hello I'm Shawn Wasserman simulation at
Earth engineering comm welcome to the
webinar digital twin manufacturing
excellence through virtual factory
application on the line with me is dr.
Michael Greaves author and lecturer on
engineering manufacturing and PLM also
in line is Fred Thomas the worldwide
energy marketing director for Dell Mia
I'm so systems if you have any questions
for them please ask them in a chat and
we'll get to them during the Q&A Fred
Mike the floor is yours
that's great Thank You Sean today we're
talking with dr. Michael Greaves on his
recently published white paper titled
the digital twin manufacturing
excellence through virtual factory
replication dr. Greaves has written and
lectured extensively on product
lifecycle management as a frequent
keynote speaker at international
conferences
dr. Greaves works including the seminal
piece on PLM titled product lifecycle
management
driving the next generation of Lean
Thinking in his most recent book titled
virtually perfect driving innovative and
lean products through product lifecycle
management
dr. Greaves consults with a number of
leading international manufacturers and
government organizations including NASA
in dr. Greaves is the co-director of the
center for life cycle and innovation
management at the Florida Institute of
Technology where he's also a research
professor in the College of Business and
College of Engineering so welcome to our
broadcast let's get started dr. Greaves
I recently saw that you were appointed
head of the center for advanced
manufacturing and innovation at the
Florida Institute of Technology does
that does that tie in with what we're
going to talk about today yeah thanks
Fred so so as if I didn't need another
job but I am now the executive director
of our new center for advanced
manufacturing and innovative design at
Florida Tech and and our focus is to
talk about and do a couple things in
terms of advancing our students
education in applying their engineering
studies to to creating product and
actually manufacturing product and
supporting price
also doing research on you know how do
we how do we basically do 21st
manufacturing in order to bring
manufacturing back to the US so our
focus is is on this virtual to physical
manufacturing that we're talking about
here today and and so so this this does
feed quite well into what we're going to
be talking about in terms of factory
replication great so let's get into it
what exactly is the digital twin model
so so the digital twin model is
basically the idea that says in the past
if you wanted to have information about
a physical product be it an automobile
or an airplane or rocket ship or even or
even a mundane thing like a coffee cup
it had to be in possession of it in
order to have information about it you
basically had to so if I wanted to know
how many hours were on an airplane
engine I would basically have to go
track down that airplane wherever was in
the world and do a readout of what that
that information was what we've been
able to do since since the evolution of
computers and communications is
basically be able to strip that
information away from the the physical
product and create a virtual image of
that which we would call the digital
twin that basically allows us to to not
have to go track down that that airplane
but that airplane is communicating on a
constant or semi constant basis all the
information we need to know about it and
so so this has has allowed us to do the
creation of virtual products and and in
the past while we could get some
information we now can have sort of the
robust information that we couldn't in
the past so if you wanted the the
geometry of that product you were
relegated to two-dimensional blueprints
and now when the computer revolution
came about especially in terms of being
able to to to create digital images of
products we have
very very rich representations of that
product in fact one of the things that I
talked about in my early book was was
the ability to differentiate between the
virtual picture of the virtual product
and a picture of the physical product
and now we're reaching a point where you
really can't tell the difference so so
there's been this dramatic increase in
virtual product richness and vitality
and and it's not simply at the product
creation stage what the whole idea
behind the the digital twin is is to be
able to to not only link the physical
product with the virtual product but
keep them linked throughout their entire
life and so so what so that what that
allows us to do is to is to basically as
we manufacture a physical product we
capture exactly what that product looks
like exactly what parts and pieces went
into it and then what we want to do is
throughout the life of that product be
able to to ask the product changes to
reflect those changes in our virtual
twin and and that gives us the ability
to then use that virtual twin for all
kinds of different things that we would
have to track down the physical product
you know one of the things that has
helped this is the is is we're talking
about a lot of data and there's sort of
two things that are going on one is is
the creation of lightweight models so we
don't have to carry around as much
information as we have in the past but
even that's going to go away as we
basically increase our amount of
computing power bandwidth and storage
and so so while veil ability of
lightweight models have allowed us to to
move down this path we basically are
because we're riding down Moore's law
which is says that that the amount of
well technically the transistors on a
chip double every 18 months it means
that we're basically doubling our
computing power but not only computing
power but also communications and
storage and so that's helping us out
also the last thing is is that we're
getting a corresponding increase in
physical product digital factories for
data so in the past we
go out to the factory floor and you had
paper travelers and and there was really
no ability to understand you know other
than when the product finally came out
and being able to to do what was what's
called quality control on it to see how
it measured up we are now being able to
put sensors on all kinds of equipment if
not all the equipment on a factory floor
and start to then basically get the data
of what's actually happening on the
factory in real time and so the digital
twin evolution has basically allowed us
that capability okay let me just follow
up on that so if I understood you
correctly really a robust manufacturing
operation management solution like Dell
Mia's app reaso solution plays a
critical role in in bringing the digital
twin model to life yeah so if we you
know I'm always a big believer that that
we ought to to visualize what we're
talking about and so so this is the
example of the digital twin model those
of you familiar with my my book probably
saw a much reduced picture of it but
since this was done by NASA who has has
the ability to do some nice graphics
this came out of a paper that we did
with at NASA but basically the the main
characteristics that we have with a
digital twin model are sort of three
full we have physical space with
physical items and in this case I've got
a bunch of rocketship a jet engine or
akkad engine rocket with boosters and
and then the the top of the rocket and
and those physical things have always
existed and will continue to exist
because we live in a physical world I
talked to a little bit before about
virtual space and and if we sort of go
over and look at the virtual space it
has all the information about those
physical things from the left side and
so so the key there is we basically
build rich representations
if you stop and think about it the
virtual space comes first before the
physical space because we do design
plans about these things before we
all.we we build them but when we start
to talk about manufacturing we start to
build the physical elements on the
left-hand side and what we want to do is
to reflect on the right-hand side the
data that says exactly how those things
were came about so so while we may say
look at the specification of this part
is is X plus or minus y when we actually
make the thing we don't have X plus or
minus y we have a physical number of
what that specification is and so we
need to capture that information in the
manufacturing process so that we know
exactly what's been built so so I divide
the the digital twin into a couple
different categories one is the digital
twin prototype which is what we designed
the product to be in which we think all
the ideal products should should look
like but then when we actually start to
manufacture these products we get the
digital twin instance which is which is
basically matched up with each physical
product that we make and so so if you
see the the two things in the middle we
have data coming over from the
manufacturing side and then when we want
to have information about how that
product was made we basically have
information we use that information in
the physical world to make quality
decisions so so so the manufacturing
piece is about building these digital
twin instances and being able to
understand exactly what has happened out
of the manufacturing floor okay great
when I look at it though it's not so
much the digital twin provides an answer
but it gives you it gives you really
more in-depth information to make
choices and decisions would that be
right well that's like that's exactly
right and and the I think the problem is
is that we really don't have a great
feel for what information
has allowed us to do and so I sort of
created the this graphics that said but
information is a trade-off of time
energy and material and what I mean by
that is is if you look at the left side
you can take any task you know
manufacturing a rocket ship designing a
new airplane or the example I like to
use which everybody can understand is
putting together a new bike at Christmas
for the kids and so if I if I take any
particular task I could divide it into
two parts one is the minimum use of
resources that it would take to do that
task if I was a mission in manip it in
meaning I knew everything and I could do
everything very well and then everything
above that so that's the green area on
this chart and everything above that is
the red area is information in
efficiencies so I don't know you know
what exactly my rocket ship propulsion
is going to do so I don't know so so I
have to do a lot of trial and error to
figure out whether it's actually going
to lift the amount of weight that I want
to lift or I don't know how long my
wings and my airplane should be and what
my lift is going to be under those wings
so I basically do experimentations or I
don't know where the wings are going to
break so I have to basically do work
there so so so if I take any of these
tasks I can in our world cost them
because I can cost time energy and
material and so so that's sort of the
the you know the world that we live in
the what humans can do is they have this
thing called information that basically
is a replacement not for the amount of
physical activity I have to do to that
that would require me to do the task at
hand but it does trade-off for the
information and efficiencies and in this
particular graph I showed trading off
completely but the reality of it is is
that that never happens but it gives you
the idea that says if I can create
information I can know not to do this
particular design because it doesn't
work I can know where I'm running out of
inventory at a machine level B so
it doesn't sit there idle so so it
allows me to basically basically trade
off information for these information
and efficiencies the problem is it's
really tough to cost information but
what makes this all work is is the the
formula that basically is there for for
the math geeks it basically says if all
over all the different tasks the cost of
information is less than the cost of
wasting resources then I can trade off
information for that and in fact that's
what Fred your company a pre-show tries
to do with respect to collecting
information so I can make good decisions
and not do wasteful inefficient and even
stupid things out on the factory floor
so so I don't think we've really have a
good appreciation for for what
information can do for us but clearly we
see the benefits of it every day and so
I will contend that the reason we've
done so well in the last 25 to 50 years
is information technology has come along
to allow us to not waste resources the
way we have done in the past excellent
really really good insight you talked to
many many different manufacturers around
the world I know you're you know consult
with them on a regular basis so in your
opinion where are manufacturers today in
relationship to the potential of the
digital twin model to help them take
their their manufacturing really to take
their product processes to the next
level yes oh so you know if I'm
optimistic about kind of where we're
going but kind of the reality of it is
is that today a lot of the work that we
do is sequential and independent we
basically you know have very different
organizations that develop and even
engineer the product and then the
organization that is tasked with
manufacturing the product is a
completely different organization that
really doesn't share much information
with
I won't even talk in today's webinar
about the poor people in the support
sustainment phase who really get the
short end of the stick with respect to
to the people at the front end not
taking in consideration the support and
sustainment issues of products but but
even between engineering and
manufacturing there's this huge gap that
basically says that that we do we do
sequential work and independent work and
then we hope it comes together so so we
do develop you know a 3d model and an
engineering building material and we
think that that's you know how we are
going to to build our product but the
manufacturing people then have to
develop a bill a process which is the
recipe and some people you use different
terminology I call it a bill a process
but this is the recipe that says here
are the steps and the activities that
have to occur to take raw material
coming in the back door and producing a
finished product out to throughout the
out the front door and so so the bill of
a product is is the development process
but they even develop their own
manufacturing bill of materials and a
classical problem that that is still at
the forefront of a lot of organizations
is ebon damn bomb inconsistencies so so
what happens is that that the the
engineering people and even the
engineering manufacturing people take
their their designs and and in the past
they've been blueprints but even 3d
models and they throw it over the wall
to manufacturing and so so I always kind
of compare it to a relay race where
engineering is running down the track
and hands it off to manufacturing who's
supposed to then run to the finish line
but the reality of it is is that in most
organizations well it would look like is
engineering hand if the manufacturing
manufacturing running a little bit of
ways turning around running back to
engineering and having engineering back
track and so so you have this back and
forth thing that is hardly conducive to
a relay race
let alone to manufacturing and so they
throw they throw the these designs over
the wall to manufacturing only have
manufacturing not be able to to build it
or have problems I mean the other core
issue in fact the we wrestle in this one
at NASA is a lot of times manufacturing
might have a better way of doing things
that would change the design make the
design even better so for example we
have to use a more expensive material
when manufacturing you can say look at
if I put in a couple of these of these
stress areas I could basically use a
lighter weight material so so we really
haven't done a very good job overall in
terms of connecting the two and then
often we developed two of the blueprints
for manufacturing floor when we've been
working with 3d models now some of the
more progressive organizations you know
are now putting 3d models on the factory
floor but there's still a fair amount of
2d blueprints and one of the problems
with today's generation is there's very
few people who have the ability to take
a 2d blueprint and visualize a 3d model
that is a rare kind of capability in
today's world and some of the old line
manufacturers could do it but we're
running into problems with the newer
generation not having that capability so
this is really about closing the loop if
you will and creating that continuous
loop of improvement between the
engineering community and the
manufacturing community and this becomes
an advancement if you will in making
that happen
yeah well and and and so so the bigger
the issue that we're talking about here
today is the fact that that we have
spent a lot of money in doing modeling
and simulation for factory operations
only discard those once it goes out on
the factory floor and we find out that
that the the build process is is very
different than what it was was proposed
to be and so so what we're talking about
here is is basically being able to reuse
these these factory simulations that are
really
quite good in fact the there are a
number instances that I'm aware of where
you can save tremendous money in being
able to to simulate what happens on the
factory floor before you actually build
the factory at NASA we saved millions of
dollars in and because we build our own
own machinery and we found out that we
had a we had a piece of machinery that
wouldn't reach into where we needed to
reach and stir welding and in the past
that would have cost us millions of
dollars in six to nine months in
retrofit and we found that out by doing
simulation but now that we've had that
built that the whole idea is to say well
let's use that simulation to talk about
what's actually happening on the factory
floor but in order to do that if you
remember back to my to my model I'll see
if I can do this is that we really need
to basically connect the physical model
with the virtual model and so what's
missing and able to be able to do that
is we need a unified repository that
basically allows us to have both the
physical and the virtual connected and
then what we need to do is have 3d
location and characteristic tags that
are on the factory floor that's
basically looking at actually what is
happening on the factory and being able
to feed that into our simulation so that
we're not simulating anymore we're
basically reflecting what's occurring on
the factory floor and so so we're
basically looking at at manufacturing
execution system tags that would
basically allow us to to know what the
place maker of what it is that were we
have designed in so we're collecting the
right information to match up against
the replication so this leads to the
concept that we're talking about today
which is digital factory replication so
so all we're talking about here although
it's not is non-trivial from a from
actually doing this is the ability to
take the simulations that we spend a lot
of money on and then keep running them
as we're running the factory and see
exactly what's happening on the factory
floor versus what we have what
we have predicted to happen and the
whole idea of that is being able to then
be able to see no matter where we are
because of this this idea of
virtualization we would have access into
what's happening on the factory without
having to be on the factory floor at all
so I think that that what what this does
is take the digital twin to the next
level that allows us to basically be
able to to match up what we thought was
going to happen with our products and
well how we were going to build them
with what's actually happening with our
products and how we're actually building
them you know they can see this
impacting a whole host of metrics that
most manufacturers you know value today
from from quality to time to volume to
time to global volume it just
accelerates the entire process in that
relationship and it has the potential to
impact continuous improvement programs
on an ongoing basis sure so so if you
sort of look at the example that we have
out here we're looking at a screenshot
from from a factory from a factory
simulation and what we're saying is is
so you see that if you've ever seen the
factory simulation they're pretty pretty
cool because you can see the actual
units moving on and you can zero in and
into the actual cells and in this
particular case not only are we actually
seeing the simulation but in factory
replication if you look at sort of the
balloons that we have superimposed on
this and this is just for illustrative
purposes we're basically showing the
what was supposed to occur and then
matching that with what is actually
occurring and and that allows people to
zero in on the problem areas and so so
we can see that that if everything was
Green you know we are at a particular
station you know measuring what we're we
willfully produced and comparing that to
what we thought we were going to produce
and if it's all green it means that
we're doing a good job so so by by
basically using the the money that we
spent in
simulating it we're taking it to the
logical next step which is saying
repurposing it to basically being able
to to then track it as production occurs
to see how it's a to see exactly how
we're making this and in point of fact
you know the only way to do this sort of
today is to look at a sheaf of reports
and then compare it to what we thought
was supposed to be manufactured and make
our decision this gives us a nice visual
representation of how it is that we
should how it is that our factory is
operating and allows us to zero in
pretty quickly without either looking a
report or walking the factory floor so
let's drill into this a little more and
get into a little bit more detail on
this I think we have the time to do that
let's go back to the model real quick it
is the concept and your mind limited to
certain manufacturing models say just
lower volume maybe high mix type you
know construction equipment agricultural
equipment or can it work also in in
high-volume environments maybe even
repetitive environments why I from my
perspective I think it would work in in
both environments because I mean that
the whole idea is is in fact where it
would be most useful is in high-volume
where you can't afford to have products
not being produced to how they're
supposed to being produced and you're
basically having complex situations like
this auto plant where you know a problem
you know somewhere in the mix here will
basically cascade into bigger problems
down the line so so obviously the the
the higher volume opportunities are
there for complex products now if I'm
producing paper clips on or like air but
if I'm producing automobiles or or any
or electronics or things like that where
I'm looking at high volume then knowing
how the factory is operating can can
give me early warnings where I'm
basically looking that but but in slower
volumes even
you know airplanes or or a little higher
value than that being construction
equipment being able to see all these
stations on the factory floor if I've
gone to the expense of creating a
simulation of it I really don't want to
put that into a drawer and and basically
you know just simply then relying on the
factory if I could repurpose that so
that any executive my organization could
see what's happening out in the factory
floor at any point in time and by the
way I would collect this information so
that I could do not only statistically
process control but but also look for
trend lines and look for for where I was
starting to drift off of my tolerance
quarters to be able to make you know
good decisions about what's occurring on
the factory and so there was a reason
you know that that in in factories you
put the plant manager's office
overlooking the factory floor with a
window this is that window except for
the fact that that for the most part the
factory manager could only look at big
problems ie when they when the assembly
line stopped but this will this allows
that factory manager or even other
members of his team to look at the
factory at any point in time from home
wherever and know exactly what's
occurring on in the factory that they
were local to or even halfway across the
world it's almost like that virtual
overhead office in the center of the
factory exactly and and that that
basically again if you go back to my
premise that information is a trade off
for waste of resources that having this
information will allow us to to have a
better handle on where we were starting
to to have inefficiencies occur in our
manufacturing process I mean I go back
again when we spent a lot of money on
doing these these digital simulations or
I could repurpose that and and just
continue running it as a factory
replication of what's occurring if I can
get the information off the factory
floor which is why
I propose this unified repository okay
let me let me ask another further
questions especially with this example
sitting there you know and obviously
I'll I have a vested interest in this
particular area but it just seems to me
that it becomes highly important for
manufacturers to really think about
their manufacturing shop floor and
regardless of their history you know and
how many spreadsheet spreadsheets they
may have used to run the factory floor
or how many different disparate systems
they have it's it's never too late to
start putting your strategy together to
put a robust platform on the floor that
for manufacturing that is truly
collecting the important information
that you would need to fuel a concept
like digital twin you're right and and
so there's a lot of initiatives that are
going on in the not only in the US but
across the world in terms of making all
these machines be smart and being able
to communicate so you know industry 4.0
or or the smart machine concepts I mean
all these concepts are about about
instrumenting what's occurring on the
factory floor to allow you to collect
information about how manufacturing
occurs now some what we're talking about
is is is basically having machines
communicate with each other to adjust
for four different aspects of one
machine doing something versus another
but collecting that information into a
virtual twin of the factory even is as
an opportunity to to basically be able
to to get in front of what's occurring
in the smart machine area and merge that
with what has occurred which I would
consider to be pretty robust in the
factory simulation so what we're really
just taking it to the next logical step
here which says you know you know we
sort of need you know three different
things that we're talking about here we
need we need the the simulation itself
we need
the machines to have instrumentation
which we're starting to see more and
more of and then we need to be able to
collect that data into a manufacturing
execution system so that we can merge
that information with what what we
basically had had designed had what our
thought our designs were and being able
to do then that visualization in
comparison yeah and that in the
real-time nature of this really negates
you know continued use of your old
legacy solutions and spreadsheets and
you know as a further reason than
investment in something like you know
tell me as a pre zone solution becomes
critically important because real-time
is the necessary time to support this
concept yeah I mean I mean quite frankly
you still can collect the data and do
analysis after the fact in spreadsheets
or big data or whatever but but you know
if if you're sort of looking at
spreadsheets by a very definition you've
already had the problem and and so so
this idea of having a visualization
real-time is I think extremely important
I mean I I basically have have said in
fact in my first book that you know our
highest bandwidth is is our vision and
so all this does is is make sort of the
data visible to us in such a manner that
we can start to make decisions much more
quickly and in fact with with better
data than we have had in the past great
let's move on this was an area that was
in your white paper that I just found
fascinating but it's the use cases and
how you have laid out the use cases that
support this could you could you go into
that a little bit sure so I wanted up
with sort of the three C's the
conceptualization comparison and
collaboration and what I mean by
conceptualization is is you mentioned
you know spreadsheets and reams of data
you know as humans we're really not
really good about being able to to
assess look at a spreadsheet and look at
the pool of data in there and make good
decisions about that I mean we're just
not set up to do that computers do a
much better job of being able to do that
analysis so so this idea of
conceptualizing you know giving us a
picture of what's occurring in terms
that we you know understand
distinctively being able to view it so
if you go back and look at you know the
blooms off the particular stations that
immediately tells us which station it is
what we were desiring what we got and
you know and we can look at the trend
lines along that line to determine hey
am I looking at red from one point on or
did it just start at one station or do I
start to see drift I mean it allows us
to make very good very quick decisions
by being able to conceptualize what
we're talking about here the comparison
piece is something that we do as humans
is that is is the idea of you know what
do we want and and and where are we
actually that today and so so this idea
of human nature is to basically close
the gap between the ID bill and the
actual and we basically you know are
able to do that effectively if we can
understand two things you know what is
it we really want to do and where are we
really at problems that always occur in
that area is we don't understand what
the current situation is so we make
faulty decisions but we don't really
understand what what it is we're trying
to accomplish or gain or what our what
our outcome is and so we basically
aren't closing a gap between anything
that's really important and so so
comparison is is what humans do
instinctively whether you're driving a
car and you're comparing the person
turning in the lane in front of you
versus where you're at or you're
basically looking at factory floor to
basically say here's what my here's what
my manufacturing goals are and here's
where we're at the third aspect is is
what humans do
very well and that's collaboration so
instead of having to send one person out
on the factory floor who reports back
what's going on we're talking about
factory replication is being able to see
what's occurring you know by many people
and then being able to bring to bear the
the collective knowledge to solve
problems so so if there was a problem in
the factory floor rather than having to
put people in airplanes and ship them to
that factory those those people who we
would rely on to come up with with help
on this can simply look at their
replication and understand what's
occurring on the factory floor
immediately without having to travel or
spend the time and effort so this goes
back to the to the the premise that
information is a replacement for wasted
resources because basically having
people travel for you know a day or two
days with the expense of that in order
to be able to see something that they
should be able to see from from
information that be available to them is
clearly a waste of resources so so so
these are the sort of the three use
cases that that I come up with is it's
the idea of conceptualization being able
to visually see the information as
opposed to having to tease it out of
reams and reams of reports you know
comparison comparing you know what what
I'm trying to obtain versus where I'm
actually at and closing that gap and
then finally being able to bring to bear
the the resources of the individuals who
can collaborate on creating a solution
quickly and efficiently without having
to expend the necessary resources okay
we're we're moving toward the end of the
the formal presentation because we want
to leave enough time for for questions
in summary realization then of the
digital twin concept in a real world
environment it's not only feasible but
from what I gathered from the
presentation it's really a game changer
especially when you think about you know
all of the dramatic changes in this in
things rush that is going on today yeah
so so you know the good news about where
we are in our industry is if you don't
think we have enough capability wait
wait 18 months and it's going to double
so so there are dramatic advances you
know in virtual product representation
and the physical product digital data I
mean if you looked even back to the
beginning of this millennia that that we
have made huge strides in virtual
product representation you know they
even simply looking at the
three-dimensional representations one of
the things that I have had proposed in
in my first book was this Turing test
idea that says you know can we
distinguish between a virtual product
and the physical product on a realm of
ways and one of them is visual and and
and today I've seen you know image of a
physical product and the virtual
representation and you really can't tell
the difference so so there's been
dramatic advances in in the technology
that we rely on what's missing is the
connection between the virtual product
and the physical product and so so if
you go back to my to my model the the
connection what we've done we obviously
have have pretty robust physical
products because we've bloomed in the
moon and back and we are now getting to
have very robust virtual products the
connection between these two has been
the thing that has not been robust
enough and so so if we're talking about
a factory replication we got to be able
to get the data off the factory floor to
compare it with what actually was the
design so so that's the area that that
we need to kind of keep focusing more
and more on and this connection dries
instantaneous and simultaneous for
sections of manufacturing so so if I can
see what's happening on the floor in
real time without having to be actually
there and I will argue that even if
you physically are on the factory floor
if it's a big factory things are
occurring you know and in parts of the
factory that you don't have any access
to because you're just not physically
there but basically this this produces a
virtual set of eyes for us that allows
us to to see you know and drill down to
any part of the factory itself as to
what's happening and it can happen
simultaneously with people not located
co-located with the factory but anywhere
in the world and I would argue that this
connection would improve productivity so
so we would not waste as many resources
we'd trade this information off for
wasted resources uniformed and eighty of
production because what we would do is
capture problems a lot earlier and and
not have variations in our tolerance
quarters that sometimes we have today
and obviously that improves quality now
now my definition quality is a little
bit different than in sort of classical
manufacturing my definition of quality
is you know will it do the things that
the user wants it to do when he uses it
but but from a classical quality control
specification management I think that it
allows us to have less variation in the
product if we have better information
it's coming off of the factory floor
that we're comparing to what it is that
we're trying to improve absolutely
fantastic I think it I think the
presentation Mike really struck a chord
with me how close we are to really
taking the shop floor to the next level
I think you wanted to say one more thing
with regard to Florida Tech yeah so so
one of the things that that I think is a
particular problem is this idea that
that understanding the connection
between you know engineering
manufacturing sustainment support and so
in order to address that we have created
a certificate program at Florida Tech in
in product lifecycle management which
covers these areas that we've talked
about today and so so
anybody who's interested in so so my
belief is is that if if people have a
better understanding of all the elements
we're going to do less of siloing and
inefficiency between functional areas
and better job in terms of sharing
information across the lifecycle and so
the Florida Tech certificate program is
24 modules of all this information about
PLM and how it impacts and what the
value is for today's organizations great
dr. Greaves thank you and with that I'll
turn it back over to Sean for for some
questions thanks and great presentation
you guys actually the next person asking
question here agrees was really
impressed the presentation they say are
you saying that in the near future the
tracking and genealogy of products will
be shown within the 3d model data like
as designed as built as maintained which
will be unique to the model will that
all be accessible through things like
simulation digital mock-ups and the
design phases and if we're not there yet
how far are we from this so I'm always
reluctant to to predict how quickly we
do things because it seems like this
technology has moved a lot faster than
even I predicted was going to do but yes
I think that I think the the ideal as my
NASA colleague John Becker said is the
ideal is what we would like to do is to
design the product virtually manufacture
the product virtually sustainless
support the product virtually and only
when we get it all right do we basically
go physically move around some atoms so
so we want to trade off we want to trade
off bits for atoms you know wherever we
can especially being able to get this
now that's the ideal and the ultimate
vision but I but we are
you know we are seeing a whole bunch of
activity occurring in terms of in terms
of of reaching that particular aspect of
of 3d miles so 3d miles started office
simply geometry we're now adding a lot
of additional information and we're
using it for behavior analysis finite
element analysis stress analysis things
like that and so so yes I think that at
some point in time you'll be able to
inspect the virtual product and and
you'll be able to obtain all the
characteristics that you would be able
to obtain from the from having
possession of the physical product I'm
not a predict the time frame I like how
you said that treating Adams forbids I
like that
so it's rating parabola yeah bitch Brown
yeah sorry
is there any commercial tool that
currently supports the concept of
digital twins well that yeah that the it
depends on kind of what part of the
digital twin that you're looking at so
certainly today you know what I call a
digital twin prototype which is the the
development model you know that's
supported in in CAD being able to do the
analysis is supported by a lot of
solvers what would it so so the
realization of a physical product from a
virtual product exists we really haven't
done as much as we need to do in terms
of taking a manufactured product and
creating a virtual twin of that although
we do collect some information I guess I
had a sort of sort of caution that that
we may not need all the information
about the physical product in the
virtual products going to depend on on
what our use cases is so so for example
I'll use a trivial one if we don't
really care what color the product is
we wouldn't have that you you wouldn't
have that in the virtual twin model so
so there is a cost to having information
I mean it's not free there always is the
cost of developing the information so
you got to figure out it is do you have
value to it the the premise that I'm
talking about here in terms of faculty
replication I haven't seen a
representation of that but I think other
people are working on being able to make
that happen we have parts and pieces we
have very nice factory simulations and
we do have have information being
collected off the factory floor it's
going to take my unified repository to
basically be able to make a factory
replication of reality okay perfect
how can you improve in the world so one
of the things that can occur here is is
while I showed kind of one Factory in my
slide you if you had multiple factories
that were this way you could not only
see what's happening within one Factory
you could basically compare factories
across the globe with each other to see
where one factory had inefficiencies
that another factory didn't have and
then drill down to find out why that was
occurring and so so this idea of
continuous improvements so what happens
a lot of times with continuous
improvement today you know Kaizen as as
as it's been stylized is I really have
to move actual physical things around on
the factory floor in order to be able to
to compare these improvements if I could
simulate those improvements and then you
know send them off to the after I have
validated that they would give me
improvements I could ship those off to
the to all the factories and then
tracking them make sure that they
implemented in the proper fashion so so
I show sort of one factory you know in
terms of collecting that that
to data and being able to show the
replication there is no reason why you
couldn't have multiple factories that
you were looking at all at once and then
collecting that information off of each
of the factories in comparing each
factory against each other in order to
understand where improvements in one
track for you visa vie another factory
were available the one thing I even
haven't talked about is is you know
being able to feed that information back
into the engineering design phase so
that if there were you know in
efficiencies in the manufacturing
process as design when the product was
designed to be built you would feed that
back so that the next version of the
product corrected that too often you see
that the same problems are solved over
and over again you know as each
generation the product is rolled out and
so so and that's the reason is is that
the designers really have very little if
any connection to the factory floor so
don't understand
you know what problems have occurred and
why manufacturing process should be
should be changed and the next version
of product comes along with the same
design-build process from the
engineering from the manufacturing
engineers and as a result you you wind
up solving the same problem over and
over again so so there's a number of
reasons you know why this would it would
help this would help in terms of doing a
better job in reducing efficiencies
improving productivity and the factory
floor perfect
now what role can connective
technologies like say the cloud or re ot
play with the digital twin yeah so so
I'll nor the cloud for a second but but
IOT the Internet of Things and in fact
Florida Tech is is doing a lot of work
and we're gonna train our own engineers
but but are creating curriculum for this
particular area because a it is I think
a seminal technology is
is basically this idea of having
everything be smart and so I can't
collect data I mean I can't I guess I
can collect it manually but the best way
to collect information is for the
machines themselves to report as to what
exactly is happening and so so the
Internet of Things is going to in
essence make the new machines smart
communicate able and in point of fact
there are a number of projects out there
to even retrofit older machines to
collect information to feed in so so so
I mean the IOT is kind of a I want to
call it a fuzzy concept but it's a
pretty encompassing concept one of the
elements of IOT is basically having
having physical products have
intelligence in order to to do two
things sense and communicate so they
need the sense what's happening and they
need to be able to communicate that IOT
is is sometimes extended into machines
talking to each other and but even then
if let's just say I have machines that
are changing their program or changing
their parameters in order to compensate
for other things are happening in the
factory I really need to understand what
they're what they're changing so part of
IOT is smart machines talking to each
other and so if I make a part that has
you know has a negative tolerance the
next time I put it in the machine
I want that machine to recognize it was
a negative tolerance and try to make a
positive tolerance even if that's
occurring on the factory floor I really
want to know that that happened as
opposed to being surprised at the end of
the process so so having intelligence
and machines I think is a good thing but
unless you have a digital twin that
allows humans to know exactly what's
happening I I would sort of contend that
that those kind of systems can go out of
control pretty quickly and can cascade
failures so so digital twinning is
important even if I have said okay well
I've got my smart machines talking to
each other you know why don't we new
humans well
while I won't contend that it's the
Terminator movies I think you can get
some really bad outcomes if you're not
in control of that from a human
perspective and and our virtual factory
replication allows us to do that okay
next question is what that is is a
digital twin bring to see a simulation
well the it's basically you have to have
it because of the fact that if you're if
you're simulating what are you
simulating and so so the idea is is that
you have physical design that you either
have you know it's been manufactured or
in the case of the digital twin
prototype is something that you want to
make so so so so if I'm going to do
simulation what I got to do is get the
physics right of what happens in the
real world in order to be able to
simulate the the even the geometry or
the behavior of my physical products so
for example you know I want to be able
to so I'll give you the trivial example
you know if I lengthen an iron beam you
know I could have a simulation that just
simply allowed me to place that let's
just say that I'm building a building
and I need a beam that runs a little
farther and so I I add length onto that
beam well if the simulation doesn't add
weight at the same time I wind up with a
building that that really doesn't work
because that beam will not hold the
weight is supposed to hold so so you've
got to get the physics right and that's
one of the challenges that we have
facing us is in simulation being able to
simulate you know being able to
replicate what occurs in the real world
in the in the virtual world
now the gamers have are easy because
they can make up their own rules about
what the physics of the universe are and
that's particularly fine so people can
fly you know you can have gossamer
structures to support a lot of weight
you know that's that's the easy stuff
the hard part is be
we'll have a simulation that reflects
what actually occurs in the real world
and so so that's where the simulation
people are really earning their money is
being able to build in the physical
models that reflect it so if I said you
know I want to design the product
virtually and test the product virtually
the idea behind that test is that if I
take that product and test it physically
it will give me the same results so so
so the digital twin is basically built
into the concept of of modeling and
simulation so have virtual twin
digitization change technical
requirements or docto job descriptions
for traditional end-user hasn't altered
the hierarchy of engineering and
management for instance if you're a
classical mechanical engineer do you
need any new skills that's a great
question and and obviously at Florida
Tech it's it's one that's first and
foremost on our mind and my contention
is you do I mean I think that the days
of knowing a lot about a little hour are
not gone away they're going away quickly
and so so mechanical engineers you know
are going to to need to know more about
about what they're designing into in the
context of design than you've had in the
past and they're going to have to be
able to do modeling and simulation you
know in the past the mechanical engineer
would design let's say a structure and
then you know give it to the analysis
people who would days later come back
and say I ain't gonna work for you today
there's no reason why mechanical
engineers can't do a lot of their own
their own engineering analysis as part
of the as part of the systems that they
have so so it is going to sort of
broaden now well you know people
engineers are never going to go down on
the manufacturing floor and manufacture
products nor vice versa but having an
understanding of what those elements are
being able to in essence
you know look at the product lifecycle I
think it's critical in order to be able
to take cost out of it and so if we do
sort of classical manufacturing where
engineering designs the product and then
sense of manufacturing who can't
manufacture and sends it back to
engineering and we have all that waste
resources we're never going to be able
to take cost out of the manufacturing
process or do it do it as efficiently as
we can so so it does have implications
for the for the for the student
graduating who's going to have to have
those capabilities and hopefully as an
educational institution we're going to
do a good job the the second question
error is an interesting one is is yeah
it should make so I'm a big believer in
basically pushing the decision down to
the people most capable of making that
decision as opposed to hierarchical
decisions and I think that that having
the the information and data available
so that you can turn the most
knowledgeable person and say is that
thing going to do what it needs to do as
opposed to somebody from the top saying
there's how we designing the product is
going to be key so so I think it does
change by by having people at lower
levels having better information at
their fingertips about what actually is
occurring either in the designer
manufacturing is is it should should
change our structures in our
organizations I mean we'll still have
some level hierarchy but as I said the
most knowledgeable ought to be making
decisions about how design and
manufacturing occurs thank you so I
think that's all the time we have today
so again I'd like to thank dr. Reeves
and friends and Fred for this
presentation you guys did a really great
job and I also want to thank everyone
who is here on the line with us for
listening in to the presentation I hope
you all enjoyed it as much as I did
so that's agrees Fred thank you very
much thank you have a good one