AAH #740 - Is Automation the Answer for US Auto Manufacturing?

TOPIC: Robotics PANEL: Mike Cicco, Fanuc Robotics; Steve Plumb, Manufacturing Engineering; Brett Smith, Industry Expert; Gary Vasilash, shinymetalboxes.net

Episode Transcript

Speaker 1 (00:00):
This is out of line, after hours, unscripted, uncensored, unapproved.

Speaker 2 (00:09):
Hey everybody, thanks for joining us today. Our special guest
today is Mike Cicco, who is the President and CEO
of fanoic America. Now, we had Mike on the show
back in September of twenty nineteen. The world has changed
immensely since twenty nineteen, and we want to get into
it with you about automation and its effects on how

(00:33):
we can become more productive in the United States. And
so joining me for this discussion and conversation is Steve Plum,
who is the editor in chief of Manufacturing Engineering Magazine.
Thanks for joining us, Steve, and our old friend, researcher
extraordinary Brett Smith, old old friend. So all right, So, Mike,

(00:56):
in the years since we've had you on the show,
give us a snapshot of the change of robotics. I mean,
what's going on there where we at now?

Speaker 3 (01:05):
And then we'll well, I'll tell you it's like, where
do we begin with that? Twenty nineteen It seems like
it seems like a lifetime ago, doesn't it. We had COVID,
we had supply chained. Now we have a tea word
that we're probably not going to talk about today, but
a lot's been happening in robotics since then. You know,

(01:26):
robotics have been around for a long time, within twenty nineteen,
but really since then, I think one of the biggest
areas that we've seen is the adoption of robots amongst
such a broader array of new businesses and new industries,
even including automotive. A lot of people would say that
automotive is the most automated out of the industries, which

(01:47):
it is and has been, but we're even finding new
ways to automate within automotive, and a lot of that
is because of what happened with the workforce through COVID,
through supply chain, and as manufacturers have become more willing
to give automation a try, we've seen the adoption rates
of robots really really increase across a lot of different industries.

(02:08):
And we can touch on that.

Speaker 2 (02:09):
So basically, auto is about a third of all the
robots sold in the United States.

Speaker 3 (02:16):
No, auto is about half of the robots that are
sold in the United States right now. Yeah, it's about
it's about half. The last year, the last couple of
years was the first time ever that non auto actually
eclipsed auto, but only slightly that that non automotive was
that But the last few years now it's about been

(02:36):
equal about fifty to fifty. But I see that changing
where the non automotive side of our business is growing
at a pace that's going to continue to eclipse auto.
So I think in the future you're going to see
auto remain strong. It's still a very huge industry for
us for robotics, but I think a lot of the
non automotive business is going to continue to grow.

Speaker 4 (02:57):
What non automotive sectors are growing and why.

Speaker 3 (03:00):
That's a great question too. I'll run down the list
of some of the biggest ones right now. E commerce
is probably the fastest growing one because it's growing from
nothing that you know, the inside of a warehouse. And
when I say e commerce, it's not just you know,
buying stuff and receiving it just like you would on
e commerce, but this is also any sort of things

(03:21):
in a warehouse. And this exists even in automotive, where
you have warehouses full and full of goods. And right
now there's just a lot of people that drive pork
trucks around and are very inefficiently kind of gathering goods
from various spots and putting them into boxes and shipping
them to people, and so that's a big one in
terms of automation. Another recent one is whatuld you call

(03:44):
primary food, So that's touching raw food. Secondary food is
when it's already in a package, but it's not yet
in a box, and then secondary packaging is when it's
already in a box. So touching primary food something that
COVID really grew quite a bit because of the point

(04:06):
about having people really close together and then people touching
your raw food and food borne illnesses and diseases and
things like that, and so there's been a pretty big
push to automate that.

Speaker 1 (04:17):
How much crossover is there between industries you talk about
that primary foods versato, But are there applications that the
same robot can basically they perform.

Speaker 3 (04:29):
There are a lot of applications where you have, say
the same size robot, where say you have a robot
that's the size of my arm that can be used
in automotive in various areas, and it can also be
used in primary food. But for a robot that needs
to go into primary food, they actually like an automotive,
you work a three shift day. So like in a
big plant, they'd work all three shifts, and primary food

(04:52):
you work two shifts and then the third shift is
just for cleaning. So they literally take the whole plant apart,
bit by bit and then clean everything and then start over.
And so the the the way that robot is made,
it's the same size and it's and it works the
same way, but it would have a lot more stainless steel,
it needs the lubricants on the inside of it have

(05:13):
to be rated for food, and so it's it's different
in a way, but it's basically the same size.

Speaker 2 (05:18):
So so Mike, here you mentioned a robot about the
size of your arm. Now, now you guys, make a
robot that can pick up a car, literally pick it
up and move it around. You know, give us give
us a sense of what robots can do. I mean
we we often just you know, think, oh, robot, but
we don't know what that is about.

Speaker 3 (05:38):
Yeah, that's a good that's a good question too. Uh,
it's grown quite a bit. Where when when when robots
first got invented, really, they they took they took something.
The reason why they call it a robot arm because
it was generally shaped like a person's arm, right, or
it was really size like the person's bodies to do
various tasks. And then as time went on, we realized

(05:58):
that we could make them a lot small to do
really smaller complex things, and we can make them bigger
and in this case really big, where now we can
pick up over two tons of weight with a robot
that's constructed in the same way. And so really it's
it's it's all what your mind can imagine a robot
could do. We have everything now in agriculture, there's robots

(06:20):
that are out picking tomatoes and strawberries out in fields
all the way to what like what you said in
some of the car plants, where they used to say
you had a like what used to be a hard
automated elevator where you you'd be assembling the car and
then you'd go from where it elevates up to where
you're working on the bottom and you're working on the top.

(06:40):
That's almost all automated with robots now, because we have
robots big enough they can literally pick up a car
and move it around. So we categorize robots into whether
they weld, they paint, they assemble, they handle, or they
we say palletize or they stack boxes, they can move material.

(07:01):
Now there's additive manufacturing where they can add material. So
we start to break down each of those different applications.
So there's different applications all of those, like I said,
and then there's different industries, and that's what I was
getting into. In terms of food and pharma and agriculture.

Speaker 1 (07:17):
You mentioned some uses welding, painting are the common ones
we all know about, but what are the fastest growing
and some of the unique applications out there.

Speaker 3 (07:29):
I would say this is one of the fastest growing ones.
Now this involves automated or artificial intelligence. Would be previous,
let me rewind previously in terms of a robot, you
would traditionally teach the robot. So if you wanted to
go pick this thing up over here and move it
over here, and it would always do the same thing.

(07:50):
One of the fastest growing things is where that robot
using cameras and AI, it would actually seize this environment
and a different brain for the robot really tells it
what to do dynamically, so it's not the motion of
the robots not fixed. It's totally dynamics. So for example,

(08:12):
you are you're trying to take material off of a
component that you're going to you know that just got
machined or something, and that component's in a different location,
you might see that, and then the robot is going
to dynamically change it's its positions based on what it
perceives in the in the in the environment. And so
that's a really new and kind of growing area where

(08:34):
we have a lot of high end software that tells.

Speaker 1 (08:37):
The robot what to do, like a lot does it
take to train the robot to do that task?

Speaker 3 (08:43):
Well, that's the big that's the beauty of it really
is what we're trying to get towards, is that we
want to bring down the skill level that it takes
to program the robots in the first place, and maybe
more importantly, bring down the time it takes to do
all those And so in some way you could say
that it doesn't take any time at all because the
robot already knew what it was going to do and

(09:05):
there's no teaching at all. It just it just it
just did it once when it saw the part.

Speaker 1 (09:09):
So we're almost to that point of out of the
box where you know, plug it in and it goes.

Speaker 3 (09:15):
That's exactly right that that's in many cases that's already happening,
and then we're trying to push that further down the
line and a lot new a lot of new applications.

Speaker 2 (09:24):
So one of the things since twenty nineteen, it seems
to me that has been a big change is the
collaborative robot cobot. So for our audience that don't know
what one of those is, give us an explanation and
why they would be important in an auto plant.

Speaker 3 (09:42):
That's a great that's a great question. Cobots or collaborative robots.
The word cobot or collaborative robot is really intended to
talk about how that particular robot is made. So in
a collaborative robot or the way a collaborative robot is
made is there's sensors that are kind of built into
the robot itself so that as the robot's moving around,

(10:05):
if the robot feels any external force, it stops. And
in that case, there's a big safety standard that is
published that says that then that robot is actually safe
to work alongside a person, because if the person ever
touches it, then the robot stops. There's a whole extra
layer of safety about that. So, like we always use

(10:27):
the example if the robot is holding a knife, like,
it's not safe no matter what, even if it stops,
if it touched you, you can't. It's true, Yeah, you
worry about that. What that has done since twenty nineteen
is that has really changed how we apply robots and
where we can put robots, and more importantly, how we

(10:50):
interact with the workers inside of a factory. We're previous
to this. In many cases you had to segregate the
robots and the people with big fence is and big
areas where you decided, I'm going to do this robot
thing over here. Well, maybe I'll do the robot thing
over here, and then you're going to do your person
thing over there, and we're separated by a big area.

(11:11):
And in that case, it made the plant really big,
and it sometimes made it inefficient because you couldn't mix
those two things together. You had to decide all the
stuff the robot can do and all the stuff the
person can do, and then you had to separate them. Now,
with collaborative robots, what you can do is you can
bring all of that closer together. So say I was
say I was doing something on this on this you know,

(11:36):
this cup holder, and then but you needed to do
something on it too. So I'm the robot and I'm
doing something robotic, and then I can literally just put
it here and then you can take it and do
the person thing on it, and then you can move
it down there and or another robot can do it,
and everyone's just standing next to each other, and everyone's
doing the things that they're best at. So there's things
that robots are best at, there's things that people are

(11:57):
best at, and now it can all happen in the
same space.

Speaker 4 (12:00):
So this is a perfect lead. And then the follow
up question of you've got robots, cobots and humanoid robots
can bring Yeah.

Speaker 2 (12:09):
Sorry, John's I was waiting for you to ask the question.

Speaker 3 (12:14):
Just a popular topic. We always see you guys talk
about his humanoids.

Speaker 4 (12:17):
Yes, it's a fascinating one for made some people a
lot of money without making any but it's true. So first,
kind of your perspective on on that transition, and and
then why would a bipedal robot be better than something else?

Speaker 3 (12:33):
Yeah, so I'll give you my personal opinion. So speaking
from my Chico personal opinion, Uh, I don't think that
a bipedal robot is better.

Speaker 2 (12:43):
I don't save that on the tape. I want to
play that for John. I agree, I want you to
stay forever.

Speaker 3 (12:53):
I thought, uh My, The way I expec laye it
is is that, however you want to think about how
we are made, whether it's God or evolution or whatever,
but we're made. Our bodies are made to do an
infinite number of things where I can drive a car,

(13:14):
and I can pick up that water bottle, and I
can point and articulate, and so our bodies are made
to do an infinite number of things. And when you
get into automation, you don't need to do an infinite
number of things. Now you have to do a finite
number of things. Now that finite number of things might
be a thousand things, but it's still finite. And so

(13:36):
the idea of trying to recreate a human body that
can do an infinite number of things where you never
need the automation to do that, they should do a
finite number of things. We strongly feel that we can
use more traditional automation. That is, that is not to
say that it's hard, because our automation hard meeting fixed

(13:58):
or or limited. We're making extremely flexible automation today. But
for example, if I wanted to pick up that water
bottle and that coaster, I wouldn't necessarily make something that
has five fingers to be able to do that. I
might make a very unique thing, one thing that has

(14:20):
a suction cup that shoots out of the center of
my hand, and one thing that has a gripper. So
I could do this and I could suck it up,
and so now I can really invent all these different
ways to do what I need to do. And you
start to see some companies do that, and then when
you get to bipedal, I mean wheels and tank treads,
and I mean just seems logical, there's way better ways

(14:42):
to do that.

Speaker 5 (14:43):
Not the smartest guy in the room, but it seems
as far as the integration with the workforce, are there
advantages or disadvantages of going with a bipedal modle.

Speaker 3 (14:55):
I think why people are so enthralled with it is
because you can see it in your mind, and you
can see it very clearly as a replacement the person
was doing this. I'm going to make something where that
the person was doing that. And then as you move
away from that, then you have to start really thinking
differently about your manufacturing process. So with collaborative robots, we

(15:16):
do feel like there's better ways to do that. So
you can have a fixed mounted robot, so it sits
on the ground and it doesn't move. But now you
can put a robot on top of a mobile robot,
like another robot that drives around autonomously, and now you
can kind of walk around like a person, and you
can put two robots on there if you need two arms.
You can put three robots on there, if you need

(15:37):
three arms. Not that a three armed person exists, but
you could do that as well, And so we really
want to look at that differently and more. Maybe the
key part of it is we're working now with the
automotive companies to rethink manufacturing again, maybe for the first
really subsistence substantial time in a long time, where let's

(15:58):
start to design things for automation so that so that
we can it's not about people reduction really at all.
It's about making everything more efficient so that the people
don't have to walk around as much and they don't
have as many hand and neck and back injuries. And
we're just trying to make everybody more efficient and so

(16:19):
I think more than ever now people are starting to
really rethink how we manufacture, how the manufacturing's done. Where
previously it was there wasn't much paid to automation.

Speaker 2 (16:31):
So basically, if we think about it that, you know,
the assembly line gets created and as time goes on,
it gets improved by things being tacked onto it. Right
that suddenly you go from a situation where you know
you have instead of ropes moving vehicles down the line,
you have a machine that is powering that moving it
down the line. Then we get to the point when

(16:52):
robots come in in the early sixties and begin building out.
But then it's just like we can stick one there
on the line, you know, and I mean it's it's
not designed for using the equipment and the automation to
its utmost. It's sort of a cluge of over time.

(17:14):
So you're suggesting that maybe now car companies are saying, hey,
what can we do with this stuff? And maybe the
way we go about it will be different.

Speaker 3 (17:21):
That's right. Yeah, So example, you know, we didn't have
to think about it before, but you get to a
point where there's a box justice just a complete jumble
of parts and they're all tangled up and the people
that are there sitting there untangling things or you know,
sorting things. And it kind of worked before because you
didn't really have to worry about it. But what if
you had a robot upstream that was organizing all that stuff,

(17:43):
And so now the person has something that's completely organized
for them, that is presented to them in a way
that now it makes their job extremely efficient. And what
that does and you speed up the line a little
bit faster and get more cars out at the end,
and every inch of floor base becomes more efficient and
things like that. So I think that's a lot of

(18:05):
where the industry is headed, where we're rethinking some of
those things.

Speaker 2 (18:10):
So according to the International Federation of Robotics that the
United States has two hundred and ninety five robots per
ten thousand employees. Meanwhile Germany has four hundred and twenty nine,
which is pretty good number, China four seventy, Korea one
thy and twelve. How do you explain we've got to

(18:33):
ninety five and Korea's got a thousand.

Speaker 3 (18:36):
Sure some of that. So to clarify the stat that's
how many robots are used by per manufacturing employees. So
that's how many people in manufacturing, and those numbers get
skewed quite a bit, but by how many industries are
considered manufacturing in your country. So if you start to

(18:57):
segregate out just automotive, it starts to normalize the numbers
quite a bit. Where for the most part globally, between
China and Germany and Korea, we're all in the US,
we're all really using a pretty pretty normalized amount of
robots in automotive. Some of that is because of actually

(19:18):
how much manufacturing we still do, not that if you
read the newspaper today, you'd feel that we do as
much as we do, but we do a lot, but
a lot of that still doesn't use as much automation
as is used in the automotive business, and so there's
still a fair share of you know, the human to

(19:38):
robot ratio is still a little bit different. Where you
look at some of those other countries, their industry, their
manufacturing is a little bit more primarily either in like
Korea in particular electronics and automotive, and so that those
are very highly automated now. And so you see that
China is a little bit I mean, it's not surprising,
it's just impressive. Maybe more than anything, because they still

(20:00):
have a lot of really non automated manufacturing businesses as well,
like furniture and fabric and things like that. So I
see that as a positive thing for us because it
means that we still have a lot of improving to do,
and in today's climate, there is a lot more acceptance
and emphasis on all of this being good and okay.

(20:24):
And we continue to work to teach young people that
manufacturing is cool and you can make a lot of
money doing it, and you get to program robots or
you get to fix robots, or you get to design robots,
and it's all really cool. And so we have a
big emphasis on that and has.

Speaker 4 (20:43):
A pretty strong academy or training program. Can you talk
about that as we get into a more jobs in
America kind of idea, we're going to have to find
ways to get people into those spaces. I've spent thirty
years of my career and that labored discussion on training,
education and such, yep, And it always comes back to

(21:03):
a lot of folks don't want to work in plants.

Speaker 3 (21:06):
Yeah, yeah, And I think that's something that COVID when
we were talking about what's changed since twenty nineteen COVID
took a lot of people out of manufacturing, whether they
switched careers all together, they retired, or god forbid, passed
away during COVID, but it fundamentally changed how many workers
we had in manufacturing. It accelerated something we've been talking
about for a long time is that there's a lack

(21:27):
of skilled labor in manufacturing, and it just ramped it up.
We sensed that, we realized that a long time ago,
so since two thousand and say ten, timeframe where we
really started to lean in heavily. We recognized that we
needed to, in basic terms, bring back shop class into
high schools and community colleges. But it was around advanced automation.

(21:52):
So it's still shop class, but instead of teaching woodworking
and things like that, we brought robots into schools and
SEE and C machines into schools, and we're teaching the
next generation of worker. All of these things really trying
to reshape the mindset of what manufacturing is and what
it looks like and what it could be. And so

(22:14):
today I'll break the education piece into two pieces. One
is new workers that are coming into manufacturing, and from
that regard, we have now placed robots or automation SEE
and C machines into sixteen hundred different schools just in
North America, including over four thousand products robots and C

(22:35):
and C machines. This is mostly in community colleges. That's
the number one percentage. Second is high schools, with universities
being the smallest piece of that. And so we're really
focused on looking at the next generation of worker and
then so those kids are coming out with those kinds
of skills.

Speaker 2 (22:53):
So, Okay, a lot of discussion going on about bringing
more manufacturing in the United States. I think we can
pretty much all agree that there may be a problem
in getting those jobs filled, given that we basically have
full employment right now, right, I mean, it's not like
there a whole lot of people not working. So my

(23:15):
question to you is, to what extent can robotics help
generate the sort of manufacturing capability that people are seeking.

Speaker 3 (23:28):
I think two ways. Number one by bringing manufacturing back
to the US, which I think is a good idea.
I think we have lost a lot of things that
we should be manufacturing here and that this is a
very good effort that we should be bringing manufacturing to
the US. But we can't do it. We can't manufacture
things in the same way that they're done in low

(23:49):
wage nations. It's just the math doesn't work out to
be able to do that, and none of us are
going to be willing to pay for what it would
cost have we made it that way. So we need
robots to help that. We need to supplement the lay
so that we can make things with an efficiency where
we can try to keep the cost at the same
that it's made in other areas. What I hope is
going to happen is is all of these training efforts

(24:10):
that we're doing, and we're talking about with four thousand robots,
we're training hundreds of thousands of kids now that are
seeing a robot in high school each year, that that
problem that we have of lack of people is going
to then change, and so now we have more people
that are going to want to get into this. Secondarily,
I see that if now we start to see that
manufacturing isn't the thing that people don't want to do,

(24:33):
it's the thing that people want to do because it
is cutting edge and cool and not super dirty and
dangerous and all that stuff. That we see people starting
to shift from other industries that maybe they thought were
a better place to go and then come back to
manufacturing or try manufacturing. And in that case, we have
training classes. We have training centers all over the United

(24:55):
States within FANIC that we use in addition to the schools.

Speaker 4 (24:59):
So those words sound so familiar to me thirty years ago. Okay,
same words I used in reports and discussions with governments.
What are the skill sets now that you need to
convey to these people. These are the things you can
do that are useful but also engaging.

Speaker 3 (25:20):
I tell people this as an example. I have a
bachelor's I have an engineering degree in electrical engineering. I
went to a school called Bucknell University in Pennsylvania. What
I learned in school to do my job. I started
PANIC as an electrical engineer. I programmed robots when I
started PANIC. The skills that I used to start my career.

(25:41):
At FANIC, they're currently teaching sophomores in high school and
I have a bachelor of Science and electrical engineering. So
I will say that the skills required is a basic
level of math and then a passion or a desire
to really utilize or harm it kind of hone in
on those skills. So we're not talking about a huge

(26:02):
barrier that now we are we are still developing some
of the greatest AI minds at you know, at Berkeley
and MIT and Carnegie Mellon and some of the really
University of Michigan in particular, really high end robotic schools.
But to bring people back into manufacturing, we're looking at
high school graduates and community college graduates and and it's

(26:24):
it's a fundamental understanding of robot programming. But it's not difficult.
We're not there's a mindset that maybe it is and
it's not.

Speaker 1 (26:33):
So how fast are things progressing? Robotics isn't a new field,
but it's still high tech, especially as you get into
AI machine learning. What's the development cycle and how far
are you looking at? How far? How quickly do things
become obsolete?

Speaker 3 (26:50):
Yeah, we were talking before we came in here that
you know, the first bit of the robotics renaissance in
the eighties, we saw this huge beginning adoption and it
kind of leveled off for a while and we're in
the second wave of that where the business is growing exponentially.

Speaker 4 (27:04):
Now, what is that growth, what's causing that spurt?

Speaker 3 (27:08):
Well, it's the thing that we've been talking about for
twenty years of that there's a lack of skilled labor
in the marketplace, that it's finally hitting now and everyone's realizing,
oh my gosh, I can't find people, and so the
conversation of robots takes jobs away. That story it doesn't
really exist. We've been saying it doesn't exist for a
long time, but now people are really starting to realize

(27:28):
it doesn't exist because people are actually experiencing job growth
and a rebirth of manufacturing.

Speaker 4 (27:37):
Parallel with the cost of robotics has come down, but
the capabilities have gone.

Speaker 3 (27:42):
That's right too. Yeah, that's right too.

Speaker 1 (27:44):
So the Deloitte studied the last year of the one
point eight million of manufacturing job shortage by twenty thirty
or so. I don't know how much that took into
increased adoption of automation. Maybe you would know, But how
much can automation offset that? And where do you see

(28:05):
it going? Carol mentioned two hundred and sixty five robots
per person per worker. Where do you see that going
in the future.

Speaker 3 (28:14):
Yeah, I see that continuing to grow. For sure, it's grown.
If you look at the history of that number over time,
it hasn't grown as fast as I've wanted it to,
but it's grown. It's growing around the world as well,
so it's not just here, it's growing around the world too.
So those things are all going to continue to happen.

Speaker 4 (28:30):
That the.

Speaker 3 (28:32):
Technology within the robots, how much the robot can do,
is going to get better. They're going to continue to
be more cost effective, and we're going to continue to
see that growth, and we're going to continue to touch
industries that we never have seen before. And I really
do feel that it's going to continue.

Speaker 2 (28:50):
So what do you say to somebody who is in
a trade union who wants jobs for people, and you say, well,
you know, robots can help, and that person says a
word that I will not send in the air.

Speaker 3 (29:07):
So I think that to that, we really need to
focus on a re education of the existing workforce. I
really wanted to touch on that, so I'm not just
talking about kids in school that are coming into manufacturing.
It's an important part of the solution, but maybe a
more important part of the solution is the re education
of the existing workforce that's out there and the barrier

(29:28):
to do that, and how do we educate someone that's
been doing something for a very long time and try
to teach a new skill, and that is a big challenge.
I'm not going to sugarcoat that it's not a big challenge,
but it's something we need to focus on and have
efforts to retrain that that workforce so that we can
go to those areas and say there is this opportunity

(29:49):
and if you learn this skill, then you can make
this much. And if you learn this skill, then you
can make this much, and there's a ratcheting up effect
I think in the pace scale too.

Speaker 2 (29:57):
So do you see this as being a public private
partnership that's necessary to get this done? Or I mean,
so I'm running a plant for General Motors. I think
that the people need to be retrained. Is this my
responsibility or do I say, kayfanic or fill in the blank,
should you come do this? Or does the government say, hey,

(30:20):
this is important that we have manufacturer. We need to
train these people. Therefore we need to in some way,
shape or form subsidize this.

Speaker 3 (30:26):
I think it's all of it, to be honest, I
really wish if I if I were to have a
stronger voice in Washington, I'd say that we absolutely need
government programs to help further educate existing manufacturing workers on
that and some states are doing it out of their
own state funds. Alabama in particular, has an amazing program

(30:47):
where anybody that lives in the state of Alabama can
go take robotics training for free and it's a wonderful facility,
all paid for by the state. So at the state
level and then public private partnerships within the school level,
we're playing those games all the time, not really gain
we're we're creating those connections all the time. Where someone
comes to the phrase I hear a lot is is Mike,

(31:10):
we want to we want to start our automation journey.
That that's what That's a really popular thing I hear.
Now a customer will come to us and say that.
And the first thing I'll do is say, where's your
plant and what community colleges are around that plant, and
let's make some connections so that every new employee that
you hire should come from that school and that then
that helps everybody.

Speaker 4 (31:31):
So for a community college that has multiple plants, multiple
different companies operating in their space, how do you provide
the resources for each plant individually or do you provide
that base level and then the plants take that responsibility.

Speaker 3 (31:47):
Then the plants we do at the base level, so
the community colleges do a really wonderful job kind of
understanding how much industries around them, and they can scale
much faster than at the university level. And so if
two more plants pop up in the area, well they
double or triple the size of the robotics training that
they do and and now they can they can educate, but.

Speaker 4 (32:08):
It's it's more of a core level training and then
going to the on the job training or company training
specific that's correct.

Speaker 3 (32:14):
Yeah, we create stackable training, so you have base level
and then you have maybe like you start adding PLC
and control work, and then you had cameras and vision
work and IoT but it's all at a common level.
So then if you want to go, you know, uh
to a chicken plant, or if you want to go
to a car company, or if you want to go
to an e commerce company, you have that baseline skill.

(32:36):
And it's all accredited too. So the training that we
offer is all accredited, so it's a certificate that they
can use then within uh, within their resume and things
like that.

Speaker 2 (32:45):
All right, so final question, Okay, I have you back
on in six years where will we be.

Speaker 3 (32:51):
Maybe I'm going to be a robot here, No, I
think six years. I think we're going to We're going
to continue you to see how I guess AI or
artificial intelligence is going to make robots easier and easier
to implement. That the barrier of entry is going to
come down so much that we're going to be able

(33:14):
to place robots into areas and and I don't know,
for lack of a better word, they're going to figure
out what they need to do on their own. That's
that's not exactly where we are today, but I think
that that's where we're heading is is that that the
robots are going to start being able to not think
for themselves is not the right word, but be pre
trained ahead of time to know that you can you
can put a robot in and have it be functional

(33:35):
very very quickly without a big, drawn out process.

Speaker 1 (33:37):
As long as they remember that first rollover robot.

Speaker 3 (33:40):
That's right. Yeah, yeah, yeah, that's not getting broken.

Speaker 2 (33:43):
They're not that smart, all right, Mike Sicco.

Speaker 3 (33:45):
All right, nice to see you guys coming all right,
Absolutely sounds good. Enjoy the rest of the talk.

Speaker 2 (33:51):
Thank you, okay, And I would say we're back, except
we never stopped, so we keep going, all right. So
I was delighted to hear him say that bipedeld robots
are not the future, despite the fact that we heard
Elon Musk say this week that he is going to

(34:12):
have his plants full of Optimist robots. So, Steve, as
a manufacturing guy, what do you think about that?

Speaker 1 (34:20):
So unprompted, I was on a call immediately before those
about a panel discussion or upcoming regional show, and one
of the panelists mentioned Optimists specifically and said, you would
consider it. He admitted that I think the current price

(34:41):
is like forty thousand dollars is what they're talking about.
He said it'd probably be twice at at least, but
I don't know. I didn't have a chance to follow
up on why he would be interested in that a robot.

Speaker 2 (34:53):
That just strikes me that it's sort of a novelty act.
It's like in the early days of robotics that companies
used to buy robots the stick them in their lobby,
so then people would come in and say, who, you
must be advanced, you have a robot. I mean, the
thing wasn't doing anything, but.

Speaker 4 (35:06):
It's hard to deny that Elan is really smart and
it's really good at creating futures. But this one I
don't understand why other than it's really cool. There are
certain very very small narrow ranges. Okay, that makes sense,
but as as Mike pointed out, stability, moveability, things that

(35:30):
we do sort of naturally well, but not as well
as some other things.

Speaker 1 (35:34):
Right, I could possibly see some sort of high broad
but you know, why recreate a human?

Speaker 4 (35:40):
Why so?

Speaker 2 (35:41):
In more interesting news, Tesla's revenue in Q one fell
nine percent year over year. It's profit was down seventy
one percent. The company blamed a sharp decline in vehicle deliveries,
partly tied to its model why redesign for the disappointing results.
Do you guys think that is the cause of the
disappointing results?

Speaker 4 (36:02):
I got in trouble last time trouble, But.

Speaker 1 (36:06):
Weren't sales down last year for Tesla? Didn't they have
a one percent the first.

Speaker 2 (36:12):
About the first quarter? We're starting fresh?

Speaker 1 (36:16):
I would say no, that was not the only reason.
In fact, profits were even less or in the negative
if you took out the credits that.

Speaker 2 (36:25):
The credits they sell for carbon emissions, so get in trouble.
Bret's say something.

Speaker 4 (36:31):
I think clearly they've got a brand issue. They also
are going through a change in transitioning product that makes
a difference, but they've clearly got a brand issue, and
they're also facing a lot more competition. Exactly, it's going
to be a lot tougher ands if you look at
it from the outside, you look at they talked about

(36:53):
the model too is they was being referenced being this
low cost, high volume thing where the Chinese play. It's
gonna be tough to play in that market. So that
went away. Now it's kind of just a read decontented
Model three, which means less profit per vehicle. Even if
they do sell them, it's going to be a tough time.

(37:15):
You know what. They remind me of a car company,
just a good old fashioned car company.

Speaker 2 (37:21):
So expand on that a little bit. You just can't
say it's like a good old fashion car.

Speaker 4 (37:28):
They're they're they're facing competition, they're facing cost pressures, and
they're facing this idea that maybe there are other alternatives competition.
But it's all of a sudden when you stop talking
about full self driving, when you stop talking about human robots,
all of these things and just look at the automotive

(37:48):
part of it. It's an automotive company, and that's kind
of where we all thought it would end up at
some point because the other stuff is you know, he.

Speaker 2 (37:56):
Says it's an AI company, so by your time.

Speaker 4 (38:00):
AI company, all of those. Again, dude has a phenomenal
track record, but it's tough to build cars in this market,
in any market.

Speaker 1 (38:11):
Yeah, maintaining market share was untunnable. I mean, he had
so much for so long because they were almost the
only player in town. But as you mentioned, new companies
coming in new models. So I saw stat sixty three
sixty five evs offered last year in the US, Twenty

(38:33):
five percent of them were new from a year before.
That didn't exist prior to that. So of course they're
going to lose out. And as you noted, as as
you ramp up production, have more more diverse models, you're
going to get more recalls, have more problems.

Speaker 4 (38:50):
What he's done politically probably doesn't help though.

Speaker 1 (38:54):
How about that is that but he did say that
he's going to spend more time at Tesla is only
I'm only going to spend two days a week working
on the government a third all.

Speaker 2 (39:05):
Right, But if if if we go to what Brett
is saying that it's it's pretty much a car company.
I mean, on the earnings call, they talked about the
unboxed assembly, which is you know and and but it
wasn't flushed out so much. It was just basically, make
a car every five seconds. Well, okay, you can make
a car every five seconds, but if nobody's buying your cars,
you got a slight problem there. You certainly have you know,

(39:28):
big inventory, So you know, I think your point is
well taken that it is just becoming a car company, a.

Speaker 4 (39:37):
Very innovative car company, a company that pushes the envelope,
which is really good for the industry in a lot
of ways.

Speaker 1 (39:43):
In addition to two humanoid robots, most Costles said that
they wanted to focus on automated vehicles too.

Speaker 2 (39:55):
And right and how they're driving themselves out of the
robot it sort of thing.

Speaker 4 (40:00):
There are I think there are actually other vehicle manufacturers
whose vehicles can drive out of the planet. You know,
they probably don't talk about as much because they don't
want to bump up their stock.

Speaker 2 (40:11):
I don't know what, or they don't think it's a
big deal.

Speaker 4 (40:14):
Maybe that's it.

Speaker 1 (40:15):
Yeah, do the tariffs actually help TESLA once they produce more.
A lot of the other evs are still being imported,
you know.

Speaker 2 (40:28):
Well, I mean even even Elon admitted on the call
that you know, not everything is from here. I mean,
they're highly vertically integrated. But you know, components come from
other places, right, And you know, I think people lose
sight of the fact that, you know, if you're building
a car, you need all the pieces, you know what

(40:50):
I mean. It's just like you can't leave that one out.

Speaker 4 (40:53):
The old story of just down the airport down here
in Detroit, there was a big group of one navigators
sitting there without seats. Can't drive off with those seats.

Speaker 2 (41:02):
They have a problem, right, And so you know they
will have to pay the tariff. They won't have to
pay as much as companies that are are you know,
having to pay the full vote. But you know this
this I sort of wonder. I mean, so yesterday President
Trump was talking about, you know, increasing the tariff on
vehicles that come from Canada, and he said, and I

(41:25):
want to find this so I quote this accurately because
it would.

Speaker 4 (41:32):
You don't want to misquote the president.

Speaker 2 (41:34):
Well, you could I put tariffs on Canada. They're paying
twenty five percent, but that could go up in terms
of cars when we put tariffs on All we are
doing is we are saying, quote, we don't want your
cars in all due respect. Okay, so the thing I
sort of wonder about is that we don't want your cars. Well,

(41:56):
aren't those cars like cars that are being made by
I don't know, General Motors Ford.

Speaker 4 (42:04):
I mean, Toyota's got a pretty good investment in North
America in US.

Speaker 2 (42:07):
And they build cars if they're Hondas.

Speaker 4 (42:10):
Four is kind of a big car, small big car, right,
So interesting.

Speaker 1 (42:15):
There's kind of an ongoing war words with the administration
and BMW in South Carolina saying that you know, it's
all smoking mirrors, that BMW is just assembling things, that
all all the content comes from from overseas, and all
the South Carolina governor all the officials really hit back

(42:39):
hard on that.

Speaker 2 (42:40):
Well, I mean, it's it's the biggest SUV plant that
BMW has in the world, you know, big, big, big investment, and.

Speaker 1 (42:49):
They poured billions of dollars into into the state to
employ many people.

Speaker 4 (42:55):
We can leave it here and realize that we're not
going to solve this industry's got mis challenge ahead.

Speaker 2 (43:01):
Well, so we had one of your former colleagues, Edgar Feller,
on the show three because I believe it was and
he had done a study which he could only hint
ad for us, and the numbers came out this he
would even share it with me right now they're out?

Speaker 1 (43:17):
Now?

Speaker 4 (43:18):
Would he still won't give it to me?

Speaker 2 (43:20):
Now? We won't really? Obviously you pissed him off somehow, Okay.
So Center for Automotive Research said the increased costs to
all US automakers as a result of the tariffs will
be one hundred and seven point seven billion dollars. And
if looked at the D three alone, so this would

(43:41):
be four General Motors a Stilantis. That's forty one point
nine billion dollars.

Speaker 1 (43:45):
So is that just this year?

Speaker 2 (43:47):
Yes? Yes, and the impact to the D three production
volume of six point eight million vehicles. Okay, Brett, we're
going to get rich.

Speaker 4 (43:56):
So what I hear? Who's we America? Richester? Well, we've
ever been how I haven't figured that part out?

Speaker 2 (44:04):
So okay, I mean seriously, so sorry you've been studying
this year. You mentioned thirty years you've been doing this
and you're looking in this auto industry, how does the
D three automakers sustain a hit of forty one point
nine billion dollars?

Speaker 4 (44:21):
First off, I think Edgar does amazing work and he
did the best he could with what he had. As
we've talked about previously, this is really a flexible moment.
Things are going back and forth so quickly. We don't
know tomorrow what's going to happen. We don't even know
what happened and now we've been in here. If it

(44:41):
is a long term, as it's been said, permanent, this
is a gut wrenching moment for the industry. It changes
the industry. There are companies that won't survive over those
five ten years. We'll see where. We'll see though that
production be back filled by others maybe, But it's a

(45:02):
transitional period for the industry if those numbers that Edgar
quotes are reasonably accurate.

Speaker 2 (45:09):
All right? Transitional? Is this like transitional like going from
your house to the funeral parlor in a box?

Speaker 4 (45:15):
Well? For some for some yes, for others, it's a
great opportunity to grow in five to ten years.

Speaker 2 (45:22):
In five to ten years, and what happens in between, then.

Speaker 4 (45:25):
Cars get more expensive choices go down again. If this
is the permanent solution, it's going to take the industry
five years to a decade to respond so fully.

Speaker 1 (45:39):
Back during the recession of two thousand and eight two
thousand and nine and the natural disasters that were happening
at the time, said okay, this is a learning moment.
The industry learned from that, we worked this supply base
became more efficient. Same thing during COVID. This is a

(45:59):
learning moment. Did the industry actually learn anything? And how
do we move forward.

Speaker 4 (46:05):
That don't end up in a box? Yes, it's I'm
not sure what the lesson is other than opening opportunity
for others, and I think understanding supply chain better. But
I'm not sure how a better supply chain can help

(46:25):
you here. This is an industry that needs scale, that
needs the volumes built regionally, not just countrywide, and even
globally at times, and to do it flip a switch
like this for an industry that invests in ten to
fifteen year cycles is really challenging.

Speaker 2 (46:45):
So okay, this sort of plays very nicely. A letter
was sent to the administration that was signed by the
heads of the Alliance for Automotive Innovation, American International Automobiler,
Automobile Dealers Association autos Drive America, of you'll, the Vehicle
Supplier Association MMA, National Automobile Dealers Association, and American Automotive

(47:06):
Policy Console, a group that.

Speaker 1 (47:08):
Basically the whole industry.

Speaker 2 (47:10):
Yeah, but usually they don't get together, right, you know,
I mean the dealers have their things, the OEMs have
their things, but they got together on this. And a
couple of quotes from that which are germane to what
you both just said. Quote, most auto suppliers are not
capitalized for an abrupt tariff induced disruption. Many are already
in distress and will face production stoppages, layoffs, and bankruptcy.

(47:32):
It only takes failure of one supplier to lead to
a shutdown of an automaker's production line. When this happens,
as it did during the pandemic, all suppliers are impacted
and all workers will lose their jobs. Ain't pretty.

Speaker 1 (47:44):
Yeah, And we don't reverse it or find some sort
of middle ground that you know, I think it's ineviilable. Uh,
that's gonna happen. We're going to go down that path.

Speaker 4 (47:55):
Three or four months ago, I sat in that chair
and said to John, who I think was sitting there.
We all think that manufacturing is bring it is a
good idea, bringing it back. We understand that over the
decades we've given up on some of those really fundamental
things for defense, for other things. But the reality is

(48:15):
it's going to be incredibly painful. It's not going to
be a we're going to get rich, everybody's the richest
you've ever been. It's going to be painful as hell.
And this is what you've just described. This is what
they've described. I go back to this part where there's
a lot of statements as to what is going to happen,
what is starting to happen, and what is permanent. But

(48:37):
the reality is is it a question is is it
really permanent? How long does it last? How much of
it's rhetoric to scare the others, how much of it's bargaining,
how much it's that sorry, you.

Speaker 1 (48:47):
Know from an economics standpoint, and you're much well more
well versed than Garrier me on those what China is
famous for their ten year plans. Other countries have these
long term pet plans. Could it and eventually, you know,
work out down the road where this is about our way.

Speaker 6 (49:13):
For our I'm sure our patience that you're sitting here
shaking like they can't see that.

Speaker 4 (49:22):
I only listened to this Andy, and so it would
be like, Okay, I'm imagine myself shaking. I think, what
the hell do I say here? It's a really, really
tough transition. I don't think we have unless we have
a totalitarian government like China. I don't think we have
the wherewithal to follow through on ten year plans. We've

(49:44):
proven it over the decades. I'm not endorsing that idea,
but that that the ability to follow through for decades
is something that is found in its atalitarian government. Yeah,
without that, we are not that. I hope we stay
not that.

Speaker 6 (49:58):
It's really hard, all right, So let me ask you
guys this, all right, with all of this stuff going on,
all this politics and so on, what are the consequences on.

Speaker 2 (50:11):
The ability for the D three or just Ford and
General Motors just just just have those two. How How
does this impact their investments in electrification? How does this
impact their investment and automation?

Speaker 1 (50:30):
And I don't mean robots, well, they're gonna have to
change that dramatically. I mean a lot of the evs
that Ford and Stillanis and GM are producing are not
in the US, and the ones that they are rely
on a lot of components that are coming from overseas.

Speaker 4 (50:51):
So I would I would go back to the Biden
administration and they believed going down a pathway to electrification.
Whether you agree with it or not, that was their vision.
They supported it with an enormous amount of funding for
those industries. The automn industry was very fortunate to get

(51:12):
a whole lot of money from the Biden administration. Now,
you may agree with that or you may not, And
I certainly love to talk about that have mixed emotions,
but this time you don't seem to have that. You
don't seem to have someone saying we know this is
going to hurt like hell, and we're going to get
you through it because we think it's fundamental. Instead they
say not much on that pathway. And I think that's

(51:36):
where whether it be you talked to talk to the
Chinese Tenure Plan or even Europe, there's a much more
willingness to understand that there is a transition cost, and
that transition cost has to be paid by somebody. And
we have a government right now that doesn't want to
admit that. I suspect they know it, but they don't
want to admit it. And we had a government previous

(51:59):
that probably a mid too much and said we're going
to give you all of this money to do this.

Speaker 1 (52:02):
Well, what is the support plan to China? And China
and the ten year plan, they had R and D
support programs all along the way. I mean, it's kind
of like the you know, the natural disaster where the
governor of it was Arkansas was asking for FEMA relief
and they had already pulled the program mat Her.

Speaker 4 (52:24):
So I'm I believe again personally is make point out personally,
we grow building stuff in this country is important. We
need to do better at her We've lost it. I
don't want to sound at all like I'm saying we
should give away manufacturing, but to do that, we have
to think about all of that stuff we lost and

(52:46):
how it cost us jobs and the pain of that
and realized that's the kind of transition we're gonna have
to go through to get it back.

Speaker 1 (52:53):
And you know, that process had started in the last
few years with the reshooring initiatives, some of it jump
started by by Covide but there is a lot, but it's.

Speaker 4 (53:06):
Going a different direction, and now we want to go
in different directions and in certain terms of not supporting evs. Again,
the idea of supporting or not supporting EVS good topic
for discussion. Not What I'm trying to get through here
is is getting this pathway to where you want to go.
And the pathway now seems to be we're going to
tell people that there's gonna be no pain. We know

(53:28):
there's gonna be pain, but we're not gonna do anything
to help the pain. And that, to me, that's the
disconnect I see here and Garyot's it's not by October
it's gonna be better because everyone's gonna be resolved. Moving
stuff from China, moving stuff from Europe, moving stuff from
Canaden to Mexico takes a long time. And oh, by

(53:50):
the way, as you do that, there's gonna be a
cost of moving it, and it's gonna be more expensive
to produce it here than most other places.

Speaker 2 (53:55):
Okay, so basically fifty percent of the cars thereabouts that
are sold in the US during a given year are
imported from somewhere else. They're not made here fifty percent.
So you take a percentage. I mean, not all of
them are not going to be sold here, right, I mean,
it's not going to be like, oh, suddenly we're left

(54:16):
with half the number of cars that you know, half
the number of cars, but with the same number of
people who are looking to buy them but probably can't
afford them, because even the domestic ones will be more
expensive because we haven't even mentioned the tariffs on steel
and aluminum, which are sort of important to the manufacture
of a car, I mean just a little bit or less, right,

(54:36):
And so that's there too, right, So let's let's just
say whatever percent So let's say of the fifty thirty
percent are coming here, right, but they'll they'll all be
more EXPENSI you're you're making faces here right again our
podcast audience on that listening. I'm just thinking, Okay, so

(54:58):
we know that right now, cars average transaction price is
about forty nine grand. Okay, what do you guys think
the transaction price would be Let's say, a year from now.
I mean, let's not worry about ten years. A year
from now, what will it be?

Speaker 4 (55:18):
So let me go answer that by going a little
bit different direction. How about this in three months from now,
President Trump has negotiated with those other countries, and they
do come back with a more tenable tariff exchange ratio,
and we do get some of this free er trade
and instead we're actually getting opportunity to sell more vehicles

(55:40):
other places. And it's still gonna be a little more expensive.
But maybe it's not. Maybe it's again. I keep coming
back to this idea that if it's permanent, it's gonna
be I can't even imagine what that cost is, Okay,
but if it's a bargaining tool.

Speaker 2 (55:58):
All right, bred devil's okay. So what cars do? What
vehicles do the Detroit to make better than anyone else
in the world, And should Corvette full sized SUVs?

Speaker 4 (56:19):
Okay?

Speaker 2 (56:19):
Sure, okay, now that's what we do the best, right,
I would agree, you agree, right, okay? So where in
the world are consumers looking for full sized pickup trucks
in full size SUVs? And yes, I know that General

(56:39):
Murtors sells a lot of SUVs, as does Forward in
the Middle East where they like big vehicles. So where
are these So.

Speaker 4 (56:48):
Okay, I'm trying. It's really hard to try this.

Speaker 2 (56:54):
I mean, so this this whole idea of like, oh,
you know, people are are just other parts of the
world of just waiting for our vehicles. I don't think
that's the case. And how long did it take companies
like Honda and Toyota to be able to build vehicles
that really were desirable? Why the America customer in big numbers?

Speaker 4 (57:13):
Okay, you're right, it's hopeless. I tried, it's hopeless. No,
it's your points are really important. And you know, we
talked to our friend Oliver Schmidt. Oliver used to tell
me long ago when I said America is becoming an island,
he said, no, you are an island. You've always been
an island. You're completely separated from the rest of the world.
Are products for the most part, very most much most

(57:35):
part don't sell overseas. That's okay. They work wonderfully here, right,
we love them here. Those trucks you talked about are wonderful.
I heard on facts that the only reason they're not
selling god DRAMs in Europe is because of the terraffs.
I got to think the facts. Folks got to get
to Europe. Ons in a islands understand this. You know,
maybe they've stayed in Georgia too long or where. I

(57:58):
don't know. Where they're from. But it's just we don't
make products that are fair there because we have a
great market between the US, Canada and Mexico.

Speaker 1 (58:07):
To answer your question, though, I think it's abundantly safe
to say the average transaction price will be above fifty
thousand dollars, maybe four to six thousand.

Speaker 2 (58:18):
I would say for six thousand more.

Speaker 4 (58:21):
I won't even guess because just so.

Speaker 2 (58:23):
Well, I mean that the four to six thousand seems
to be what most analysts are saying. I mean that,
and you know, at some point I guess when you're
getting a seventy two month loan that it doesn't look
that bake.

Speaker 4 (58:34):
But yeah it does. I've seen the numbers.

Speaker 1 (58:36):
Yeah, I mean, it's still bottles in my mind that
the average transaction prices forty nine.

Speaker 2 (58:42):
Thousand, well, you know, I mean. And the other thing
is is that we even go down the road of like,
you know, parts, I mean, things do break on cars
and they need to be fixed, and you know, and
only that they have.

Speaker 4 (58:52):
It, by the way, that reads insurance rates because you're
gonna have to fix those parts that are more expensive.
So again it's I go back to this idea that
maybe it is just a really you know, maybe he's
playing three deck chests and the others are not, and
he's gonna get He's going to get agreements from them

(59:15):
that are more fair and more reasonable. Long term. That
helps a little bit. It doesn't help tomorrow, but it's
that's all I got.

Speaker 2 (59:28):
Well, as your retirement state is going, that's.

Speaker 4 (59:31):
Why I'm here. All right? Are you getting paid for that?
All right?

Speaker 2 (59:39):
We got to end this on and up note, yes, please?
So what about the Tigers.

Speaker 4 (59:48):
I was so glad the Tigers didn't play today because
every day I wake up and listen to Tigers as
I'm doing stuff. It's like I can't believe they're winning.
This is so great. I gotta take a day off tomorrow.
Good day off today.

Speaker 2 (01:00:01):
See, everybody thought that Detroit was down and out. We
got the Pistons in the playoffs. Lions did incredibly will
last year. Tigers are on a great start hockey team
not so much so.

Speaker 1 (01:00:13):
I don't know if you remember those, Carrie, but for
the past nearly thirty years, some of my high school
friends and I go to an out of town Tiger series.
Last year we completed our last major league city Houston,
so I actually got ridden up front page of the
Free Pros.

Speaker 2 (01:00:32):
Really.

Speaker 1 (01:00:33):
Yeah, but so this year we went down to spring training,
the first time I've ever been to spring training, and
those are positive vibes.

Speaker 2 (01:00:42):
Yeah, so you're attributing their success to you and your boys, seeing.

Speaker 1 (01:00:46):
That it only took us thirty years.

Speaker 2 (01:00:48):
Day, okay, all right, so with with happiness about the
Tigers after all of this stuff. The robotic stuff is
very interesting. I thought that was, you know, it's encouraging
that there's possibilities and they've got good jobs that people
can get assuming that they're willing to take the training
and doing the work and put that in. I think

(01:01:09):
that's that's fantastic. Yeah.

Speaker 1 (01:01:11):
One thing I didn't get a test to ask Mike
was how much it's spreading down to the tier two,
tier three supplier as we know what level of automation
do they have and will they be able to afford
it and will they be able those that don't get
left on?

Speaker 2 (01:01:27):
All right, Steven six years. I'll have you back when
we'll ask him. How so sorry, I went out to
thank you for tuning in. John will be back next week.
We'll have another show. We appreciate your what watching the
show go to YouTube, go to the website, join, put
thumbs up, do the patron thing, just support this show

(01:01:51):
so we keep going on. And and if you know
about work, here's bread. He needs help. So anyway, thanks, thanks, I.

Speaker 4 (01:02:00):
Won't work in a manufacturing plant though I'm an American.

Speaker 1 (01:02:06):
Yah,