- Hi everyone, I'm Brian O'Flaherty Wills.
I'm the worldwide go-to-market lead for AWS IoT TwinMaker.
I'm really pleased to speak to you today
about a collaboration with AWS
and Siemens Digital Industries on Digital Twin.
And today I'm gonna talk to you about this collaboration,
show you an example of how this collaboration
is resulting for innovation for customers.
So first, a few words about this collaboration.
Siemens Digital Industries is a company
that needs no introduction
for anyone working in the industrial setting,
but this collaboration is something relatively new
that we announced last year.
Siemens, of course, provide software
to create comprehensive Digital Twins
across the value chain, including the design,
manufacturing and service parts
of the product and manufacturing life cycle.
And through collaboration with AWS,
we're actually bringing Siemens' Digital Twin technology
into the cloud, leveraging the deep industry expertise
of Siemens with the scale and global reach of AWS,
combining different services
and bringing those to customers.
Our recent new service, AWS IoT TwinMaker,
which we launched at re:Invent last year
is at the cornerstone of this collaboration.
What customer challenges are we actually looking to solve?
Well, Siemens and AWS are working on behalf
of our joint customers to bring together
the different pieces of our technology.
When we're looking at customers in the manufacturing sector,
we're looking at a lot
of common challenges across this space.
Our customers are talking to us a lot
about improving efficiency, improving uptime
and OEE and operational metrics,
as well as really driving insights
for stakeholders in engineering,
stakeholders in the plant floor,
and basically bringing the data
that's coming into the AWS and out of their operation,
bringing that into a place
where stakeholders can actually use it and take actions
and make decisions against it.
So you're seeing a couple of example use cases here.
Increasing product complexity across the life cycle,
optimizing material costs
and getting the most out of material inputs
without giving up quality,
increasing productivity, increasing flexibility,
reducing downtime and cycle time.
And of course, everyone needs to be thinking
about addressing sustainability
and getting the most out of their energy inputs.
So these are some of the customer challenges
that, again Siemens and AWS joint customers
are talking to us about.
And where does Digital Twin fit into all this?
Well, Digital Twin is really an example
of bringing all of these different data sources
through manufacturing and operations,
and bringing those to light for customers, for end users,
in the shop floor, in the control room,
in the operation room, in the management room.
Our example here is of a cold brew coffee plant.
So we're actually gonna show you today
an example of a Digital Twin,
a comprehensive Digital Twin,
put together jointly by Siemens and AWS
that demonstrates the full value of the Siemens portfolio,
in combination with the AWS Cloud Services.
So we're gonna walk through
this cold brew coffee plant Digital Twin demo.
What's really interesting about this demo is
that it really takes a full picture of the life cycle
of the equipment in the plant, going from a plant-level view
to the very specifics of an individual piece of equipment.
So I'm going to not spend too much time on this slide.
I want to get to this actual demo
and walk you through it.
Before we get there, though,
let's talk a little bit about the how,
and we talked about that view
of going from the plant level
all the way to the individual piece of equipment.
So really what our customers are trying to do is
take data sources from across industrial operations,
bring those data sources together in a model
of their plant and their operation,
and then serve that together with a 3D view
to bring that data in context
and serve it up to end users at scale.
So you've really got the data sources.
You've got the model,
and you've got that front end view
to serve up to users at scale.
So if you look at the demo architecture here,
we're really speaking to those three pieces
with different elements of the Siemens and AWS portfolio.
So if I start on the right-hand side,
what we're gonna be showing you is
a front end developed on Siemens Mendix.
Mendix is the leading low code platform
for industrial solutions.
So Mendix is a fantastic solution for taking data sources
and helping customers, real users,
to visualize those data sources and bring them together
and take actual insights against them.
In terms of the Digital Twin model itself,
this is really being driven off AWS IoT TwinMaker,
and AWS I TwinMaker, as I said,
is a service that we launched at re:Invent in 2021
that helps customers build and manage Digital Twins.
What we're gonna see from AWS IoT TwinMaker
is the bringing together of those different data sources
into a common model that represents the entire plant.
And then what are those data sources?
So those data sources are going to be live data sources.
Those are data sources coming from SCADA equipment,
coming from cameras,
coming from condition monitoring sensors.
Those data sources are gonna be transactional data sources
that govern the operations of the plant,
so things like the manufacturing execution system,
the MRP system.
A lot of these, by the way,
coming from Siemens technologies,
like Siemens Teamcenter, Siemens Opcenter,
and then the other data source
that we're gonna be looking at is
simulated data sources or synthetic data sources.
Here Siemens has an amazing portfolio
in terms of being able to predict
and plot sensor values that we can't actually measure,
so using simulation technologies
we're going to show that as well.
So we have transactional data sources.
We have live data sources.
We have simulated data sources,
all coming together in this Digital Twin.
So let's take a look.
So we're in the cold brew coffee plant.
Before we get there, this is an asset-level view,
so looking at the entire scope of operations,
including this one particular plant,
but you can see, this is really an at-a-glance view
of the entire operation showing major KPIs.
So in this case, we wanna take a look at a specific issue
or a specific anomaly within the plant.
And here, what we're gonna do is dive into this visual view
of the entire plant floor layout that's augmented
with these UI widgets
that represent individual assets in the plant,
and the data sources associated with those assets.
So in this case, what we're doing is
zooming right into this part of the conveyor.
We're looking at this robotic arm
where we've detected an anomaly,
we've detected a strain threshold exceeded.
So you'll see on the right-hand side at the top,
we've got some measured values.
We've also got a simulated value,
and that's gonna be one of those unmeasured values
that we're producing using the Siemens xDT solution.
And also, of course, we have the view,
the live view of the camera there.
So all of those different data sources
plotted against each other.
So that's nice, now that we know there's an anomaly,
but really our next question
is going to be well, what's going on?
What is really the issue at hand here?
And so we wanna be able to navigate
to where we can click and double-click down
on those details of that robotic arm,
and here's where you're seeing that.
And here's the real power
of linking this operational Digital Twin
into operational insights from MindSphere,
or in this case, right into the PLM system itself.
So we're gonna be looking
at a bunch of time series data here
that we're gonna be able to plot and window against,
relative to that robotic arm.
And here we go, we're gonna open an up Teamcenter
where we're actually gonna see the PLM system
of that robotic arm, and be able to go down
to really detailed levels, in terms of the 3D geometry,
in terms of the component parts,
in terms of understanding where is this robotic arm used?
Why are we seeing this anomaly?
Where else are we seeing these kinds of anomalies,
these kinds of issues, and being able to dive in
and root cause on this issue.
So some real power going from the end-to-end view here.
The next step is,
so I've seen these anomalies here.
I've seen some ideas
on how I wanna take a corrective action.
What I wanna do is simulate the output of that.
And so here, I've just gone into the Mendix view again,
and run a simulation against those new values.
So again, incredible power here,
going from the asset level view, the plant level view,
going to a specific location
and looking at a specific issue within the plant,
going right into the the details of the data
that we're getting from this robotic arm,
all of this housed in Siemens MindSphere IoT platform,
and then going even further
into the actual lifecycle management software,
and into the simulation software that's associated with it,
all through a single user experience.
So really powerful capabilities being shown here.
So that's actually not all.
In addition to the cold brew coffee demo,
and those capabilities we talked about,
I want to highlight some additional Digital Twin use cases
that Siemens and AWS can bring to life for customers.
When we think about Digital Twin
in the design part of the life cycle,
so when you're designing, laying out,
simulating a plant operation,
Siemens has some amazing technology
that we can bring to customers.
So in this case, we're looking at a simulation
and optimization of an entire plant layout.
We're looking at validating,
optimizing some filling equipment
and looking at the fluid flow through that equipment.
We're looking at optimizing packaging processes
and simulating robot-human interactions.
All of these capabilities are gonna come in
in the front end of the design cycle for operations.
So again, we're looking at everything
from design, commissioning,
building, operating, and maintaining
an end-to-end plant, in this case.
So some really exciting technologies
and some really exciting solutions
that we can bring to life for customers.
So to sum up, Siemens Xcelerator portfolio
and AWS services, including AWS IoT TwinMaker,
we're innovating on behalf of our customers
to bring these technologies to life
and to drive these technologies at scale.
Developers can create Digital Twins
from the very simplest use cases for a single machine
to the most complex end-to-end solutions
for full plants combining these technologies.
And we're really excited to bring this to you,
and to share more with you.
If you have questions or ideas
and you wanna discuss with us,
please go to one of these two links,
Siemens digital transformation,
or aws.amazon.com/iot-twinmaker.
Thank you very much for listening.