:29:15.723 --> 00:29:16.320
save money.

9f88cdad-3611-4ab0-b2cc-04bd43d016b5-0
00:29:16.600 --> 00:29:19.521
And, you know,
ultimately they just get things to market

9f88cdad-3611-4ab0-b2cc-04bd43d016b5-1
00:29:19.521 --> 00:29:19.880
faster.

81593040-397a-4157-9267-28e09e4d4fc3-0
00:29:21.120 --> 00:29:24.030
And we have a saying here and that's
going to be seeing is better than

81593040-397a-4157-9267-28e09e4d4fc3-1
00:29:24.030 --> 00:29:24.440
believing.

0a212837-228a-42d3-ad29-679eb6727b6a-0
00:29:24.960 --> 00:29:28.269
Like I said before, you know,
someone who's a bit more engineering

0a212837-228a-42d3-ad29-679eb6727b6a-1
00:29:28.269 --> 00:29:31.875
minded can understand, you know,
the numbers and the the boring parts of

0a212837-228a-42d3-ad29-679eb6727b6a-2
00:29:31.875 --> 00:29:32.320
our jobs.

63d000dd-c82a-4d3f-b5a9-26dd6171d9c7-0
00:29:32.320 --> 00:29:35.826
But being able to take something into,
you know, a meeting, a board meeting,

63d000dd-c82a-4d3f-b5a9-26dd6171d9c7-1
00:29:35.826 --> 00:29:39.196
something like that and have people
physically see what's going on and be

63d000dd-c82a-4d3f-b5a9-26dd6171d9c7-2
00:29:39.196 --> 00:29:41.200
able to intuit and quickly solve a
problem.

16ef9883-7e63-400b-a639-11da0757f5c1-0
00:29:41.760 --> 00:29:43.480
You know, it's just,
it's what we're here for.

e6c3fda0-bcc9-46f9-8fa3-d746f0056260-0
00:29:43.480 --> 00:29:45.320
It's what it's what our desired goal is.

0d50a03f-7832-4d9a-bfbc-e12475ee839a-0
00:29:46.080 --> 00:29:50.285
We do also have a kind of AC,
an e-book that kind of goes into a little

0d50a03f-7832-4d9a-bfbc-e12475ee839a-1
00:29:50.285 --> 00:29:53.440
bit more in depth everything we've talked
about here.

e51e0b0c-6cae-4e0a-b462-2565a76d904a-0
00:29:54.240 --> 00:29:58.000
But like Victoria and Dave said, you know,
we're here to answer any questions.

5a64c40b-4505-4d35-a12e-31a00aaff1af-0
00:29:58.000 --> 00:30:00.168
So if there's been any that have been,
you know,

5a64c40b-4505-4d35-a12e-31a00aaff1af-1
00:30:00.168 --> 00:30:03.532
typed in the chat during the presentation
or if you have any now, you know,

5a64c40b-4505-4d35-a12e-31a00aaff1af-2
00:30:03.532 --> 00:30:05.480
we're more than happy to help answer
those.

0eec803d-a1de-43c5-8d7f-9bb9bb730230-0
00:30:07.240 --> 00:30:10.717
Hey, Carter,
a question that comes up often,

0eec803d-a1de-43c5-8d7f-9bb9bb730230-1
00:30:10.717 --> 00:30:15.200
are there any size restrictions on parts
for CT scanning?

bcdbc4fa-77b0-46dc-8baf-5e4c51e74acd-0
00:30:16.360 --> 00:30:17.280
Yeah, there is.

e5e5f281-8326-4b6b-a2e9-c2217c94ba79-0
00:30:17.960 --> 00:30:21.960
We have two machines here in house,
a Metrotom 800 and a Metrotom 1500.

124bc77e-6524-44d3-abe2-b874d504f2c4-0
00:30:22.760 --> 00:30:25.360
The 800 is going to be the smaller
machine.

fdd107a1-2cf8-4340-b8e0-c3879a064d1f-0
00:30:25.360 --> 00:30:26.480
It has an envelope.

e69957e5-fc32-41a8-a070-44868bf6a003-0
00:30:28.720 --> 00:30:34.547
I think it's about probably do about 6
inches in diameter and we can do through

e69957e5-fc32-41a8-a070-44868bf6a003-1
00:30:34.547 --> 00:30:35.640
stacking scans.

aa20394e-875c-4bb8-a9ac-627c3d062faf-0
00:30:35.640 --> 00:30:39.320
We can do probably about I think 2 feet
in that machine vertically.

846d1acf-c57e-45ce-a086-cc672e118bed-0
00:30:39.320 --> 00:30:41.680
The 1500 is going to be a bigger detector.

5abfd644-cc51-403a-a563-c0b147142dc4-0
00:30:41.680 --> 00:30:46.371
We can do about,
I think it's 16 inches and then we can do

5abfd644-cc51-403a-a563-c0b147142dc4-1
00:30:46.371 --> 00:30:48.280
about 3 feet vertically.

9708e341-d14c-4ced-9536-06b77a4debe1-0
00:30:48.880 --> 00:30:51.384
So yeah,
we can add to that by saying there's some

9708e341-d14c-4ced-9536-06b77a4debe1-1
00:30:51.384 --> 00:30:52.760
density limitations as well.

3ac6e6cd-56ae-430f-98cf-0309d365df5f-0
00:30:53.200 --> 00:30:56.908
These two machines that we're talking
about are in the, you know,

3ac6e6cd-56ae-430f-98cf-0309d365df5f-1
00:30:56.908 --> 00:31:01.235
energies are and machine configurations
are, I'll call them metrology grade,

3ac6e6cd-56ae-430f-98cf-0309d365df5f-2
00:31:01.235 --> 00:31:04.045
you know,
But when we get into some of the higher

3ac6e6cd-56ae-430f-98cf-0309d365df5f-3
00:31:04.045 --> 00:31:06.293
energies,
we can get more into strictly

3ac6e6cd-56ae-430f-98cf-0309d365df5f-4
00:31:06.293 --> 00:31:07.080
visualization.

d713ab71-538f-4d72-8d35-5c87b48e477b-0
00:31:07.560 --> 00:31:11.846
And when we go into those higher energy
machines, we,

d713ab71-538f-4d72-8d35-5c87b48e477b-1
00:31:11.846 --> 00:31:17.800
we work with our OEM partners to,
to provide our customers access to that.

6b84540a-fbc9-4490-ad83-f04ed00da459-0
00:31:17.800 --> 00:31:21.200
So we can go as high as 9 MEV.

00f3f2f7-07e9-4ffa-9f1a-5355595f735a-0
00:31:22.400 --> 00:31:26.957
So we're, you know,
our 1500 was at 225 MEV or 225 KV and we

00f3f2f7-07e9-4ffa-9f1a-5355595f735a-1
00:31:26.957 --> 00:31:31.962
can get through, you know,
maybe what 1/4 inch of steel we can get

00f3f2f7-07e9-4ffa-9f1a-5355595f735a-2
00:31:31.962 --> 00:31:36.520
through like an inch and 1/2 inch and a
half of steel maybe.

0e198444-a23e-42db-974f-f679e4935d69-0
00:31:36.600 --> 00:31:39.398
And when you go up to the six MEV
machines, I mean,

0e198444-a23e-42db-974f-f679e4935d69-1
00:31:39.398 --> 00:31:42.735
you can punch through an engine block,
get through, you know,

0e198444-a23e-42db-974f-f679e4935d69-2
00:31:42.735 --> 00:31:43.919
several feet of steel.

d498e674-bfa6-4933-a288-be4fb6a0f2d1-0
00:31:44.640 --> 00:31:48.529
So, you know,
through through those partnerships,

d498e674-bfa6-4933-a288-be4fb6a0f2d1-1
00:31:48.529 --> 00:31:54.520
we're able to really kind of offer a full
range of park sizes and densities.

b2b03866-8ea4-44d0-8ff7-5bac719aa470-0
00:31:57.960 --> 00:32:02.865
So in addition to that,
can you kind of expand on what materials

b2b03866-8ea4-44d0-8ff7-5bac719aa470-1
00:32:02.865 --> 00:32:08.449
might be restrictive or materials that
are typically compatible with this

b2b03866-8ea4-44d0-8ff7-5bac719aa470-2
00:32:08.449 --> 00:32:09.279
technology?

30465a95-5e62-4b48-87c1-b204d26275a2-0
00:32:10.800 --> 00:32:13.788
Yeah,
Obviously a plastic is going to be the

30465a95-5e62-4b48-87c1-b204d26275a2-1
00:32:13.788 --> 00:32:14.320
easiest.

5f896501-e6c5-4e81-96e2-2fc1e6698b72-0
00:32:14.320 --> 00:32:16.040
We can get through a lot,
a lot of plastic.

c130003b-12b7-4dbd-8a61-0c2a37eca40d-0
00:32:16.040 --> 00:32:19.920
It's very low density and that's it's
mostly tied into density.

dc60028d-8c0b-488b-80af-720e375f4a8b-0
00:32:19.920 --> 00:32:23.491
The more dense the material and more of
the material is going to be the limiting

dc60028d-8c0b-488b-80af-720e375f4a8b-1
00:32:23.491 --> 00:32:23.800
factor.

74a4bb2f-9815-416b-a420-8965b2efae71-0
00:32:24.840 --> 00:32:28.266
We typically like to mention steel
because that's usually what we're we,

74a4bb2f-9815-416b-a420-8965b2efae71-1
00:32:28.266 --> 00:32:30.520
you know,
mostly see in in production products.

d0f86684-7279-44ad-a72b-e9168572c9e6-0
00:32:32.720 --> 00:32:35.218
But yeah, much,
much higher density materials,

d0f86684-7279-44ad-a72b-e9168572c9e6-1
00:32:35.218 --> 00:32:37.876
things like lead or depleted uranium or
tungsten,

d0f86684-7279-44ad-a72b-e9168572c9e6-2
00:32:37.876 --> 00:32:42.288
those are going to be start to be harder
to get through and we're going to be able

d0f86684-7279-44ad-a72b-e9168572c9e6-3
00:32:42.288 --> 00:32:44.840
to get through less and less material of
those.

42b7a6bf-71ad-4ca0-b0eb-ad193d14ba4d-0
00:32:48.200 --> 00:32:50.760
And then how about multi material?

c33e974d-b0e0-4acb-8ca5-b4fd5978e254-0
00:32:50.760 --> 00:32:52.680
Can you expand on that a little bit?

2f54ab77-0602-4aef-a464-d6f19c8cfc47-0
00:32:53.720 --> 00:32:54.080
Sure.

6af5c44d-c4bb-491e-a60c-a47cbdc56a64-0
00:32:55.000 --> 00:32:59.324
So there is a a multi material capacity
with CT Unfortunately,

6af5c44d-c4bb-491e-a60c-a47cbdc56a64-1
00:32:59.324 --> 00:33:04.609
due to the nature of the technology,
we do have to kind of error on the side

6af5c44d-c4bb-491e-a60c-a47cbdc56a64-2
00:33:04.609 --> 00:33:10.101
of capturing the higher density material,
which does degrade the quality of the

6af5c44d-c4bb-491e-a60c-a47cbdc56a64-3
00:33:10.101 --> 00:33:11.679
lower density material.

08bd19f7-0c9c-4681-a78f-ce168aaa9e25-0
00:33:12.040 --> 00:33:16.966
We do have some kind of software
algorithms that we can do after the scan

08bd19f7-0c9c-4681-a78f-ce168aaa9e25-1
00:33:16.966 --> 00:33:21.160
to help minimize any,
any noise and stuff in the lower density

08bd19f7-0c9c-4681-a78f-ce168aaa9e25-2
00:33:21.160 --> 00:33:21.760
material.

af994ea5-1b9f-4594-b9c1-b14d3b525ca9-0
00:33:22.200 --> 00:33:23.640
But there it won't be perfect.

7aa2ce68-6dfe-429b-888e-410e9ddb6103-0
00:33:23.640 --> 00:33:28.280
It'll it'll still have a little bit of
noise, but that's usually only in the 3D.

cd53c2e7-a6a1-40ef-be67-5f79f1a1a140-0
00:33:28.280 --> 00:33:32.129
If we're looking at at, you know,
2D intersections like in that my VGL

cd53c2e7-a6a1-40ef-be67-5f79f1a1a140-1
00:33:32.129 --> 00:33:35.600
software for kind of parsing through a
part section by section.

584c7b9d-2fe1-46d4-b949-ada62d2c0d6e-0
00:33:36.160 --> 00:33:40.630
We do get much higher visual fidelity in
the the 2D versus the 3D for multi

584c7b9d-2fe1-46d4-b949-ada62d2c0d6e-1
00:33:40.630 --> 00:33:41.160
material.

00d724b6-1f34-412f-ab4c-3fe4cd36d440-0
00:33:42.200 --> 00:33:45.927
I would say stay tuned on that because we
are acquiring some techniques that will

00d724b6-1f34-412f-ab4c-3fe4cd36d440-1
00:33:45.927 --> 00:33:48.200
allow us to have more control over the
data sets.

05786731-6f57-4419-aa30-05730d2ca121-0
00:33:48.200 --> 00:33:52.680
So we soon hope to be able to produce
cleaner and cleaner data sets.

4b4fb601-022f-45e6-9be4-d9ea87d61930-0
00:33:52.680 --> 00:33:56.920
So when it comes to mixed material,
separate those materials out a little

4b4fb601-022f-45e6-9be4-d9ea87d61930-1
00:33:56.920 --> 00:33:58.640
better than than we have been.

e4368923-2d29-443b-b8d3-bf40791b6f74-0
00:33:59.880 --> 00:34:01.560
Sounds like another good webinar.

9dd03714-cf08-4bc8-aabd-abddb6dfa03c-0
00:34:02.160 --> 00:34:03.880
Yeah, could be, could be.

b074c025-d908-4be4-9673-ba90e8967966-0
00:34:05.800 --> 00:34:06.320
All right.

ec389eb2-f33b-4699-b321-973840f9a4fb-0
00:34:06.320 --> 00:34:09.807
Well,
if there aren't any more questions or any

ec389eb2-f33b-4699-b321-973840f9a4fb-1
00:34:09.807 --> 00:34:13.440
final thoughts,
we can go ahead and wrap this up.

05d53142-b15c-4896-a06d-38ebde81db9b-0
00:34:13.800 --> 00:34:17.200
I want to thank everyone for joining us
and thank you for your time.

8985ba92-4471-4714-85ba-3020aa90f1a1-0
00:34:18.120 --> 00:34:20.800
And I look forward to doing more of these
in the future.

8b2feac5-ac2f-485a-b0ff-845bbe47ac8b-0
00:34:23.640 --> 00:34:24.560
Thank you again, folks.

cc9667d1-2baf-4fa4-b185-082be26803fe-0
00:34:24.760 --> 00:34:25.520
Yeah, thanks, everybody.

00:34:26.080 --> 00:34:28.040
All right, have a good day.