Manufacturing Execution Systems (P229)

Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
Welcome back to the Automation podcast, the world's
number one industrial automation product and technology show.
Thanks to you,
our audience of highly skilled automation professionals. Thank
you
for being a member of our audience, and
thank you for tuning back in this week.
Now if you're brand new to the show,
my name is Sean Tierney from Insights and
Automation.

(00:21):
And each week, I invite a new vendor
to come on the show to talk products
and technologies.
And this week, I have a gentleman who
started an MES company
on the show to talk about what his
company, you know, the solution he has and
the problems that he solves that many of
the very large MES companies just can't do
affordably.
So I think you guys will enjoy this,
and you'll also probably notice if you're a

(00:43):
regular
that the podcast has been released a day
early. I like to do this during Thanksgiving
week so that you can listen to it
on Wednesday if that's your final commute of
the week instead of Thursday, which everybody's busy
typically here in the US, busy with turkey
and family and sitting down to a nice
meal. So I hope you get to enjoy
that if you're one of our listeners in
the US. So with that said, let me

(01:05):
jump into our sponsor's message, and I'm actually
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If you're one of my students in an
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(01:26):
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(02:11):
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So with that, let's go ahead and jump
into our show.
And if you don't mind, Ryan, could you
please introduce yourself to our audience?
Thank you so much for having me on
today. Appreciate your time. And, I'll I'll do

(02:33):
my best to not go into weird rabbit
holes and boring sections.
I am the ass, which is easily done.
But,
my background, I grew up in the Midwest
in a small manufacturing town in Illinois.
Kinda always been into making things, got into
cars very early.
Went to school for mechanical engineering
in the automotive industry. So in 2009,

(02:55):
took my first role with General Motors,
spent 10 years in GM, couple years at
Tesla in their early days, launching the Model
S and building out
the Fremont supporting structures in their factory.
Did a tangent into a software company for
a couple years doing cylinder deactivation
controls for gasoline engines, which is pretty cool.

(03:17):
And then I had a chance to run
a motorcycle factory for three and a half
years.
So largely automotive, and then I think, you
know,
bigger company down to smaller company, the 2
themes,
all the way to the point of starting
one. And we formed PECO because,
frankly, we're just sick of using
really

(03:37):
poorly designed and laid out software that wasn't
up to modern
expectations.
It's the 3rd time that I've been involved
in building an MES and hopefully the last.
So I would very much not like to
do this again.
So I would not recommend starting a company
unless you absolutely need the product to exist
on the other side. So It is a

(03:59):
big
undertaking.
And, you know, I just you were talking
and I was like, you know, my Dodge
Charger has the cylinder deactivation.
Yeah. Yeah. And I'll tell you, when it
goes into eco mode and shuts down half
the cylinders,
you know, I never even hear it. I'm
getting older now, but I've had it for
15 years. I never hear it, and I
never notice it. So that is some excellent
technology. So I just wanted to throw it

(04:20):
out there. Basically, don't call the level beyond.
It's the individual cylinders. We shut them down
1 at a time instead of 8 to
4. But anyway, yes, neat stuff.
Yeah. Yeah. So, they they say don't call
it a semi hemi, so I won't, if
anybody remembered the the funny commercial from way
back then. But in any case,

(04:40):
so MES now I think all of the
audience understands what a manufacturing
execution system is,
but from your standpoint as somebody who actually
ran a factory. Right?
Tell us what you what MES means to
you. But before we get into that, I
want to thank those of you who signed
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(05:02):
In appreciation of your support,
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And with that, let's go ahead and jump
back into this week's episode.
So there's there's a couple of camps out

(05:24):
there, and we can the
the definite the formal definition of MES is
the command and control layer. So if you're
curious, you can look up a spec called
ISA 95,
and it lays out ERP on the top,
MES, SCADA, PLC
sensor levels.
And there's a lot of issues with that
pyramid in in how the systems come together.

(05:46):
The theory is correct in the fact that,
like, all these things have to play nice.
The
the the new camp is unified name space.
I'm sure you've gotten into that over in
in in your world. But the,
MES has classically been
receiving orders of what to build,
structuring when those orders are gonna hit the
shop floor, so sequencing and optimizing for that,

(06:09):
routing,
and then governing
that the work is performed,
correctly as far as the source of truth
or historian
of the data,
either back to the ERP or to hold
in this in its entirety.
So the the command and control layer is
the easy way to say it. The
the problem with that is is it forces

(06:29):
you to have to integrate everything.
And especially when you start with depending on
the legacy system of choice. I mean, a
lot of automation systems have been around since
the eighties nineties.
You get into ERPs, they're just
as old.
The integration of these systems can be a
challenge to say the least.
So we, we we have a slightly different

(06:50):
take on MES. We violate the the southern
boundaries of the ISA 95
stack and get down to we can take
in a $2 micro switch as an input
through one of our edge devices.
We have
I wouldn't call them SCADA functionalities because there's
no safety component, but the ability to govern

(07:10):
work or data and move it across stations.
So you have some of the the transmission
values. We can talk directly to PLCs.
Our theory is that you need to take
what's supposed to happen.
So think it is like, you know, work
instructions in its rawest form
and tie it to the things that are
doing the work. So

(07:31):
tools, people, machines,
so that you can collect the data that
matters,
which drives
insight and value
on the other sides, right? There there's value
along the way in training,
error proofing,
first pass yield improvements. But where the real
value comes in in this kinda industry 4

(07:51):
point o, call it whatever BS term you
want,
is when you can generate,
oh, crap. If these two things occur, this
problem happens. We should probably fix those. How
do we fix those? Oh, we're applying too
much epoxy. Put a scale underneath it. Measure
how much came out. Hey. Now we're in
range, we're good to go. Problem goes away.
You never see it again, whatever it might

(08:13):
be. We shoot bolts,
use a DC nut runner or just a
clutch tool with a feedback loop. So it
says how many you shot. Now you don't
have to worry about one of them being
not present. You know? It's the ability to
say this is what was supposed to happen,
and then make sure that it did.
Yeah. I remember back in I think it
was the very late nineties, early 2000s, Rockwell

(08:34):
was getting us all trained up on SP
95,
and that's when it was still it was
still a proposed
spec or,
and, I I just remember the slides with
all the different octagons on it, And MES
was made up of all these different pieces.
We had,
data collection, historian, we had analytics, we had

(08:55):
x, y, and z. I think there were
11 or 13 of these little boxes, and
it's evolved over time quite a bit.
And I think for a lot of the
people who are on the plant floor, they
have these
I hate to say this old, this is
gonna be like buzzword bingo. I hate to
say
islands of automation. Right?
But in many cases

(09:15):
Yeah. You know, and a lot of times
they try to glue it together with their
SCADA system or the historian,
but that just doesn't
get you to the layer of MES. Right?
It doesn't
what we end up having is we end
up having all these
silos of data.
These blobs of data that never get looked
at. Right? Well, you know, maybe somebody looks

(09:35):
at a trend and if there was a
problem, they may go back and manually look
at it.
Right? And they may even have a condition
of monitoring package that can see
a deviation and and give us an alarm.
But, you know, what what you're talking about
is really taking the orders in from the
front office and saying, you know, make 10,000
of this and then orchestrating that down. I

(09:56):
believe, and correct me if I'm wrong, but
taking that down to the the the plant
floor and saying, okay, this is what we
need to do to make this happen. You
make so many of those, you make so
many of those. I mean,
but also tying into the historians. So you
know that,
hey, this is the data for that run.
If I want to pull up this this
order, this this production run,

(10:17):
it knows where the historical data is and
it knows how to you know tie that
in. All the am I even close?
Yeah. I mean, there's, you know, there's hundreds
of small functions that build all these systems.
It's no different than any of the other
layers. Right? And they all have to work
together.
So in our world, you know, in our
definition or how we execute, we have things
like process dependency checks, where when you when

(10:39):
a part enters a station,
you check to make sure that it has
a valid complete flag from the station in
front of it. Well, it could be a
manually assembled station, like, did they actually bolt
it down? And we're looking at at at
a minimum, did the operator signal that they
completed the the work? It could be, you
know, looking at physical measurements from tools that
were associated with the work. It could be

(10:59):
a $2 micro switch that just said, yeah,
the part was in the fixture, and now
it's not. But something that says it did
what it was supposed to do, and then
we'll release it into the downstream.
There's also a layer that says, you know,
you have the I did it, and then
you have the what what do I do
next?
So the the what do I do next
part of it is you ordered 5 bicycle
frames of this configuration.

(11:21):
So this station needs to produce 5 of
these subassemblies, and, you know, it was different
than the order before, and it's different than
the order that'll follow. But how do they
know which variation
of the process to run? So we'll govern
that with a parent child
relationship between the manufacturing order and the individual
work ticket.

(11:42):
And then you mentioned the historian. So that's
a key piece, not only for the in
process movements in the quasi SCADA world,
but also just, you know, 6 months later
when something goes wrong,
you're trying to understand,
did I build one of these bad? Did
I build all of them bad?
What changed?
You know, sometimes you have all the information

(12:02):
you need to make that decision. Sometimes it's
in the supply base. But how do we
integrate all of these things together against
the idea of the product produced?
It's an interesting
challenge because
classically, MESs were all custom,
right? They would live within a framework, and
then you had to customize everything around it.
And I think a lot of the problems

(12:23):
was the systems they came off of weren't
the right
fundamental level framework.
If you think about how automation works, it's
not
directly
set up. It drives a lot of IO,
it has a logic system inside of it,
but it's not thinking of the world as
what's supposed to happen, where is it supposed

(12:43):
to happen, and what did it do. You
you can try to configure it that way,
but it's not its core. And an ERP
is thinking about transacting material.
Right? I have raw I have raw goods,
and I'm gonna convert them into
finished goods, and there's a cost associated with
it that the accounting side of it needs.
Neither one of those is how the shop

(13:04):
floor works. So
how the shop floor works is I have
things that I need to do over here,
and it's a series of steps that get
carried out in some form of sequence,
similar in many ways to automation. But there's
a physical world constraint, again, similar, where I
can't I can't have the same same device
in 2 places at the same time.

(13:26):
Yeah.
And I might have 5 stations that are
all similar to each other that can carry
out parallel work,
but it's the physical world constraints, and you
have to marry the 2 together and add
an operator or an ID for the equipment
that's carrying out the work. And now you
can actually perform work, you can collect data,
you can generate insights, you can create value.

(13:47):
So
it's a different framework. And I think
by changing that framework, we can get out
of a lot of the customization that has
been in the past, and the customization is
not bad. You you want the system to
line up to your factory. But if if
you're starting from a far away away and
you have to do a lot of customization
to get it there, it's really expensive, and

(14:08):
that's the problem that people have seen. Right?
Typical MES deployments are measured in months, if
not years, to set up and in 100
of 1,000 or 1,000,000 of dollars.
Yeah.
If you can switch that out and do
this kind of bottoms up approach
instead of a top down routing
and hierarchical approach,

(14:28):
like the classic deploy,
you can change the cost paradigm dramatically. You
can build an element of work, copy it,
you can tweak it, you can make variants
of it, you can stack it into a
workflow
that creates products. I mean, the devil's in
the details. It's fun to
theorize about, but
proof's in the pudding. You know, we're an
order of magnitude cheaper with the same capability,

(14:49):
if not more,
of classic MES. I mean, we ripped and
replaced a Rockwell deployment in 6 weeks in
a semi truck factory.
Nice.
That was So that's a good point. Let's
let's talk about that. So you can connect
to let's just talk about this. So a
lot of process a lot of these manufacturing
cells are automated.
Right? They may get loaded manually, but then

(15:10):
they run and then a lot of times
they're unloaded manually as well. Sometimes there's material
handling between the cells. Sure. But if that
if that automated system has a Rockwell or
a Siemens PLC or somebody else's PLC,
your system is capable of talking to those.
Right? Hey, everyone. I just wanted to jump
in here and pay some bills. Thank you,
first of all, for listening to this episode.
And while today's vendor wasn't able to sponsor

(15:32):
this episode,
I still wanted to invest the time to
bring it to you because I think you're
like me. You like to learn about new
products and technologies.
So with all that said, I'd like to
ask you to consider becoming a member
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help me offset the cost of producing these
episodes each week. In exchange for your membership,

(15:53):
you will receive member only perks and ad
free editions of every unsponsored episode of this
show.
With that said, thanks again for tuning in
this week, and now we'll return you to
this week's episode.
Yeah. Through typically, either direct to depending on
the PLC and the licensing they have, so
a tag read write structure,
or we have

(16:15):
intermediaries. You can go through products like PTC's
Cupware, where it kinda does a translation layer
across all of these.
Or you can go up to the scatter
layer, so Ignition being one of the more
popular ones lately,
where you can do things like, you know,
an OPC UA,
back and forth structure.
So, yeah, we the big thing that PECO
does different

(16:36):
is we can connect to
you name the tool. There's 200 families of
tools
that we connect directly with either through our
little $65
microcontroller
based edge device. So I have a USB
scan tool in my hand. How do I
connect to that? Well, I can't can't plug
that into an Ethernet port, so I need
something to gateway it into the system. That's

(16:57):
what those edge devices are for. Serial converters
are another great example, RS 230.
You know, 232 to,
to be able to speak, you know, pick
your flavor of choice, Modbus across an RS485,
things like that. You gotta get it into
the network if it doesn't have an Ethernet
port sitting on it. So

(17:17):
our ability to do that becomes really interesting.
We can connect to torque tools. We can
connect to scales. We can connect to laser
engravers. I can connect to a PLC. I
can connect to an ignition deployment for an
automation
system.
It's trying to give people the opportunity to
solve problems.

(17:37):
Everything that we connect to was brought into
the system to solve a problem, a data
silo problem, a error proofing problem, whatever it
might be, a speed up the system problem.
But if you can connect to those different
physical world entities,
you can solve that. If all you have
is a API structure on your edge and
you force all that integration work onto the

(17:58):
teams,
now every single factory
has to go repeat that integration.
Well, that's not efficient. That's super annoying. You
know how many people every day probably look
at a DC torque tool
spec and try to figure out how to
talk open protocol to it? I mean, it's
terrible.
The it shouldn't have to be that way.
Like, how do we eliminate that repeated work?

(18:20):
And in the automation
systems, it's really fun. There's a lot of
things you can do. Well, that's why I
was going to go to my next thing
talking about manual stations. And I think, you
know, a lot of times
when you're talking to Rockwell and the other
big automation vendors,
even if it's a totally manual station, maybe
there is a couple of buttons they have
to press and some things they're going to
scan. The answer is to put a PLC

(18:40):
in there. It sounds like with your
it's like, I really don't need a PLC
for this. Yeah. So it sounds like your
Edge device has some IO on it, and
you could take in a scanner, you could
take in other devices. You could probably take
in some clickety clack contacts as well and
maybe turn on some lights.
Yep. Oh, yeah. We have output, input. We
have I mean, the we we use the
Raspberry Pi based microcontroller.

(19:02):
Our secret sauce is the,
the software that it took to make them
5 nines reliable, which was a trick, but,
because no one cares why that factory goes
down. Right? If it's the barcode scanner that
didn't work, it's still down, and we have
to fix that level of reliability.
But it has that. We have the ability
to add in other IO modules, right, that
can communicate with either our server directly or

(19:24):
through that. So you can go or you
can go to a PLC.
Like, the PLC is still really great in
a lot of applications. But to your point,
you know, if you wanna read a $18
Amazon special pressure transducer
for just to know the airline is in
range of the pneumatic tool, seems a little
wasteful to put a PLC
in place with an IO block to grab

(19:45):
that when I can do it with a,
you know, $50 piece of hardware.
In the same regard,
using the PIE as a safety critical motion
system controller is probably not a really good
idea for you.
But
we just wanna give the right tool for
the job as an opportunity
and then to solve the real problems.
So you mentioned

(20:07):
mixed automation and manual, which is the way
of the world, frankly. There's always a human
being somewhere. If you can find that lights
out factory that isn't making, like, semiconductors,
I'm interested in seeing it. But what you
know, battery manufacturing, I'll use that because, like,
we bump into that a lot. It's a
hot topic in some circles.
You've got these automated cells, but you still

(20:29):
need to record the epoxy
lock code, for instance, that's going into the
dispense system. So you change out a 55
gallon drum.
You know, there's a human being that did
that. You're gonna put in all the effort
to have a fixed barcode reader on there
and a rotating system to get the drum
in the right location, and then an arbitrary
pick your backup system when the drum got

(20:49):
scratched and the barcode can't be read and
it's found. So you got a camera for
the human readable? Like, to automate that doesn't
make any sense when you can have the
person who dropped it off go beep with
a $60
scan tool. So it's that blending things together
that I think is a really interesting piece.
The more automation you have, the less the
MES is kinda needed. Frankly, we get cheaper

(21:10):
and cheaper the more things automate.
But it's about filling that gap. And then
we talk about data next, which is the
other side of the house. But, you know,
the automation creates all that information.
So And I've and I think we've already
discussed this really, but I really want to
circle back to this. So like you said,
starting a company is a lot of work.

(21:32):
And developing a platform from scratch is a
lot of work. And you would never want
to do that again, but you did this
and I know we kind of already touched
on this a little bit, but but I
really want to circle back to it. We
we, you know, to this is a massive
undertaking. Right? And so what was if we
could if we just go over this again.
What was the main drivers
for you taking on this massive

(21:54):
thing to to create a new MES that's
gonna, for once in it all, just do
it right?
Yeah. I mean, to me, the the there
there were 2 key weak points when we
started PECO that I wanted to attack. 1,
the ability to airproof your processes
in 5 minute changes.
I'm not talking about having to write, you
know, a new driver because you wanna bring

(22:14):
in a random scale. Like, how do I
how do I have this massive,
you know, engineer's toolbox
to allow me to have a problem bubble
up in the morning, whatever happened. Ah, crap.
We had a you know, there's a a
chance for a human to cause a mistake
or the automation system was allowing something to
get through. I don't wanna deal with that

(22:34):
ever again. I want a clean-cut in a
repetitive environment. Like, how do I block that?
So being able to do that has always
been possible, but being able to do it
quickly and efficiently
is the challenge. Like, when I was a
GM, you know how many days it takes
to get another torque tool put online?
Like, it's insane.
We can input
tools in literally in 5 minutes. You plug

(22:56):
it in, it auto identifies if it has
a system that communicates. You know, if it's
a printer, you might have to create a
template.
DC torque tools are under an hour, and
the majority of the time is to set
up the rundown process. Like, it's taking out
all of that
wasted energy
so that
people on the plant floor can solve the
problem quickly. That was the number one pet

(23:17):
peeve. And then number 2 pet peeve for
me is the access to the data.
I call it the difference between thinking and
knowing.
Right? You think you
you you have a good thought on how
you build something, but if you don't have
data to prove it, you don't know. I
don't care who you are. Like, the and
the ability to have that data trail

(23:37):
drive continuous
improvements,
it's an addiction that once you've had it,
you can never let go of.
The ability to go, oh, let me pull
up the serial number and see the here's
exactly the produceconsume chain. It went through this
subassembly into here into here. Here is every
piece of information collected. There's not a
go into another system to get the torque

(23:59):
data and go into another system to figure
out what the voltage read on the cells
coming into the module were in a different
system that tells me, oh, I gotta go
into the dispense system now to figure out
the lock code that's inside of it. Like,
that stuff slows down progress.
And when you're in a complex industry like
aerospace or automotive,

(24:20):
that matters.
Right? If you if it takes you 2
days to solve an issue, 2 days would
be great, first of all.
But if you can solve it in 2
hours, you can solve so many more things
when 80% of your day is meetings and
firefighting.
Right?
Like and it was about having systems that

(24:40):
allowed that to happen.
Sure. And that kinda it brings me to,
like, are you relying on other people to
collect and store the data, Or do you
grab, like, for let's take Ignition, for example.
Are you using their data
that they collect? Or are you actually taking,
look, I need this data in my system
separately? So how how does that work? Do

(25:01):
you start anything in your own system? Or
Yes. User's choice. So we we look at
ourselves as an aggregation option.
So,
and our focus is on being able to
make sure any factory can do this. A
20 person factory,
it's a tier 4 supplier,
you know, or or building that little widget
that they sell commercially,

(25:22):
or, you know, a 1500 person facility. Right?
Everything in between.
In the past, this type of technology was
limited just to that bigger size facility that
could afford the really expensive deployments.
But
inside of that world then, you give the
user a choice. But before we get into
that, I wanna thank the automation school.com for
sponsoring this episode of the show. That's where

(25:42):
you'll find all of my online courses on
Allen Bradley and Siemens PLCs and HMIs.
So if you know anybody who needs to
get up to speed on those products, please
mention the automation school.com to them. And now
let's jump back into the show. So if
you built if you have automation in place
and it's already connecting I'll go back to
the battery example. It has voltage measurements and

(26:03):
barcode reads on the cells, and then maybe
it does a high pot test on them,
the module, and there's, like, an image capture.
We can grab that from the automation system
and tie it to the downstream systems that
are manually assembling the battery pack, for example.
Right? Because it's hard to automate those those
pieces of the puzzle, especially that I can
fix.

(26:23):
And that way, there's not a data silo
problem in there. If they haven't built the
automation yet, and for some reason, the automation
company has a hard time figuring out how
to connect to one of those devices, you
can insert PICO. It'll connect to the device,
and then it'll tell the SCADA as if
it was a PLC when triggered
what the value is on that or to

(26:43):
kick off a routine.
You know, we can run Python scripts for
flashing firmware, for example, something that's possible to
do in automation, but it's just really easy
for us to do. So save yourself a
few $1,000,
and it's just part of that deployment. So
that's that's the more sophisticated route when people
have been through it once or twice. They
can start mixing and matching who's good at

(27:04):
what, knowing that all the systems are integrated
and they'll play nice together.
But that's how I see it is the
it it's giving options.
If you speak ladder logic and that's the
only logic you wanna know and you wanna
go in and everything's a PLC and program
to it, great. No problem. You know, We
can fetch a CSV file you generate and
parse it into variables on our side

(27:26):
and run dashboards and SBC charts against it
or create a report that's the full traceability
required by the US Navy for the thing
you made, whatever it might be. Like, why
ask the automation system to do that kinda
work if we can do it more efficiently?
So and then in the same regards, we
we don't do time sequence data worth of

(27:47):
shit, frankly.
Sorry for my language.
Like, we're really good at events. We're really
poor at time sequence versus the PLC
where it can it can watch a variable
over and alarm when it goes out of
sequence and things like that. So married the
2. What a great marriage, right, that's doing
this. The alarm goes off, we take that
alarm trigger, we already have connections into Microsoft

(28:09):
Teams or into
Slack if you use that or email or
text. And now the automation company didn't have
to figure out how to do all of
that stuff. So,
anyway,
that's the vision is you can just solve
a problem without having to create
code.
Now I think let's let's talk about the
and that makes a lot of sense to
me. Let's talk about what your customers see.

(28:33):
So they have a Pico MES system.
Like, are there different views for different type
of people?
Who sees what? And I know every plants
every deployment can be unique. Right? But, you
know, explain some of like in one of
the one of your,
your more favorite, I guess, applications you guys
worked on. Talk about the different views people
have. Like, I'm sure you have somebody who's

(28:54):
who's,
like higher up on the food chain, maybe
up at the front office who needs a
view, and then you have people on the
plant floor. They wanna know. Maybe they got
OEE. They gotta get their act together or
else the line's gonna be shipped overseas or
or maybe there's a bonus tied to getting,
you know, keeping some quality or, you know,
cutting scraps. So talk about the different views
because I know your system does a lot,

(29:16):
you know, through code, but it also has
to interface with people. Right? That's right. We
have we have 4 key customers, if you
wanna think of it that way, on the
in the in the factory. So the first
one is the operator doing the work. So
we have a, it's a work construction visualization
or worker guidance suite. So similar to an
HMI, but it's moving step by step as
they are moving. So you scan a barcode,

(29:38):
it accepts it. If the pattern match works,
it'll automatically advance forward. The operator doesn't do
anything.
And now out of the corner of their
eye, they see a visual representation of the
next step, image, video,
CAD screenshot, whatever that might be. There's text,
there's layered content, there's a strain a training
kinda side of the house there where more
information's available

(30:00):
in certain situations.
And then the the layer above the person
doing work or, you
know, on the machine side of the house,
you would just use the HMI, so you
wouldn't need that view. Okay.
The the next layer up, though, is the
supervisor. So they're going, okay. Now I wanna
look across multiple stations and know who's on
pace, who's not on pace, who's having trouble,

(30:21):
who's what's working well, where are my issues.
It's basically a reacting
type role, right? I react to wherever the
problem is. And
so they get a view that's we call
it a TV view, but basically it's the
classic,
you know, 5 colors of station status. If
they're on pace and there's no alarms going,
it's green. If they're falling behind pace, it

(30:43):
might go yellow. If the they have a
machine issue or a person is,
having a trouble, it goes red. But that's
their their item. They also can interact with,
we we interact with teams and these kind
of shared comms, so they could be following
on their phone whether or not an alert
occurred or quality defect, and it'll ping them,
when when things are happening. Then you go

(31:05):
level up to the engineer. So now their
view is in the background,
for a lot of it. How do I
they're setting up the work instructions. They're setting
up the device connections. They might be looking
at the data to go down a Kaizen
project,
and do a they're looking at cycle time
data and how can I rebalance it? So
their views are in the what we call
the manage pages

(31:26):
sitting in the background. They have access to
all the other views as well. Yep. But
they might be focused on the the setup
and the data side of the the the
granular data. And then the final is the
executive
view. And now there's arts and charts, as
we lovingly call them, for what did I
make today, what did I pay what did
I get for paying people effectively? So you

(31:47):
have your
output run rate charts by part number or
product number.
You've got
OEE over on the station level side of
the house or equivalents.
You've got,
maybe standard reports they wanna see. So, like,
we send in this work order. When was
it completed? Some of that comes out of
the ERP. Some of it would come out
of PECO depending on how they set it

(32:08):
up. But it's much more of the strategy.
And then typically, they're going a level it's
like a Venn diagram. Everybody overlaps at least
one level. So the executives might be looking
at one level down data to understand, oh,
do we what's our capacity?
Do we need to buy more
equipment, run over time, add a shift? Like,

(32:29):
where are we relative to that? If I
improve these perennial problems, could I save that
equipment purchase? It's a really common question.
You know? If I if I get an
order for 15%
15% more, am I buying equipment, or can
I find 15% in my processes? Well, at
least we can tell you what your losses
are.
The engineers are looking at you know, the

(32:49):
engineers know you get to do your job
right up until the moment something goes wrong,
and then you stop and you put on
your firefighter hat, you walk out to the
line, and now it's problem solving time. So
you often they're watching the TV view like
everybody else or the connected channels. So,
but that's how we see the world
is kinda in these areas.
You notice the roles that PECO didn't directly

(33:11):
interact with. I didn't mention the electricians or
the technicians or the maintenance crews.
Right? They have opportunity if they wanted to
use us for,
you know, maybe there were constructions associated with
PM on a machine. But there's other systems
out there that work really well for that.
So if you wanna use MaintainX or Limble
or pick your flavor of ice cream for

(33:32):
PM, CMMS,
well, we integrate with them.
So one of the manually
done tools like a DC nut runner has
a problem, the operator can trigger a ticket
for maintenance into that, or we can do
it based on number of rundowns for standard
calibration cycles. But that way, yeah, we can
interact with their world, but they can live
in the world that works really well for

(33:52):
the CNC machines that they're operating or the
injection molding machines or whatever, you know, the
automation equipment, let them stay in their world.
Same thing with the ERP. We connect into
the ERP so the accountants get the information
they need. Right? They need to know how
much labor they put into those parts so
that they can write it off for taxes.
Right?

(34:13):
Yeah. How much scrap happened? Taxes. These things
like that that need to go back and
forth.
So the key for us is making those
integrations as easy as possible.
Yeah. And scrap definitely,
depending on where it happens, that the process
could be cheap or very expensive.
That's right. Add a bunch add a bunch
of labor content or parts on the other
end of it, and tear it back down

(34:33):
again. Yeah.
So yeah.
But the goal when I think of this
whole thing, it's just it's trying to just
let people,
you know, get out of their island.
Mhmm. Every every one of those those views,
whether it's the person the engineers creating the
automation and the engineers setting up the processes,
the operators, the execs, they have their island.

(34:54):
But if they can't see the the world
around them
Hey, Hey, everyone. I just wanted to jump
in here and pay some bills. Thank you,
first of all, for listening to this episode.
And while today's vendor wasn't able to sponsor
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So with all that said, I'd like to
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(35:16):
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With that said, thanks again for tuning in
this week, and now we'll return you to

(35:37):
this week's episode.
Then the then the factory can't win.
And I would argue, one of our things
we're doing is by making this technology
available to the supply base, to the smaller
factories,
you're actually able to go outside of the
4 walls now, and you could in theory
change
transfer data across suppliers and the whole supply

(35:57):
chain for
a complex assembly
can now collaborate or improve,
or, you know, there's circularity of scrap, there's
matching a, b, and c bearings with a,
b, and c rotor shafts, right, for tolerance
stack ups and things like that.
So but you need a digital backbone for
that.
You can't do that with Excel and paper,

(36:18):
it's too delayed.
So
being able to build these
these solutions for each one of those views,
but in a way that it structures,
that that was always the goal of that
ISO 95 pyramid when we come back to
the beginning.
Right? It's like is everything's available or unified
namespaces after the same target.
But then you put that across multiple factories

(36:40):
and things start to get really interesting.
And that's what PECO is really unique about.
Our data model's the same for every factory
we deploy into. So we have tools that
can cross factories.
It's the next generation.
Yeah. Very important too too. And I I
know plants factories compete, especially there's a lot

(37:01):
of companies that have
multiple plants all over the US and they
compete heavily.
A lot of times it's shown as a
failure if plant x cannot provide products and
plant y
gets to provide the product to plant x's
typical customers.
And so they compete internally
very very,
heavily because they don't want to be if

(37:22):
there's a downturn,
you know, the weakest has to be called
and they always want to be at the
top. They want to be not only getting
the bonuses and giving the people, you know,
that that, you know, assurance that their job's
stable,
but also is that internal plant versus plant
versus plant. Everybody's
a lot of companies, they're vying to beat
each other and be the most efficient and

(37:42):
more productive
of facility and around. Even with things as
simple as
aluminum cans that we drink our beverages out
of. I mean, it's very competitive.
So,
you know, what are the what are the
some of the what are some of the
things like a prospective customer comes to you,
what are the kind of things that you
wanna hear from them or you wanna ask
them to know if they're a good fit

(38:03):
for PECO MES?
Yeah. So for us, the the first thing
right out of the bat is the type
of work being performed. Right? Are you building
are you are you making things? Are you
making
things that contain things? Right? Or whatever the
classic process versus discrete.
So we're
we we focus on the discrete side of
the house and with the with an assembly

(38:24):
flavor. There should be people involved. And if
you're heavily automated, we we're still happy to
to work with the team. Most of our
factories are a mix of manual and automation.
But
that that's the first kinda scheme is does
it fit does it fit what we do,
which is guide people, tie into tools and
equipment for error proofing data collection, and then
use the data for for value.

(38:46):
And then from there, it's it's really what
is the pain of a mistake
is a good way to think of it.
Right? If you make one thing if you're
a job shop that
takes one order, makes one part, and may
never see it again, to invest in infrastructure
to ensure that one part make you should
be investing in quoting software
and, you know,
workflow management

(39:06):
software.
There's better stuff out there than that.
If you have a fleet of CNC machines
and you're just wanting to monitor those to
have the highest OEE, there's better like, we
can do some of that, but there's way
better software out there,
that does that. So we tend to push
people that way, and kinda help them find.
But for us, sweet spot, you're assembling something

(39:28):
ideally in north in in the US,
and then you have
that repetitive some amount of repetitive nature, either
consistent processes to make lots of things
or,
make the same thing over and over again.
So Yeah. We go ahead.
I was gonna say automotive and aerospace and
industrial equipment are our sweet spots today.

(39:50):
Yeah. I think you did a good job
explaining that. And, you know, I was kinda
thinking that's 88. Right? So this is not
a batching package.
There's a lot of similarities.
Equipment arbitration
and
but batching gets into respite handling and and
I there is some of that here, but
and there's a lot of similarities, but you
know,
process automation is is different on on many

(40:13):
levels. And
I can see why given the kind of
information and the kind of customers you've talked
about why you'd be talking more about manufacturing,
like discrete manufacturing,
making products.
And I think that's what most, like, you
know, my world of PLCs, HMIs, SCADA. That's
what most facilities are doing.
But, you know,
you also have it in utilities. You have
it in process.

(40:35):
But,
but, most of the people I meet and
train, they're in manufacturing. They're making products whether
it's an aluminum can or it's something very
and there is even some extruded products that
would, I think, fit very well. Because they
they,
they, they run it like it's in a
what, it's not really a batch,
you know, even though they run a, they're

(40:55):
running a product, like let's say making a
sheet of plastic.
It, it, it, to me, it always seems
to have more in common with,
you know,
discrete manufacturing. It's like making a very long
bumper for a car. You know what I'm
saying? Versus making, you know, 50,000 tank gallon
tank of, you know, of of some kind
of a paint or thinner or something. Very

(41:18):
much different process because that's actually gonna be
pumped somewhere at the end of the day
and not actually cut up and sew those
pieces. Right? So, I always I like to
describe it as beer versus gaskets. I know
it's kind of an interesting comment.
Yeah. When you make
and the other thing I mentioned to people
is, like, you can make a system like
ours work in those other environments. Just like
you could probably take an OSI PI system

(41:40):
or equivalent and get it to work in
certain discrete applications or take ignition and try
to make it into worker guidance.
It's the pain involved in doing it. Yeah.
That's what you're just that's that's all we're
sorting for is to try to make the
cost as low as possible and the speed
at which you can deploy, which is another
version of cost,
you know, as rapid as possible.
So, you know, could we make beer work?

(42:02):
Sure. But, like, if you think about where
our edge really lies, it's like a gasket.
So gaskets are you know, you have a
slurry process, and then it might come out
onto a sheet conveyor, go through an oven,
there's a slicer, and then there's the former.
And at the end, it's now it's cranking
out individual pieces. And especially companies that take
that little piece and put it into a
higher level assembly, now you're talking.

(42:23):
But could can we run that line? Sure.
Yeah. We know how to talk to scales
and things like that. We can set alarms.
It's just not as creative a fit as
another system,
that's designed specifically for
that kinda time sequence flow of material through
a pipe.
And there's there's there's everything overlaps. Like, this

(42:43):
is why I think it's hilarious that people
get into the weeds of, like, oh, you
you you're you're this niche. And I'm like,
I wish I could just have that niche
because it would make my sales life infinitely
easier. But the reality of it is that
everything kinda overlaps, and it's Yes. Yeah. Might
it centers around there. But,
yeah. Anyway, because
you think about our connected supply chain

(43:04):
comments. You know, if we wanna make the
corner assembly that's going into
the to the truck plant, right, so it's
got upper lower control arm and a knuckle
and a brake and a rotor and a
caliper, all of that, right, classic assembly.
Well, then you need to if you're gonna
have the information of that whole corner be
available to Ford, you need to be able
to go into

(43:25):
the system that was machining and assembling the
bushings into the control arm. And then you
gotta get into the casting house that made
the thing in the 1st place. Right? Otherwise,
you lose
that data through the system, and now something
goes wrong. You don't know if it's because
the casting was wrong, the machine part was
wrong. Like, pick your flavor of ice cream
on where the problem might be.

(43:45):
So there's flexibility
that allows these to come together.
And then more importantly,
I
I I call it the don't be an
a hole thing, but it's like
if somebody came to us and was like,
hey. We want you to run our state
of the art casting facility, I would say
that's probably a bad idea.
Like, don't be an asshole and help them
find the right solution.

(44:06):
But when it comes to that assembly
of the control arm, yeah, we're really good
at that.
Can you give us some other examples that
you've worked on with some of your customers?
Those are good ones, but I was just
thinking maybe throw some others out. Yeah. We
have so the automotive examples won over,
we make a lot of complex industrial equipment.
So think, like, switch switch gears to go

(44:27):
into data centers, like all the electrical
cabinetry
for power generation and backups. Those are really
complicated. You can't measure you can't memorize that
process.
And then making an error is really expensive
because you gotta tear down a lot be
able to fix it.
Vehicles clearly,
come into our world, whether it's a tugger

(44:48):
all the way or a fork truck into
RVs.
We have legs into, you know, pull on
automotive plants,
things like that. You can use this as
a piece of the puzzle. You know, we
sit alongside traditional MES systems, and we're just
a worker guidance tool.
We have other companies that actually don't use
the worker guidance part and just use the

(45:08):
tool connection part.
So there's just a trigger and response
system. Okay. And then you get access to
our huge library of manually actuated tools.
And then what are some other fun ones?
We've got a lot of battery manufacturing,
especially 2, 3 years ago when that was
really spooling up. We had a lot of
plants come online.

(45:30):
Yeah, I mean, semiconductor equipment, that's another example
of the people inspecting wafers or,
doing part of the parts of the process
with the photo. I forget the name of
it, but we shine the photo and it
makes the system. There's all those motion controls
inside of there that are just
extreme tolerances inside of really complicated assemblies.

(45:50):
Yep. We have a good strong footprint in
there. We spooled up a, oh, yeah. Boats
are fun one. You know how a pontoon
boat is made. That's really interesting. I'll give
you I'll give you a hint. It's not
automated.
And then,
yes, some other fun ones. We have, high
mix,

(46:11):
like sensors and valves for oil and gas.
So you can imagine think about all the
part numbers you can order for
proximity sensors and different configurations
and housings and all of that. Now put
a layer of safety on top where they're
rated for harsh environments like that.
Now you can't have an air and you
have this crazy high mix and you have

(46:32):
to label it and have all of the
certification
paperwork, so we help manage that significantly.
But I'd say over half our business is
automotive and aerospace suppliers.
And then the other half is these kind
of random industrial
things. We do have one process factory. He's
a former user who went to a process

(46:52):
factory and is like, oh, I can use
you here. I can make a work. It's
perfect. Yeah. He's got a scattered network for
everything else, and he just uses us for
the sampling systems. Okay. So which makes total
sense. Right? You get our whole IoT network.
And so we connect into the scattered networks
for the data silo problem and nothing else.
We're just fetching files and bringing it into
the historian,
and then you can tie all the inspection

(47:13):
systems together. So the scales that measure the
you know, okay. What was the dispensed component
amount? Our camera systems that we can deploy
for, like,
was the slurry applied properly?
Yeah. Environmental
sensors, all that fun stuff. So And that
is a place a lot of times where
the automation guys struggle because it's very expensive

(47:35):
to try to automate that with a PLC.
I mean, you can deploy PECO for
trivial amounts of money. You can even deploy
it now. We we released a free what
they call a freemium model. So there's a
free version of work instructions for up to
10 stations. You can add a paid user
license to unlock all the digital tools for
$100
a month. Like and then you can go

(47:56):
to a connected station. So in theory, if
you just had one user and one connected
station to do that inspection,
you're only gonna $200 a month. You could
reach out to us if you needed a
one time buy so you didn't have to
deal with recurring charges.
So, like, why on earth would you go
through it? For the less than the cost
of the PLC, here's 5 years of PICO.
Right? And you didn't have to wait. What's

(48:17):
the current lead time on Allen Bradley's? Right?
Are they finally down from 9 months or
whatever they were at a year ago?
I don't know. I haven't had them on
the show. No comment.
No. I don't I literally don't know. I
mean, I used to. I don't anymore, though.
Well, I think and that's true. Would you
say go ahead. Go ahead. It's just an
easy way to supplement a bigger system. That's

(48:38):
what we mean by modularity.
Like we No. Use it different.
If I if I we have some listeners
who are struggling with that, kinda like
those manual systems where they have, you know,
people have to do some manual assembly or
manual setup and they're struggling. They're like, this
doesn't fit what a PLC does.
I mean, is is that a good customer

(48:58):
for you
to contact you and say, Look, we do
a lot of stuff, but we're really good
at this. This is one place we're really
good at, and we can tie into your
existing PLCs and HMIs.
But we can we can take over those
stations, those operating stations where they're doing some
assembly. You're not capturing that data right now.
Is or or am I off on that?
No. It's it's a great application. And and

(49:20):
what I like about it is we get
really lightweight and really low cost at that
point. So, like, we can be we don't
because we're not trying to drive the entire
thing,
we can be just a little piece in
the puzzle. Just think of us as, like,
instead of buying a key on sensor, you
bought a Pico manual station
control system Yeah.
For that. And then we can what I'd
like about this is,

(49:41):
it doesn't matter to me where the data
historian is as long as there's a single
source of truth, and it's all in one
spot. So if you want me to feed
whatever happened in the manual world at Build
Complete into the automation system, then we just
set up the communications to do that. You
can use the same comm structure in all
your different locations,
or we feed a common database that that

(50:03):
effects effectively becomes a unified name space if
you
insert lots of details.
But the
it's a neat tool that now those teams
can build bring to bear. What we typically
find is actually the opposite,
where the automation company is like, I just
wanna do my little sweet spot, or the
automation engineer. I'm really good at this. I

(50:23):
can do the motion and the pick and
the place and the testing and the Yeah.
The value add. And I don't wanna figure
out what the hell you're doing over here
in manual world. And in which case, then
they go, here's how this works. You should
buy
a system like PICO or one of the
others that Yep. I mean, pick your flavor
of 1 you'll hate more.

(50:45):
Then we just tie you into us, and
the user
has that that kind of flexibility.
They have to learn
it's a very minor,
software set inside of Pico to learn. It's
not like this is months of training. It's
hours of training
because they're not trying to get into the
craziness.
So at that point now, they can see
the automation data, they can see the manual
data, and they're happy.

(51:05):
Well, I see that use case. I can
definitely see that use case.
I think another use case, tell me if
I'm wrong,
but you have these small to medium size,
manufacturers
that they always knew they needed
an MES system. They need some KPIs, they
need some OEE,
they have some manual stations they want to
track, and they they just there's no way

(51:27):
there's no way in God's green earth they're
going to get a $10,000,000
you know, capital project approved for MES. Right?
And so they've always just said,
you know, is that a type of customer
that would be a good target as well?
Because I know so many people never do
the projects because the price just goes,
you know, through the roof. It's 1,000,000 and
1,000,000 of dollars.
Yeah. Our that's our sweet spot. That's what

(51:48):
we built the company for. It's for small
and midsize factories. We know we can go
up to the bigger factories and do from
time to time because it pushes the technology.
But 90% of our customer base
is small and midsize by definition, 500 people
or less.
The the real sweet spot's between a 102100,
people inside of the factory. Right? No one's

(52:09):
gonna touch that typically
in, in the MES space.
And what we do is we give them
that's part of the reason why you have
that whole lower pyramid is an MES by
itself is effectively useless, frankly, if you can't
tie it into data structures that are feeding
it good information.
So the
it's giving them that whole system

(52:29):
as a place to start. And with us,
you can start for
the $100 a month is like a trial.
Yes. In theory, you can start there. But
it is we have a significant customer base
that's at $12,000
a year, 12 k total, and they just
run the digital tools. They care about traceability
and worker guidance. So think the value props
are training reduction,

(52:50):
always the right process on the screen at
the right time,
and the ability to say this is when
the part went through. So it's not error
proofed, but it has all the traceability.
So if your process or your product is
error proofed, great application, low cost.
Aerospace suppliers love this because they can run
local, which means then you get ITAR
certification.
Right? So we we can run-in the cloud

(53:11):
or local, which is kinda nice. And then
the you the I'd say our our most
common customer
is the one that blends in the error
proofing. So this is where the ACV or,
annual contract values get into the
40 to 50 k range, and we're governing
probably
20 to $30,000,000
worth of product creation, maybe more,

(53:32):
depending on whether they're selling a widget or
they're selling
a finished good with a higher markup.
So round off error in the value prop.
I mean, we'll move you 30%
in output.
Same amount of equipment.
You're either gonna get data you never had
or you're gonna be taking busy work off
of a lot of people's shoulders.

(53:54):
Because without a system like this, there's a
lot of people trying to do busy work
or
people just don't want to do it, so
it doesn't get done. So you don't get
that traceability. You don't get that information.
And so That's 3.
Yeah. Gosh. 3 3 value props you just
point to just every time. So just measuring
something that wasn't measured before and giving the
operator feedback, just giving them basic feedback on

(54:14):
how they did, you're gonna get anywhere from
5 to 15%
output increase. And there's a little gamification that
occurs. Not everyone will move, but the mean
will move up that much. You go put
in
error proofing in the the continuous data flow.
So just being able to the traceability data
says how long it took me to build
it and where my errors are, you'll go

(54:35):
find 1% improvements 20 times.
You'd be shocked. It's not it's very rare
you go into a factory and there's a
20% hand grenade sitting there. Oh, man. If
I could know
not to do that, I could increase my
output 20%. Right? People aren't stupid,
but they can't see 1% failures that are
occurring randomly throughout the factory.

(54:57):
Well, with our world, you can, and more
importantly, you can stop them. That's where the
tool connections become very important. So you gain
another 20% there. Right? The range officially that
we state is anywhere from 15 to 50%
increase in
the number of parts produced
for unit labor.
Right? Now I don't know your factory. If

(55:17):
it's running and having a hard time, you're
gonna be up towards the 50%. If you
have a really strong factory, you're gonna be
down in that lower section. If it's heavily
automated, it's probably less than that. But what
we can guarantee you is you will find
the gains that you didn't know existed,
and the pricing aligns to the value. Right?
You don't spend a lot of money if
you weren't gaining a lot of things. Right?
The way the whole structure of selling by

(55:39):
the station.
So to me, it's just
that's the one thing I hope people realize
is
in the past, expensive,
difficult to roll out. You're gonna be held
back by it. It's gonna cause lack of
flexibility in your factory. Arguably, what happened with
automation too.
Right? What's modern world look like now?
Flexible,
easy to readapt around the change in your

(56:01):
business system. It generates data that drives insight
that has increased value over time because you're
able to continuously improve and find things over
there. And it's modular. You can now get
a click PLC for $300.
Right? You cannot spend an You can get
you can get Rockwell and Stevens PLCs for
$300 too. I mean, almost every vendor
yeah. You can. And that's the problem because

(56:22):
if you go with a big house, they're
gonna wanna use the the $50,000
PLC.
I just mean there's options. There's just choices.
There's lots of options. Yeah. Yeah. Well, that's
a real issue in itself. But
Yeah. You go back, like, if I wanna
buy, and I'll just say brand x
MES,
they're going to probably want me to have
the Cadillac of every other product they have

(56:43):
and that doubles the price. It's like, I
really don't need that.
I really don't need the Cadillac. You know,
you you actually make, you know, you make
compact cars too. Those work well. You know,
if you if you're if you're if you're
not, you know, for the use case. But,
well, I I guess the last question go
ahead. Go ahead. It's just giving him a
choice. That's all. And then walking him through

(57:04):
the path. Being
don't don't be the a hole philosophy. Right?
Like, help them through their choice, whether it's
to you or to somebody else.
Yeah. Absolutely.
So I guess my last question is if
we've if any of the audience out there,
we have the best audience in industrial automation,
if any of them say, you know, we
should look at this, like, who would they

(57:24):
contact to maybe do like a Teams or
a Webex or, you know, a Zoom call
to learn more about what you guys do?
Yep. We're a put up or shut up
kind of a house. So if you go
to,
our website, there's a there's a request demo
form that'll allow you to to ping, and
we'll reach out from our teams or our
side of the house to set up that

(57:44):
that call. So we'll ask you a couple
questions so we don't waste your time and
show you something you're not interested in. But
then we can set up a live demo
and literally walk through the MES. But the
other side of the house is you could
sign up for the product and play with
the work instruction side of the house and
the digital tools for free. And then that
way, you're not just listening to me about
what it's like. You can actually experience it
for yourself. There's also a boatload of YouTube

(58:06):
videos and things like that too.
So and I I just wanna jump in
here and say for those people walking their
dog or, you know, driving home during their
busy commute, could you give them your website
URL? Yes. Yes. Picomes.com.
So picomes.com.
Yeah. Super easy. You can't get better than
that.

(58:26):
Well, Ryan, I want to thank you for
coming on the show. I really enjoyed talking
to MES. I haven't talked to MES in
a while and, talking,
ISA 95 and all this stuff. And I
do think there's a lot of smaller factories
out there that can use a product like
yours. So I really wanna thank you for
coming on the show.
Thanks for having me, Sean. And sorry for
the rabbit holes of going into, but it
was really fun. I enjoy the the kind

(58:48):
of back and forth like this. So,
and for anyone listening, you know, if you
wanna get into the weeds on the technical
conversation, I'm I'm available on LinkedIn. You can
find me there or just reach out to
Pico and they know how to get a
hold of me, but I love having these
kind of conversations
too. I hope you guys enjoy that episode,
and I wanna thank Ryan for coming on
the show. And I wanna thank our members

(59:09):
who made the video edition of this episode
possible. You will find
the video edition in the members only areas
on both YouTube and on the automation blog.com.
So thank you to our members for supporting
the work we do here at Insights and
Automation.
And with that, I, again, wanna wish you
all an awesome Thanksgiving weekend. Hopefully, you get

(59:29):
all 4 days off,
and I just wanna wish you all good
health and happiness.
And until next time, my friends,
peace.

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