Could We Really Make Anything, Anywhere, Anytime? A Deep Dive into Distributed Manufacturing - Dr. Charles Johnson-Bey, ERVA Co-Principal Investigator - The TechEd Podcast

Episode Transcript
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Matt Kirchner (00:00):
Matt? Well, it's another week and another episode

(00:10):
of the number one podcast inSTEM and technical education. My
name is Matt Kirkner. I am thehost of the TechEd podcast.
We're going to have a lot of funtoday talking about some really
cool research in the world ofmanufacturing that has been done
released in a report we aregoing to talk with the CO
principal investigator of thatreport. It is Dr Charles Johnson

(00:32):
Bay. He is the Irva co principalinvestigator, Senior Vice
President of Booz Allen Hamiltonrecently retired, as I
understand it. And so Charles,let's start out with just
welcoming you to the TechEdpodcast. So awesome to have you
with us.

Charles Johnson-Bey (00:46):
Man, it is such a pleasure for me to be
here. I'm an educator at heart.
You know, the former professorat Morgan State, this is a great
place for me to be. And so justreally happy to be with you.
Yeah,

we're happy to have you. We're having so much
fun. And you know, our audience,as you suggest, includes a lot
of educators, and they're goingto love hearing about the work
that you've done. Certainly atthe university level, we have
educators as well from Technicaland Community Colleges, k 12
industrial trainers and lots andlots of people that are
interested in STEM and tech edin general. I know they're going
to really enjoy this episode.
Charles and like I said, it'sawesome to have you here. I

(01:19):
mentioned in the intro that yourecently retired from Booz Allen
Hamilton, I think our listenersprobably know one of the more
iconic consulting firms on theplanet. So great career in
consulting, but your careerwasn't limited to that. You
spent time in engineering and inleadership roles at places like
Lockheed Martin, Motorolacorporate research labs, and as
you just suggested, you're aprofessor at Morgan State

(01:41):
University. What a greatbackground, what a wide variety
of experiences you've had.
Charles, looking back at that,talk about some of those common
threads on that journey, andthen how it ultimately led to
your work with Irva, which, bythe way, Irva is the engineering
research visioning Alliance. Sotalk about that a

bit. Yeah, thanks. So honestly, it's one
more name I have to say in therefrom my education, and that's
the Baltimore PolytechnicInstitute, or poly. Poly is an
engineering High School. It'sthe engineering high school in
Baltimore. That and my oldestsister sort of got me on this
road. I say my oldest sister,because she would make me do

(02:19):
math problems over thesummertime. Yeah, so I wouldn't
embarrass her, as the littlebrother coming into school, she
was like, you're gonna knowthese problems. You're gonna do
this over the summer. So thatwas fun or not, but I do like
math now. So you know, we getsomething from it, for sure. But
I will say that I've really havebeen interested on just how
things work, but not just thetheory of it, but just the

(02:42):
practice as well. Like, how doyou demonstrate things? How do
you bring things so that frompaper into realism that just
hints right there tomanufacturing. And so just going
through school, I think what oneof the things that I focused on,
and even in my PhD, was, youknow, looking at the hardware
and how do you design somethingthat, you know, on paper and

(03:04):
math sort of works out. But thenhow do these electrons and all
this stuff make it work? Ithought it was magic, and I
wanted to learn magic, to behonest, Matt, so that's sort of
how I got on my way.

I love that. You know, we just had our last
episode was with JordanEllenberg, who wrote one of Bill
Gates his 10 favorite books. AndJordan talked about that. Talked
about that. Talked about, if youunderstand mathematics, it's
almost like understanding magic.
You understand engineering, it'salmost like understanding magic.
And by the way, the fourth PhD,as I understand it, or at least
close to that of your family. Sothat's incredibly good genes
that are going on at the JohnsonBay household. Obviously, I

(03:36):
could tell you, Charles, I havea younger brother, I made him do
a lot of crazy things over thecourse of the summers that we
had growing up together, none ofthem involved doing math
problems. So credit to yoursister for challenging you that
way. And obviously created abrilliant brother, and one that,
by the way, as we mentioned inthe intro, co principal
investigator on this engineeringresearch visioning and Alliance,

(03:58):
or Irva report, helping to guidenational conversations about all
the great things happeningacross society and what the role
of an engineer and thediscipline of engineering in
general can be around all ofthose challenges taking place
across our society. So what drewyou personally this topic, you
call it distributedmanufacturing. Why is that topic

(04:19):
interesting to you? And maybejust a little bit on what your
definition of distributedmanufacturing is?

Yeah, thanks. So I know originally we
had talked about maybedemocratizing of manufacturing,
but that's such an essay T word,right? Nothing wrong with SAT
words, but we thought thatdistributing would be something
that was just a little a betterlanguage, right? Better term for
that. And so what really we weretalking about was, how can

(04:48):
anybody, anywhere at any time,build and manufacture something
that they need, right? And oneof the things when we were
talking about this was, rightduring covid. Right? And if we
learn nothing during covid, welearned about supply chain.
Like, everybody started talkingabout supply chain, oh, we can't
get this because we can't get itnow. And so we were, like, from

(05:12):
a national standpoint, that'ssomething that's gotta be
addressed,

right? Yeah, no question. I mean, you think
about the whole idea of supplychain, and you know, the way we
say it on the TechEd podcast iswhen you could get what you
wanted, anytime you wanted, at aprice that seemed fair. Who
cared about supply chain, right?
Nobody was in thinking about, Iwas going Amazon or wherever,
and I order it, and it shows upin my front door, not too much
to worry about. And then all ofa sudden, to your point, this

(05:35):
hiccup called covid, and we'vegot all these ships stuck on
docks, and we can't get productin. People can't get materials,
and all of a sudden, whateverthat thing is that you just took
for granted doesn't show up atyour house. And it's like, oh, I
guess this does come fromsomewhere. I guess somebody does
make this. I guess it doesmatter where this gets made.
It's interesting that definitionof distributed manufacturing, if
I looked at at a standard as astandalone word, I'd be

(05:56):
thinking, well, what is thislike? Supply chain distribution
thing? Or what is it? And itfeels more, and you can tell me,
if I'm getting this right, itfeels more like the idea is, how
do we make manufacturingavailable to everybody, whether
that's on the supply chain side,whether it's, you know, people
interested in getting into thediscipline of manufacturing is,
you know, I made my living therefor 25 years and still spend a
lot of time in and aroundmanufacturers. Am I? Am I

(06:18):
getting close in terms of howyou're thinking about this.
Yeah,

you are.
It's two points I want to makethere. One, if we look back a
little bit at the history of theUnited States, right, where the
manufacturing boom happened fromabout 1940 till about 1979 or 80
we were booming in the UnitedStates, and that was an area
where folks could get a job, getinto the middle class, make a

(06:42):
good living, all of that in thiscountry. But now, over time,
that has declined right sincethe since about 8182 forward.
And so we're going, you know,we're sort of in this thing of
coming back. And so we've gotthings now today, like the chips
act and things like that. That'slooking at manufacturing in the
United States and bringing itback. And so again, we thought

(07:04):
this was an important point forIrva to look at, because the
thing I really like about Irva,and again, it's the engineering
research visioning Alliance.
It's sponsored by the NationalScience Foundation. We don't
lobby, so we don't tell NationalScience Foundation, sort of what
they can fund and do that, orCongress, or anybody. So we

(07:24):
really convened sort of about 50of the best minds in a given
area from across the nation tocome together to look at global
challenges that have nationalresponsibility, and what can
engineering do to help move usforward. And so just that kind
of convening takes is an art initself. I will tell you that.

(07:47):
That is, you bring 50 people inthat all have opinions and all
of that, and getting them totalk with one voice is, I think
the thing that Irva, I think wedo pretty well, right? I think
in so part of this distributedmanufacturing was to bring us
together to talk about that, andnot just your area of research,

(08:08):
but how do we as a nation facethat? What are some of the
questions that we've got toanswer? And then the second
part, though I want to hit on alittle bit, is innovation. And I
certainly have a different takeon innovation. You can't talk
about innovation unless you talkabout your constraints. Because,
you know, if you mentioned, ifyou've got everything you need,

(08:29):
at the price you want and allthat, why do I have to be
innovative? Right? I've goteverything, but if I don't have
the resources, if I don't havethe material, if I don't have
those things, I really got toget innovative and think about,
how do we do this? And so that'swhy we really looked at an
extremely challenging problemof, how can we manufacture
anywhere, anytime, right? Andthen we also talked about the

(08:52):
waste and all that. So it's allthose other side pieces that
come along with this

absolutely well, you know, as you're saying that,
first of all, I won't tell youhow offended I am that you
brought together the 50 greatestminds in engineering and
manufacturing, and you didn'tinvite Matt Kirkner, the host of
the TechEd podcast. I'll getover it, but

email it said you said you were busy. I
must have

been number 51 is my guess. I'm just guessing I
was the last guy to get cutbefore you got to the top 50.
I'm kidding. Of course, thatsounds like an amazing group of
people. The other thing that Ireally think is amazing and
interesting when we starttalking about constraints in
manufacturing, and that youbrought that up, I mean, to me,
my life, my manufacturing life,changed 30 years ago when I read
the book The goal by gold rat,he wrote the theory of

(09:35):
constraints as well. And it'snot luck, but just a phenomenal
author in the area ofmanufacturing and looking at
constraints and manufacturingprocesses. And I think you're
exactly right. And you know,anything continuous improvement,
improving yield, improving cycletimes, improving quality. I
mean, any of those things comeback to looking at what your
constraint is in a process whichdoesn't necessarily, by the way,

(09:56):
have to be limited to themanufacturing process itself. So
you. Your point, it might be aconstraint of, how do we get
materials, or what materials arewe using, or proximity to
suppliers, proximity tocustomers, all these different
constraints that we can find youtalk about waste, believe it or
not, I made my kids, who are now25 and 23 when they were about
eight years old. I made themprobably 10 and eight, something

(10:18):
like that, memorize the SevenDeadly Wastes. And to this day,
each of them can tell you theseven deadly waste in
manufacturing, of course, thatwas brought to us by Taichi Ohno
of the Toyota Production System.
But identifying thoseconstraints, identifying those
wastes, you and I are 100% onthe same page. Talk about the
report in which you know, if yousay we're putting these things
on the table, we're talkingabout waste. We're talking about
constraints. We're talking abouthow we need to be able to

(10:39):
manufacture anything anywhere. Iagree with you. I think that's
where the economy is going.
Where the manufacturing economyis going is with with processes
and manufacturing getting closerand closer to the point of
consumption, for a whole bunchof reasons. We'll get into but,
but let's just kind of sit uphere at 30,000 feet and tell us
about the report engineering.
The future of distributedmanufacturing, by the way, is

(11:00):
the report's name, and we'll besure and link that up in the
show notes as well for ouraudience. But go ahead, what are
you up to in that report?
Charles

Matt, as you know, manufacturing is such
any topic is just a big topicwhen you're looking at on a
national scale. So one of thechallenges, not just for the
manufacturing but also the othervisioning events that we put on
is we need to have somethingthat's big enough that will have
national impact, but focusedenough that we can get people

(11:28):
around to talk about it and haveand focus on what are those key
questions. And so in this case,we came up with sort of the
three big grand challenges totalk about. One is the material
supply chain. So how do wedesign the next generation
materials for manufacturing thatenables synthesis and non
polluting, recyclable andrenewable materials? Because,

(11:51):
again, you don't want to dosomething good, but then you got
something bad on the back end.
So we wanted to be very mindfulof that. Next is tools and
processes. So how do we designnew systems based on adaptive
control with closed loop? Howcan we have sort of like some
swarming manufacturing thatenable multiple small tools to
impact what we're doing and thencreate sort of this open source

(12:15):
hubs, right? So, though peoplecan understand, these are the
processes that are going on.
This is how you can improvethings. And then the third
thing. So again, first ismaterials and supply chains. The
second one is tools andprocesses. The third thing, and
it's, you know, all these areequal, but I think this one
might be more equal than theother two. Sounded

like George Orwell in Animal Farm, right?
All animals are equal, but someare more equal than others.
Okay, go ahead, thank you.

See, it's just like that, right? Good
book, by the way. It is goodreference. It's just data and
quality assurance. And I thinkthis is actually the thing
that's really going to be thedriver going forward. Sort of,
how do we share data? Becauseright now, people are like this,
right? I don't want to share mydata, or do I trust the data

(13:04):
that's being shared with me? AndI think those that's extremely
important. And how do we get tosome model based, you know,
certifications and things likethat?

For sure, I certainly agree with those three
tenets as being incrediblyimportant in the world of
manufacturing, obviously,materials and sustainable
materials. We'll talk about thata little bit more. No question,
the tools we use important. Youmentioned a term. Most of those
terms you mentioned, I'mfamiliar with. Swarming is one
that I'll admit, I'm not sureI'm totally familiar with. Can
you share a little bit moreabout what you mean when you

(13:34):
talk about swarming as a tool?

That's a good, good question. We've got
references for that, so we'llshare those too, so folks can
look it up. But really swarmengineering is, how do we use
multiple small tools likesubtractive, additive form, join
those kind of things to helpsolve a problem? Right? So we've
got these things all comingtogether, all these I'm going to

(13:56):
call it different disciplineswithin manufacturing to help
solve a problem. And it's reallyhard, as you know, for small and
medium size, which most of thebusinesses in the United States
are, it's probably, what, justover a half a million of them.
But you know, they're all smalland medium, so it's hard to do
that. So how do we get them towork together to solve a

(14:17):
problem?

It's fascinating, if you don't mind me invoking a
comment from, actually, one ofBooz Allen's competitors,
McKinsey, we had their GlobalDirector of Strategy on aztage
party a year or so ago. He talksabout, actually wrote a book
about it. But he says, you know,70% of innovation in the United
States of America happens insmall to medium sized

(14:38):
manufacturers. And I think youknow, of all r, d, of all
innovation, 70% of thatinnovation is happening inside
of small and medium sizedmanufacturers. So I think you
make a really interesting pointwhen we talk about those size
businesses where there'stremendous amounts of
opportunity to innovate, but alot of times those companies.
And you can tell me if I'm onthe right track here, if I'm a
machining company, I knowmachining, if I'm a fabric.

(15:00):
Education company I know weldingand wire bending, and you start
to think about, there isprobably never any one best way
to manufacture a product, butthere may be an optimal process
to use. And maybe it's additive,maybe it's subtractive, maybe
it's metal fab, maybe it'scasting. I mean, there's all
these different manufacturingoperations that we could
utilize. So a little bit thisidea of swarming is, let's pull

(15:21):
subject matter experts fromvarious disciplines together to
say, Let's exchange some ideas,and let's see if we can't
optimize this process with ourcollective knowledge. Is that
kind of what you mean byswarming?

Yep, absolutely. And the thing that
we're going to need for that,and something that's going to
help enable that, are thebusiness models, right? So we
really have to look at, what areour current business models?
What are the new business modelsthat we need? And again, that
hits sort of the constraints,right? Because right now, people
have their business model, theirinvestment, what they do, and

(15:52):
it's like, I make my money thisway, right? Or I make an impact.
Because not all of you're inbusiness to make money, but
you're also most folks inbusiness to make an impact,
right? For sure, in the area100% so how do I make a better
impact and reap the rewards ofthat? So I think that's also
gonna come from focusing in onthis area, in this way,

you know, running several businesses that are
focused on securing the AmericanDream for the next generation of
STEM and workforce talent. Weknow all about what it's like to
run a business to make animpact. And I think you're
right, and that surprises somepeople, sometimes too, where,
you know, if you haven't spenttime in and around manufacturing
in general, or business ingeneral, manufacturing
specifically, you know,sometimes people from the

(16:30):
outside looking in will be like,well, those guys are just all
about making money, forgettingabout the fact that you have you
know, almost every manufacturerthat I know cares deeply about
their people. They care abouttheir customers. You know, their
teammates and their teammatesand their team members, their
customers, their suppliers, thegreater environment. I don't
just mean that environmentallyand sustainably, but that's
important too. But just ingeneral, the community that

(16:52):
they're in, and I think thatgets lost sometimes, is that,
you know, manufacturingspecifically, can have a huge
impact in a lot of differentways, not the least of which, of
course, is continuing to improvedesign, making products
available to consumers at alower price, doing that
sustainably. I also, by the way,will agree wholeheartedly with
that third point, and the moreequal than others on the data
side, and I think that it'sbecoming even more equal than

(17:14):
others as time goes by, and wesee the incredible role that
data can play. If we can captureit, we can acquire it and then
we can analyze it in a way thatprovides usable and actionable
outcomes, really, reallyimportant. So I want to dive a
little bit deeper in our nextquestion. Charles, on that first
topic you mentioned, with regardto materials, I've probably no
less than a dozen times on thispodcast, talked about a book

(17:35):
that I read within the lastseveral months called Genesis.
It was written by HenryKissinger, co authored by Eric
Schmidt and Craig Mundie.
There's a whole section in thereabout in the age of AI, and the
whole book is around artificialintelligence in the age of AI,
how important materials aregoing to be, how much innovation
we're going to see in the futureof materials, that being able to
use a large language model andan AI agent and understanding

(17:57):
different material properties,we're going to have new
materials that nobody's everthought of that are going to be
stronger, they're going to belighter in weight, in some
cases, they're going to besmarter, they're going to be
more environmentallysustainable. Certainly, that's a
topic that really, reallyfascinates me, and I think is
going to be front and centerhere more so than it's ever been
in the field of manufacturing.

(18:18):
Talk for a bit about whymaterial engineering is such a
linchpin in your mind fordistributed manufacturing. You
mentioned sustainable materials,but, but why is that important?
And you know, let's dream alittle bit about some of the new
opportunities that we may unlockin the

future.
When we talk about materials,we're not even talking about
just the material itself, but wetalk about housing material
developed. Where do you get it?
Where does it come from? Like,if it's got to come from a far
place, that's something thatgets fed into the equation,
right, of the business and howwe do it, and then once it's

(18:52):
used, what happens to the waste?
Right? If we get a waste of thatthat is harmful, then we're
going to have to deal with that,right? And it's a whole bunch of
regulations and all thatcircular and that. But if we
could develop materials where wecan use the waste, right, if we
have it such that we can look atmaterials like bio based feed
stocks that can be reused, welook at novel alloys and

(19:16):
composites, things that canreplace the difficult to obtain
materials, and the output, sortof the waste product of that
feeds into another part of theecosystem, right? I think that's
the thing that is going to helppropel this thing forward and
even generate ideas that peoplehaven't thought of, right? Oh,

(19:38):
now we can do this, and wedidn't know this. And again,
when we talk about the small tomedium sized businesses that are
all in manufacturing, and whereare these businesses? They're in
neighborhoods, right? They're incities like yours and mine, and
where people are talking and sothat just helps the ecosystem of
the city get better, right? Andthat just helps, again, the
United. And it states getbetter. And, you know, not to

(20:00):
say on motherhood or apple pie,but man, we're all in this thing
together. And if we can do somethings, I think that's I think
this helps everybody, to behonest,

you and I are 100% aligned in that regard. And
solid manufacturing economies,solid outputs, doing it
sustainably. All of that playsinto a stronger community, more
opportunities for everybody.
We're so we're 100% aligned onthat particular topic. You know,
you think about this whole fieldof materials and what we're
going to be able to do now byanalyzing data and engineering
at scale and quickly, and thensome of the outputs. You know, I

(20:32):
think there's an old schoolexample that just came back to
me on Friday night as we recordthis, on a Monday morning, I was
walking with my wife in ourneighborhood, and I smelled
chocolate, and not justchocolate in general, but like a
really, really familiar smell ofchocolate. I'm like, Man, that
smells good. And I'm like, issomebody baking cookies or
whatever? And then we walk bythis that are one of our

(20:52):
neighbors about half a mile awayfrom us, just re landscaped our
front yard, and what they usedfor their mulch was cocoa bean
shells, believe it or not, andthere are companies that would
make cocoa, but then they hadthese shells that were left
over, and they created this. Imean, it's a really simple
example, but it's a byproduct ofrather than just putting those
shells in a landfill or puttingthem out somewhere to rot away,

(21:13):
they actually repurposed them.
Created another revenue stream,right? Because they're selling
that now to somebody that'sgoing to use that in their yard.
And so we that's like a reallysimple idea, right? Everybody
knows what a cocoa bean lookslike, and everybody knows that
it comes in, or that, you know,it's grown and has a shell,
repurposing those shells. Andthen you start thinking about,
to your point, getting into someof the way more complex

(21:34):
scientific considerations about,how could we repurpose something
into a clean biofuel, or whathave you. So it's not just
thinking about the manufacturingprocess itself and making sure
that the process is sustainable,that the materials are
sustainable that end up in thatproduct. But maybe there's a
byproduct of that that is alsohas another purpose, right? It

(21:54):
plays on itself for creatinganother revenue stream, or for
that matter, once that product,whatever it is has reached the
end of its useful life, thenwhat happens through it, and is
there an opportunity torepurpose it? Am I? Am I getting
that right? Is that what you're

thinking?
That's absolutely right. And Ido think that AI is something
that can help us right. This isCharles Johnson Bay's opinion. I
believe that the technical folkswho are developing these tools
and technologies, I think wehave to do a better job of
explaining what they can do andwhat they can't do and what's

(22:27):
possible and what's notpossible. And I think in the AI
space, we aren't doing a goodjob of that, you know, I'm a sci
fi guy, right? It's a wholebunch of sci fi movies out here
and, you know, and people arethinking, AI is going to do this
that the other you know? And I'mlike, Yeah, we got to do a good
job of saying this is a toolthat people are using. It's not

(22:49):
going to take over. I want toqualify this. Yeah, it's not the
AI that's going to take overpeople's jobs. It's the people
who know how to use AI and knowhow to use it. Those are the
things that are going to takeover the jobs, because they know
how to use this new tool to howto do it. So it's not the tool
itself that's going to takeover. Agree, it's not. I think
that if we understand what itcan do, if we understand that

(23:12):
this thing can go through a lotof iterations and look through
the ecosystem of a material fromstart to finish and then help us
jump start, sort of how we canuse it. Then I think, yeah,
we're in pretty decent shapethere. I think that's a good
place for research. No

question, that's a good place for research. You
know, we talk quite often. Infact, I'll steal a line from a
former guest on the podcast bythe name of Dr rich Barnhouse,
who's the president of WaukeshaCounty Technical College in
Southeast Wisconsin, who told meonce, and I use it over and over
and over again, will AI takeyour job? And the answer to that
question is no, but somebodyusing AI might. And so the whole

(23:50):
idea is that, you know, AIdoesn't need to be a threat. If
two things, I think you make agood point about, let's
recognize that there'sapplications where it's gonna
work, and in the end, it shouldbe a problem solving tool. It's
not any different than any otherlean tool we use in
manufacturing. It's a tool thatwe can use to get to a greater
answer, to get to a greaterpurpose or a greater result. But

(24:10):
it really does speak to thiswhole idea of upskilling the
next generation of young people,and really people of all ages
around the applications ofartificial intelligence
understanding, what I like tocall the edge to cloud
continuum, that it's not justwhat chat GPT is doing, or how
you could use Cloud or meta AIor perplexity, or whatever
platform you're using. I use allof them to answer a question or

(24:33):
to solve a problem or to figureout a recipe, or all those
different things that we usegenerative AI for. But also, how
are we gathering data on theedge? How are we acquiring that
data? How are we analyzing it onthe edge? Where does it go? What
kind of a control system are weusing? I know I'm going down the
rabbit hole here of controlsystems, and I think I read in
something that that's aninterest of yours as well. We

(24:53):
could probably do a wholeconversation on lateral logic
and PID control, but we'll sparethe audience that conversation

I got.
Patent in that area. Yeah,really,

what's your patent

on? That's why I like you, man, because,
like, look, hey, man, let's talkabout it.

Yeah, you brought it up.

Yeah, this is work that I did when I was at
Lockheed Martin, and we wereworking with the Navy. When
you're on a ship, right? It's alot of systems, right? You got
you right, machinery, plant,control, monitoring system, it's
a lot of stuff happening, andyou only have so many people,
right. And so the patent is on,how do you continue to maintain

(25:32):
control and situationalawareness on a ship that size,
that's minimally personed, huh?
Right? So we are agnostic on thehardware. So regard there are
certain things that arefundamental to big systems like
this, and so we came up with away to be able to maintain that
control and keep things movingwithout a lot of people.

Fascinating. I toured a few years ago, Charles
an aircraft carrier. You workedat Lockheed Martin. You spent a
lot of time around that kind oftechnology. Kind of technology.
And I hadn't, I'm a lifelongMariner, but not somebody that
ever worked on that aircraftcarrier, a large military
vessel, and they had, like, awhole machining shop on the
aircraft carrier. I mean, like,literally, yeah, I mean, and

(26:14):
you're looking at me, like,Yeah, no kidding, but yeah, I
was just shocked by that, thatthey've got, you know, all but
you think about it. I mean,you're deployed, you know, in
the Middle East and the SouthChina Sea. I mean, wherever it
is that you're you're doing yourthing, and all of a sudden
you've got to be able to fix aproblem, repair a part, what
have you. They had their ownmachining center sitting right
there. That was, was really,really fascinating. It's kind of

(26:34):
like the ultimate in puttingmanufacturing and production as
close as you can to the point ofuse, right? It was really right
on the on the aircraft carrier.
Which kind of leads into my nexttopic in question, which is your
whole idea of doing exactly thesame thing. You know, we started
a little bit while ago talkingabout localized supply chains
and about the appreciationeverybody got for having
manufacturing proximate to wherethey were consuming that

(26:57):
product. Actually did an episodeof the podcast, it's been
probably, I don't know, 10months or so ago with Barbara
humpton, who's the CEO ofSiemens, USA, and we talked
about this, her belief, and mybelief, that we are in the
middle of this trend where weare going to see manufacturing
getting closer and closer andcloser to where we're consuming
the product. It takes out allthe supply chain risk, takes out

(27:18):
the transportation costs, takesout all the inventory risk. We
also are able to be a lot moreresponsive to the needs of local
consumers and so on. Lots morevariety, lots more choices. Is
that the way you're seeing it?
Why do we need to enable more ofthis agile and localized
manufacturing? And then to yourother point about data, what

(27:38):
role is data going to play inthat process.

Great questions. And I believe Siemens
is they're a big conglomerate.
They're old. They've been arounda while. I really like their CEO
and their CTO. I think they havea very good vision, because what
they're doing, they're pivoting,right? They're pivoting in this
space and looking at how AI canhelp them with manufacturing.
They've got a big global r, d, Ithink their North American hub

(28:03):
is in Princeton, New Jersey, sothat's a company that is really
doing things among others. But Ithink that getting to the point
you just brought up a real it'sa really beautiful point where I
think that the bringing thingscloser together, right? That's
getting right back to, I guess,the title of the report, right?

(28:25):
Because, from a distributionstandpoint, how can we do it?
How do we bring things closertogether so that we can do that?
Things that sound potentiallyimpossible today, in the future,
they won't be but also, whenbringing, also the matter of the
ship that you talked about,that's all constraints, right?

(28:46):
So we're in a ship route, in thenotion we need this stuff. How
do we do it? Oh, well, let'sbring us a little, small
manufacturing place, right here,on ship, right? In order to do
that, it can't have a huge powerdraw, right? It can't vibrate,
but so much because you don'tnecessarily want to be seen at

(29:06):
certain times, so you don't wantto put signatures out there.
Just getting into the wirelessthing, another I led a vision
event on wireless comms, whichis a whole nother subject that's
fascinating, but it's certainthings that you've got to take
into account and to get up.
That's why I like engineering,because you've got to figure out

(29:26):
all these problems, these realworld problems, to make it
happen, right? So those arereally good examples of that.
And now getting down to data, Iwant to talk about data from a
couple of standpoints. The firstone, there's certainly sort of
in situ data that still needswhile you are manufacturing,

(29:46):
while this thing is in process.
I think there's research to bedone in those areas of, how do
you collect that data? Right?
How do you help a machine or theautomation get better while
it's. Going instead of waitingto the end. There's a lot of
stuff that we can do in digitaltwinning, in computer and math
and things like that. Butultimately, we got to get down

(30:10):
to a thing that I always like tosay, something you got to hit
with a hammer, right? So how doyou make that so that it has the
right ting when you hit it withthe hammer that you want it to
while it's being processed. So Ithink it's a lot of research
that can be done. And we talkedabout that in a report, you
know, just an in situ data like,how do you gather the data? What

(30:32):
are the type of sensors that weneed? How do we communicate that
data? Is there a way in which wecan commonly sort of collect and
identify that data so that weall know what we're talking
about while we're doing

it. I think that's exactly where it's going.
Charles is, you think about theevolution of manufacturing, and
even in my lifetime, you know, Ispent my 25 years, whatever it
was in the manufacturing world,starting kind of early to mid
1990s or so. And even back then,you know, he started out, and
you kind of knew you had aproblem when a problem when a
customer complained about it,right? And then somebody said,

(31:04):
Well, okay, what if we couldcatch that in final inspection
and before it ever leaves theplant? And so we started
inspecting things at the at thereceiving or at the shipping
dock, or maybe we had adepartment called inspection
where things went, and we'd, youknow, we do samples and
whatever, and not to say thatwe're not still doing that,
because certainly we are, andthere's and that's important.
But then we backed up and wesaid, well, what if we could do

(31:25):
in process inspection? So ratherthan having this thing go
through five differentoperations and then to final
inspection to find out that wemade a mistake in operation two
a week ago and kept adding valueto a product that we couldn't
ultimately sell to a customer,how about in process inspection?
And now we're in this age wherewe're able to pull data in real
time, right? I mean, with smartsensors and devices, they've got

(31:45):
embedded intelligence. They cancommunicate with each other,
proximity sensors, lightsensors, ultrasonic sensors,
smart RFID, smart barcode, smarton light smart. I mean, we've
got all this ability to pulldata in real time and then
create a large language modelout of that data. You're right.
There's a ton of research to bedone there so that we can using
data as opposed to an inspectionprocess. And I should have had

(32:07):
your computer vision too, ishaving a huge impact on that.
And then we can use data toidentify an anomaly in our
process. And then let's get tothe point where we're not
identifying an anomaly in theprocess. Let's model it in a
digital twin to your point, andlet's find that anomaly before
we ever build the machine orbefore we ever produce the part,

(32:28):
and then fix the problem beforewe ever have it. Is that kind of
what you're thinking?

Yes, Matt, you're a perfect spokesperson.
That is the flow, right? Becauseit all makes sense. And we start
looking at these ecosystemsbased on the need and the
constraints and what we have.
And again, these are problemsthat we need to focus on. And
one of the things that I'll talkabout is in the report we bring
out here, what are some of thecritical questions within a five

(32:55):
to 10 year standpoint, withinthe 10 to 20 year standpoint and
then a 20 plus year standpoint.
Because our challenge a lot oftimes, this is quoting one of
the matrix movies. People thinkfive minutes in front of their
face, right? It's like you justgave them the bridge, right?

(33:16):
People think two minutes, fiveminutes in front of their face.
We need people to think out 20years and say, and it's hard,
right? Yeah, it is hard. Butwhen you think about sort of how
quickly technology moves, whatare some of the things 20 years
from now that we need to belooking at? And then we can back
that up into the five to 1010,to 20, that way. So then we can

(33:37):
start saying, Okay, this isreally novel. This is really
bold. These are things. Theseare areas to go. And when you
lay out, sort of the flow, asyou just eloquently did, that's
the thought process of an urbanvisioning event. I

love that you're looking out into the future. I
mean, is there something youknow, take us forward 20 years?
Is there something that kind ofpops into your head that says,
This is the world ofmanufacturing in the year? What
would that be 2045, so 100 yearsafter the end of World War Two,
what does manufacturing looklike? Yeah, make sense.

So yeah, actually, I'm gonna name one
thing from each of our thing, ifI can. Yeah, go for it. So for
materials, one of the thingsthat we talk about in the 20
plus years is develop AIalgorithms for material
substitution, addition orreplacement of other materials
based on Property Performance,trade offs from shared adaptable

(34:28):
knowledge and sustainability toprevent waste, so no waste.
Yeah, right. And then algorithmsshould take into account
regional availability tooptimize options that account
for local materials variability.
So looking within your space,what do you have? What can you
use so that you have no waste?

(34:50):
You manufacture, you gotsomething that you hit with a
hammer and it's no waste? Yep,beautiful. That's one. Let's
talk about tools sostandardized. As raw materials
and processes, tool heads androbot lineup and establish a
global supply for the standarditems. So what are some standard
items that we need? And thenwe'll just line these things up.

(35:12):
So we've got a lot ofautomation. We've got some
robotics, right? So you gottaneed to manufacture the robotics
that we have, very much likeyour logo, right? And all that.
And then we distribute, right?
The autonomous general purposefactories capable of handling
the product life cycle fromcradle to grave, right? So being
able to do that 20 years fromnow is like a vision. So what

(35:33):
research do we need to do tomake that happen?

That's so cool.
Let's go a little bit deeper onthat too. Charles, you know, you
think about this whole idea oftools, and we and we've talked
about data and manufacturing.
We've talked extensively aboutmaterials, you know, the
equipment we use inmanufacturing. I toured my
friends, brand new to him, hejust bought a manufacturing
company within the last year orso, and I hadn't been there, so
we, I did a tour about two weeksago. He had a machine in that

(35:59):
plant that was built in the1950s right? And it was still
just cranking product away. Imean, literally, this thing is
now 75 years old. I rememberwhen I was running for Rockwell
Automation, a great automationcompany, by the way, we gave a
shout out to Siemens, and I rana Rockwell spin off for 10
years, you know, number of yearsago, and we had a piece of

(36:20):
equipment in that plant, believeit or not, that was pre World
War Two that was still producingparts, was still generating
revenue. It's just just crazyand it, but it was, you know,
it's built for one purpose, andthat was the purpose that it had
served in that case, for, youknow, 6070, years. So now here
we are, and you're starting totalk about machines that are in
you just kind of teed it up inyour last discussion about

(36:42):
having an autonomous factory, aMobile Factory, versatile
factory, machines that are,quote, small, agile and
reconfigurable, which reallykind of fascinates me. Most of
the manufacturing equipment wehave today are built. It's built
for a single purpose, or atleast it might be like a
machining center. It's built tomachine product. It might be a
punch price that's built tofabricate product. What do you

(37:03):
mean by small, agile andreconfigurable machines, and
what does that look like for thefuture of manufacturing? Yeah,

so I think all these topics are, like, just
great research areas. I'm like akid in a candy store. It's like,
Oh man, that looks that looksgood. This looks good, right?
All that. But one thing I wantto say quickly about just the,
what I'm gonna call the older,maybe older technology, just
from a date standpoint, yeah,man, just because it's new, or
just because it was thought ofor built in 2025 doesn't make it

(37:32):
better. You and I both seemachines that are working and
continuing to work. What bringsto mind, like this micro
controller called the PDP 11that NASA used for space
applications

for years, right?
Yeah, we still see slick fivehundreds in manufacturing,
right?

That's right, that's old school stuff.
So getting on hardware. I'm aelectrical engineering
education. We have a thing whereyou can have a common something
that is specifically built for agiven purpose, right? And then
we had chips where we would callthem field programmable, right,

(38:10):
where you could put them in thesystems, and if you wanted it to
change, then you could, youknow, sort of change some code
which changed the configuration,which gave you a new system. I
think manufacturing is goingalong a very analogous path,
right where you have machines.
Some are originally thought offor a given problem, but when
you look at how quicklytechnology is changing today, or

(38:34):
how quickly we are gettingsmarter at the things that we
can do. Actually. This ties backa little bit to the example I
was saying when you've gotmachines that are looking at,
sort of the data while thingsare happening, and then be able
to address and change itself.
Yep, I think that's where we'regoing. So sort of a field

(38:56):
programmable manufacturingprocess, and I think that's
probably first heard on me. SoI'm a, I'm going to trademark
that, but I think that'swhatever manufacturing, yeah,
real programmable manufacturing.
SPM, for short, that's right. Ithink that's where we're going,
honestly. And I think there'scertainly a need from that. I
think that now manufacturing,you got different flavors,

(39:18):
because you've got things likebio manufacturing we're looking
at like bio materials, I thinkthat probably is an area where
that field programmablemanufacturing is gonna work,
right? As you're learning aboutthe biomes, the proteins and
things like that, I think that'swhen you look at the constraints
and the need. I think healthcaregets better if we do that

(39:41):
better. So I think the pull toget sort of that field,
programmability, intomanufacturing, in that space,
right, it has a bigger need. SoI think my opinion is that's
where we would see it pop

fascinating. You know, first of all, you. At
that, that patent on situationalawareness, now you can have both
a patent and a copyright on FPMthat, there you go. Yeah, field
programmable manufacturing, Ilike another one of the topics
that I just want to dive intowith you here quickly, Charles
and again, it speaks back to thereport and some of the
recommendations and items thatyou considered is this idea of

(40:17):
common data standards. I shouldsay so the ability to commonize
standardized data. Talk aboutwhy that's important, and then
the other one is number five,with sector wide connectivity.
What's going to need to be donein order for us to not just have
that common data standard, butalso have connectivity across
sectors, whether that'stechnological connectivity or

(40:38):
just connectivity in terms ofpeople and talent.

Yeah. So certainly, when we look at how
manufacturing is going, and as Italked about collecting data and
having some standards on whatdata we're collecting, what does
it mean, the format, all thatthat's important. And I'm going
to talk about my friend daroda,who is the PI, the lead pi in

(41:04):
Irva, her and I attended amanufacturing conference
actually was leading up to thisvisioning event, and one of the
things that they talked about,that they talked about in that
conference, was how futuremanufacturers aren't going to be
the ones that have 2030, yearsof experience, but we're but
we're going to need these peopleto keep moving things forward in

(41:26):
the challenges that we have,both as a country and globally.
So having a standard data, howdo we do it? What do we collect?
And all that that is important,right? It's important for
decision making, becausemanufacturers must collect that
decision useful data, while alsoprotecting against cyber attacks

(41:46):
and stuff like that. So sotrusting the data, and also when
I believe the resiliency of thedata is what I like to call it,
because if you assume that thatit's bad actors or folks in
there trying to futz with yourdata or something like that, you
need to make sure that you havethe right data so that you can
use and then also trust to me,is a timeframe, right? So I can

(42:07):
I trust you over this time. Socertainly, a lot of research
that's going to go into that,but I think that the current and
the next generation operationsare going to require that sort
of effective, standardizedmethods for storage management
and sharing that data as we needto. Yeah,

there's no question that that's going to be
important, the whole idea oftrust. And I think it's
fascinating that you bring thatup, Charles, over a period of
time, trusting data, trustingthat your data is going to be
safe, recognizing andunderstanding what technology is
available to keep the stuff thatwe want to keep to ourselves, to
ourselves, and what we'rewilling to let out of our
plants. You know, back in theday when everybody was air

(42:45):
gapped and there was no way fordata to get out of an individual
facility, that was one situationnow where we have machines,
sensors, control systems,networks that are all sharing
data, talking all over, makingsure that we protect that secret
sauce that may be the magicbehind a specific manufacturing
operation, keep that secret, butalso have data that we can share

(43:05):
across platforms and acrosspeople. It's going to be really,
really important, not just forlarge companies, but probably
even more important for smallercompanies. You know, we've
talked a lot conceptually aboutsome of the recommendations in
the report. If I'm a small tomedium sized business, you know,
what should I be thinking interms of making this vision a
reality?

And this report, honestly, is for the
small and medium sizedbusinesses, to be honest. I
mean, that was the focus. So Ithink that a lot of the research
areas and all that are for thosesmall businesses, because that's
the heart, right? If we don'tget it right at the small and
medium sized businesses, thenwe're not going to get it right.

(43:44):
And us, manufacturing is such ata critical juncture right now,
and we won't maintain or haveglobal leadership if we don't
get that part right. I don'tthink we need to convince the
small and medium sizedmanufacturers that this is
important. They know it'simportant. They know the service
that they bring. But what Ithink we need to do is we need

(44:05):
the more general public to say,Hey, this is important to me,
and I need to understand it soit's so important to me that
there's things that I can do,right? I can do at home, like,
you know, the advent of 3dprinters and things like that.
Like, I have one in my littlesecret laboratory in my
basement, right? That my kidsbrought for me, but I love it,
right? So I've got one of thesethings. So things like that have

(44:27):
made things that were impossiblewhen you and I were younger
possible today. And so I thinkthat looking at re energizing
the manufacturing, especiallywhen we look at the use of AI
again, another tool. Let's startbringing these tools together
and saying, How can we do it?
And how can small and mediumsized businesses help solve some

(44:47):
larger problems by workingtogether? And I think this whole
idea of data and trust andworking together and business
models, I think that. That's thething that's gonna make it work,
just to inspire the folks to dothat, both academic, industrial,
government, all that. I thinkthis is a prime time and that's

(45:09):
why this particular podcast isso right on time and so
critical, because we need this.
And now's the time for us tostart focusing on it.

Now is the time to start focusing, indeed, the
next episode, assuming that weget together again, Charles,
we're going to do on locationfrom your secret laboratory,
just so, you know. So I thinkthe biggest, yeah, the biggest
news that we we've learned a tonof great news. But Dr, Charles
Johnson Bay has the secretlaboratory

complete with the printer and a foosball
table. So bring your

Foosball game.
It's perfect. I actually gotgame when it comes to foosball.
We could have some fun withthat. Yeah, absolutely, in fact,
I hit the ball so hard thatsometimes I break those little
guys. But the beauty of it isthat if you get a 3d printer, we
can just print

another one. So we can print them off.
We can print them up. Some goodhealth insurance. It'd be great.

Exactly. Sounds like fun. You know, you know,
you mentioned the importance of,you know, small to medium sized
businesses, industrialemployers, government, academia
coming together. Let's what'syour message for academia? So,
I'm an educator. What do we needto be doing to create this next
generation of engineers andtechnicians for the way that
manufacturing is going tochange?

Oh, so part of this is we have to think
about education differently,right? Yeah, that's one.

So as a former professor, I love it when I hear
you say that, or maybe you'restill teaching, or you did teach
then, then how do we need tochange it?

So I do a lot of mentoring, as you would
imagine. But the other thingthat I'm really proud of is that
I recently joined the board ofProject Lead the way. Okay? When
Project Lead the Way pullstogether STEM education,
curriculum and such hands onwhich I like, as I told you in
the beginning, that's what Ilike, right? This one theory and

(46:55):
practice. So this bringstogether the theory and
practice. They're in schooldistricts across the United
States. Another thing I thinkthat educators can do is get out
of the students way, right,because they are really
interested in things thatthey're interested in, and let's
let them be interested in them,and then show them the tools.

(47:17):
Here's a tool you can usewithout presupposing what
they're gonna do with the tools.
Here's some tools, and just haveat it, right and be amazed at
what they do. I think thingslike FIRST Robotics that's
growing. I think is fantastic. Iused to run an underwater
robotics competition when I wasa professor, actually, in

(47:37):
Baltimore City. So I would trainthe teachers in Baltimore City.
We held a very big regionalevent, and then the winners of
that were going to the nationalevent, and winners from
Baltimore City was invited tothe third science fair that
President Obama went on, and Iwas able to accompany them. How

(47:59):
cool is that? Yeah, man, it'sreally cool. So what I think for
educators is become familiarwith all the there's a lot of
tools that access out there. Andmaybe we change, I'm speaking
real time here. Maybe we changesort of science fairs, right?
Maybe science fairs go from, I'mgonna show my age here, from

(48:22):
baking soda and vinegar andvolcanoes in the solar system.
There was a student, high schoolstudent, who was designing a
apparatus for her sister's shoe,right? I think one leg. She had
a issue with her feet and allthat. So she was looking at, how
do I design an apparatus so thatshe can walk better? And that

(48:45):
was that part of the curriculum.
I talked to her about it. Shehad her little design, I said
little design, but she had herdesign all that, but that's
something that she canmanufacture, right? Three print
things like that. I think wewill be amazed at what the young
kids, the younger people can do

no question, yeah, you forgot about the salt,
though. I think that's what weuse to make the little volcano
that you put the vinegar and thebaking soda in to create that
eruption. I remember that.
Remember that very well. I didthat project myself. You know,
we have come a long way, andhave a ways to go, but to your
right, to the extent that we canhave a student go from problem
identification to ideation to,you know, coming up with some
solutions, to actuallymanifesting those solutions, in

(49:25):
this case, a real world example,like that girl whose sister had
the issue that she was trying tohelp her get over. That's a
that's a perfect, perfectexample. You mentioned, you
know, some great organizations,first, robotics being one of
many I've been involved in aproject called discover AI over
the course of the last year,which is kind of hitting the
same target that you're talkingabout, in terms of different
experiences for differentstudents. Get out of their way.

(49:48):
Let you know everybody's goingto learn at their own pace. We
need to guide the studentthrough their learning journey,
as opposed to just dictatingwhat that is. Everybody learns
differently, matching thedelivery to the learning style.
Really important, and thenletting students choose their
area of interest to learndifferent concepts. I think
that's the future of education.
You and I agree 100% on that, aswe're kind of wrapping up and

(50:10):
closing out on our time herewith Dr Charles Johnson Bay, I
wanted to pose two lastquestions to you, one of them
still related to education,Charles and that is, we all have
our own education journey,obviously, with a couple letters
like doctor in front of yourname, yours went pretty deep,
and you're a pretty smartindividual, no question about
it. But do you have a couplethoughts in addition to what

(50:30):
you've already shared with usabout education that might
surprise our audience a bit?

Thanks for the kudos and the very kind
words there so kids and people,they all learn, right? They all
learn. And I think that as aneducator, we need to give them
the space and opportunity tolearn and to fail, quote,
unquote, right, to try somethingand get it wrong, and then try

(50:58):
it again and maybe get thatwrong, and then try again, and
then maybe you get it right, andmaybe you talk to your friend.
Hey, I got this friend, Matt.
Let me give Matt a call and letme, let me bring Matt over to
the table and let me talk tohim. I think, from a very
togetherness standpoint, I thinkone of the things that part of
our challenges is to make surethat people know how to

(51:22):
communicate with each other,right over a problem, right?
Here's a problem. Let's talkabout how we are going to solve
this problem. What's your idea?
Because we have a lot of folkstoday, you know, just with the
phone, and they're looking atthe phone, or they're they're
not ready to go online to try tofind this answer. How about

(51:43):
let's just sort of think aboutit and talk about it and try
something. I think that'sanother part of education that
we can accentuate. Goingforward. We

learn as much from failing and trying again
and figuring out what works andwhat doesn't work, and over the
course of that process andreaching out to people, having a
lot of different individualsthat can influence our thinking
and show us a different way ofdoing things. That's the way so
many of us learn. That'scertainly the way that I
learned. I've learned a ton fromyou so far. Charles on the
TechEd podcast, we got time forjust one last question. It's one

(52:16):
we love to pose to every guestthat we have here on the
podcast. We're going to take youback a couple years, maybe a
little bit more, before BoozAllen, before Lockheed Martin,
before Motorola corporateresearch labs and so on, before
you were spending your time atMorgan State University, go back
to when you were 15 years old.
You're a sophomore in highschool. And if you could tell
that young man one thing, givehim one piece of advice, what
would you tell him?

So I was 15, I was at Poly probably
getting ready for our bigrivalry football game, and which
we won, by the way. Again, whatposition I played, defensive
end, okay, high school, nice andoutside linebacker at Hopkins.
So go hop that's theconnections. But actually, this
is getting to my answer is thatthe friendships and connections

(53:02):
that I made when I was 15 arestill friends and connections
that I have today, and it's somuch more valuable. So what I
would tell my 15 year old selfis to just maintain those
friendships, also being older,maybe sit a little bit with the

(53:23):
person who might be sitting bythemselves, right, just to have
a talk with them to see what'sgoing on, to be that ear. You
know, my mom would always say,you never know when someone just
needs somebody to talk to orshare with. I think I would tell
myself to share more of that. Ithink that I would also tell
myself that it's gonna be okay.
I think when I was 15, that I,you know, I had some

(53:44):
insecurities, all that, I thinkI would tell myself that it's
gonna be okay to just keepdriving. It's gonna be fine.

All really, really good advice I still have.
If I made a list of my 10 BestFriends, there's probably four
of them on the list, give ortake, that were buddies of mine
when we were kids, when we were,you know, in some cases, going
all the way back to early gradeschool. And you know those
friends, and they know you inways that nobody else does. And
so, yeah, maintaining thosefriendships, and it does take
work. You know, every once whilepeople will say how you still
friend? Well, you got to work atit. You know, you text them, you

(54:13):
call them, you get together. Youknow, you can go years, in some
cases without seeing someone inperson sometimes, but you just
maintain that connection. Andthen when you do get back
together, you pick up like itwas yesterday. It's just
absolutely, absolutelyfascinating how that worked.
Yeah, it works really well.
That's the family you pickright, right, exactly, right.
Yeah, you're stuck with your momand dad. You're stuck with that
sister that made you do mathproblems, or, in my case, the

(54:34):
brother that I had bossed aroundwhen we were kids. You know, the
second part of your answer aboutspending a little bit of time.
You know, certainly I would havedone things differently as a
brother when I was growing up.
You just maybe don't know anybetter, or what have you. And
you know, as a friend to yourfriends, and then maybe as a
friend of those people that youdon't necessarily know as well.
You never know when that kidsitting alone at lunch might

(54:55):
need an ear to listen to or tolisten to them, or, at a
minimum, they don't need onemore problem with some. My
picking on them. So you know, tosome Be careful about that side
of it. Then finally, that wholeidea of it's going to be okay.
And it's amazing how many peopletell me that that look, if I
could go back in time and justtell myself, I don't know how
this is all going to work out,but somehow it's going to work
out. And just take a little bitof that anxiety off of there.

(55:17):
Things have certainly worked outin your case, Charles, really,
really fun to have you here onthe TechEd podcast. You've got a
great background. You're doingsome amazing work at Irva, doing
some great volunteer work in theworld of STEM and technical
education. And really appreciateyou taking some time for us.

Thanks.
It's been my pleasure, Matt. I'dlove to come back talk about
some other stuff. So keep me onyour list. Yeah.

Well, you're not coming back. I'm coming to that
secret laboratory. So that's theway we're going to do it. But
until then, certainly thank DrCharles Johnson, Bey, the CO
principal investigator fromIrva, former senior vice
president of blues, AllenHamilton, now retired. Really,
really fascinating conversationabout the present and future of
manufacturing, whether it'smaterials, whether it's process,

(55:58):
whether it is supply chain,whether it is equipment, there's
going to be some great thingshappening in manufacturing. One
thing I can promise you is theTechEd podcast will be here to
keep you up to date the wholeway through. We will also be
here with the best show notes inthe business. You can find those
at TechEd podcast.com/johnsonBay. This episode, show notes
will be at TechEd podcast.com/jO, H, N, S, O, N, hyphen, B, E,

(56:24):
y, when you're done there, checkus out on social media. We are
all over Instagram. You willfind us on Facebook. You can
track us down on Tick, tock, ofcourse, on LinkedIn, wherever
you go for social you will findthe TechEd podcast, and you will
find me right back here in thestudio. One week from today,
can't wait to talk to you nextweek. Until then, I'm Matt
Kirkner, thanks for being withus.

Unknown (56:49):
You.

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