Hi there and welcome to What I Wish I Knew, a
series where we uncover IoT implementation
lessons, advice and the occasional regret
from the innovators leading the way.
I'm Jennie Caddie.
And today I talked with Finn Mainstone of
Siemens Gamesa, an innovator using Iot
solutions to build more agile factories,
increasing speed, quality and efficiency.
Fent talks with us about how IoT has impacted
their business, the role of managing
expectations along the way, and the critical
importance of really understanding the
problem to solve so that you start right,
which is half the work.
My name is Finn Mainstone.
I'm the senior product manager at Siemens
Gamesa and I'm working on the Optical Blade,
which is a digitization project that we're
working with different departments around the
company, but mainly run out of the digital
venture lab, which is a newly set up part of
Siemens Gamesa.
Digitization I mean, obviously, that's a sort of global
thing at the moment and has been in progress
for a long time, so to speak.
But in Siemens Gamesa, this is like quite a
hot topic.
And this particular product, I guess, you
know, blades somewhat the core of our
business. We manufacture our blades, you
know, we build them from scratch with raw
materials. So in that sense, anything that we
can do to improve our blade manufacture
really has an impact to our business.
And then you could maybe even zoom out a
little further and say, if we have, you know,
success in our business, then that makes wind
power generally better.
If wind power is better and we're able to
produce turbines at a cheaper cost, then that
brings down the level and cost of energy,
which, you know, has a knock on effect.
Basically broken down into three key
categories, these are the problems that we
were looking at.
We did a very lengthy sort of use case
investigation, detailed user stories, et
cetera, et cetera.
And all of that broke down into those three
categories, speed, quality and efficiency.
So if I just take them sort of one by one, if
I talk about speed, so what this sort of
looks like in reality, if you imagine like
a sort of Formula One pitstop 60 years ago,
you know, they took two minutes or something.
Right. They weren't super safe and everyone
was just sort of making it up as they went
along, right.
And so what we're looking to do with this is
to make just like a Formula One pit stop in
two seconds or something, you know, change
our designs, change our processes, change the
way that people work together and just
overall making our blades much faster.
We don't release for quality blades into our
turbines if we have a quality issue early in
the manufacturing process, that just equates
to extra repair time later on in the process.
And that repair time obviously costs us
money. So if we can reduce quality defects
earlier on in the manufacturing and reduce
the repair time later on, this is a benefit
to all of us.
And then that then, I guess, ties in pretty
much directly to the final point efficiency.
You know, where we have staff working on
things in different ways.
We have a global footprint in factories
across, you know, countless countries and
we're spread across all the continents.
And so then there is the natural variability
in how blades are produced, even just between
onshore and offshore.
So reducing that variability, making sure
that each team is able to perform as well as
the best team, that's sort of what it's
about. So that those are the nuts
and bolts behind the technology that we've
developed. When you're developing something
that is truly cutting edge and hasn't been
done before, you don't know exactly how it's
going to turn out, you know, so so that's
always a bit of a challenge.
I mean, we of course, meet with the
executives of the company once a month, give
them status updates and let them know how
things are going.
But, you know, managing expectations about,
you know, what can we deliver?
How realistic is that?
I would say in our manufacturing we are you
know, we're quite agile, so to
speak. I mean, of course, we have all of the
standard manufacturing, you know, tax boards
and all of these sorts of things.
But I think when you work on something
that's truly cutting edge, it elevates
the standards of what used to be considered
impressive. The goalposts move, you know, and
then and then it raises everyone's game.
This is fundamental technology now that we've
developed that can be used for all sorts of
different use cases in manufacturing.
And we've already highlighted many of those
and actually even extra functionality even
onto this product.
So it's a key enabler in that sense.
And I would say it also sets the scene for
actually how we develop these sorts of
products in manufacturing.
So with the digital venture lab set up with
the relationships that we've now built and
really nurtured across the business and
between stakeholders in manufacturing,
digital teams in India, supply relationships,
et cetera, that really sets the scene for
future development the ways that we can
continue developing on this technology is
almost countless.
One of the things that we were probably
overly ambitious at the start of this
project, you know, I think there's
always a challenge when you when you're
scoping where to draw the line for the MVP or
the proof of concept.
You know, there's you on one side of the
coin. You don't want to dampen the enthusiasm
in your organization.
And on the other side of the coin, you want
to try and be as ambitious as possible.
And so so I think where we drew the line for
the proof of concept, which we which we
completed in the summer of last year, we were
probably overly ambitious with the different
levels of features that we would that we
would develop for that week.
We mainly focused on one particular feature,
but we probably should have pushed everything
else off to the side and looked at that at a
later stage.
We realized too late that there were
fundamental topics that we needed to cover.
And, you know, for example, the and it's
quite technical, but let's say the
positioning of the devices and which, you
know, it was in the early stages of
the project.
It was, you know, sort of make it up as you
go along and we'll fix that better later.
And whereas if we had taken a bit more time
and maybe moved a bit slower through some of
those more fundamental topics, then we would
have had a system, a system that was that
much more robust and didn't need resetting up.
And once we got past the sort of learning
phase. So I think it's a balance.
I mean, on one side, you really want to
develop quickly and move fast and fail
quickly and learn from it.
But then, of course, that means that later
on, in the later phase of the project, you
are having to rebuild quite a bit of stuff.
So I think now we are at least much more
aware of that.
We balance that and we're more aware of
moving fast, but also not maybe moving so
fast that we jeopardize the stability of
something later on.
For the last year, or at least for the last
six months, we've just been working on, you
know, making that more robust and more
resilient and more stable.
I don't think we underestimated the
development work that was required in getting
something production ready.
But I still think, you know, it still amazes
me when, you know, the more you get down the
development journey, the more details that
come up with something like the framerates
of the camera.
How, you know, not only does that then affect
the computational requirements that you have,
but also the networking, the power
consumption, maybe at the server room.
So, you know, each one of these little
things where you might develop a user story
and the knock on effects of that is huge.
When we have an update on one factory, we
push that out to all the different factories.
So so sort of knowledge sharing and lessons
learned and making all factories
perform like the best.
That's going to start to become much
more normal in our business.
To learn more about the solutions that
Siemens Gamesa implemented.
Be sure to check out their case study and
other resources linked here or visit Azure.com
For additional IoT solutions and
services.