February 13, 2020 • 30 mins
Imagine a future where machines could talk and tell us what they need––or a warehouse that could actively track not just your packages but also the wellbeing of the hardworking people behind the scenes of the assembly line. Advancements in the next generation of wireless connectivity and mobility are bringing that future closer with the promise of smart factories and connected production facilities. In this episode, we hear from Irene Petrick, Senior Director of Industrial Innovation in the Internet of Things Group at Intel; Pat McCusker, COO of Fast Radius, a company using 3D printing on an industrial scale to reimagine the supply chain; and Sean Petterson, founder of Strongarm Technologies, a company using data to help improve worker safety and reduce workplace injuries for factory and warehouse workers. Make sure to check out other episodes in this series featuring: Arthur Orduña, Chief Innovation Officer of Avis Budget Group and Oliver Cameron, Co-Founder and CEO of the startup Voyage.
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Episode Transcript
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Speaker 1 (00:02):
Last week's episode, we discussed the future of connected transportation
and the future of connected mass transit. We heard from
Arthur douna Chief Innovation officer of Avis Budget Group, the
global car rental company that also earned the popular car
sharing service zip car, on the Cameron, co founder and
CEO of the startup Voyage, which is testing and expanding
(00:22):
the use of autonomous vehicles in retirement communities, and Marcus Velts,
he leads the Siemens Intelligent Traffic Systems business in North America,
which is actively innovating to change the way we use
public transportation. Everything is getting smarter, from our watches, to
(00:45):
our homes to our cars. In a more connective future,
even the way our favorite things get processed and made
will be getting smarter. Factories where machines can tell their
teams in real time their status and eventual need for
repairs or a future and manufacturing worker safety can be
bolstered by real time data collected from new perspectives. The
(01:08):
next generation of wireless innovation with future five G networks
will create new opportunities for connected factories and the ever
changing landscape of manufacturing. Thanks to support from team Able
for Business Today will explore our advancements in five G
connectivity will enable innovations in the manufacturing industry that could
shape the future of production. In general, consumers want the
(01:44):
products exactly customized to their needs, to their body type,
to their foot size, etcetera. And so Henry Ford's you
can have any car if you want, as long as
it's black, just doesn't fit anymore. So the future is
a lot more digital, it's a lot more short term
in terms of having to respond to orders more quickly.
(02:06):
That's Irene Patrick. She is the senior director of Industrial
Innovation in the Internet of Things Group at Intel. Intel
is one of the world the largest manufacturers of computer chips.
All kinds of companies use those chips to power their businesses,
including other manufacturers. It's Irene's job to understand the challenges
(02:27):
those companies face so Intel can build solutions to help
the industry adapt to the future. The economies of scale
production that we've been living off of for the last
several decades really don't meet the needs of customization, highly
personalized kinds of products, and so we've got to find
ways to help factories become a lot more agile. Factories
(02:49):
are not often thought of as being agile, but several
technologies are coming together to make production lines far more responsive.
This is often referred to as industry full point oh.
Industry four dot O is really giving workers from the
factory floor clear to the C suite a very real
(03:10):
presentation of the operating environment in real time that's derived
from data that's collected from sensors throughout the factory. Eventually
this will reach clear into the supply chain, into the
enterprise resource systems, and so industry four dot O is
really saying, do we have a digital model of the
physical world. Can I use that digital model to simulate
(03:33):
what might happen if I change something in the physical world?
And then how can I improve things in the physical
world based upon those digital simulations. So it's really all
based on data, and that data is connected through an
intricate system of senses and connected machines. As complicated as
it sounds, is all driven by something rather simple. Manufacturing
(03:55):
only happens because somebody wants to buy something, and as
people's ideas about what they want to buy change, our
production has to change also, and we've been very slow
to do that. By the way, in the industrial space,
Intel is in the business of enabling the manufacturing ecosystem,
so irone is focused on understanding challenges facing the entire industry,
(04:16):
so Intel can create solutions at scale. We don't sell
the manufacturers, We sell to their suppliers, and so much
of the power behind things, much of the compute power
is provided by Intel, but it takes an ecosystem to
deliver that. The ecosystem as it sits today, where individual
companies provide an ingredient, is not going to be effective
(04:39):
into the future. We can't project Intel's thirty year journey
toward digitization into an existing manufacturer who hasn't been on
that same journey, and so we really have to understand
what the pressing problems are at a whole bunch of
levels of digital maturity, today's manufacturing landscape, increasingly driven by automation,
(05:00):
robotics and three D printing, might well look unrecognizable to
Henry Ford. According to Irene, the factories of the future
will be more efficient, faster, and increasingly data driven. Of course,
to make data actionable, you have to collect it, process
it and deliver results, and that's where future five G
(05:22):
networks could play a crucial role. More bandwidth, faster, networks
and lower latency could allow more manufacturers to make better
decisions in real time, increasing efficiency and improving products. In
this episode, we'll look at the latest innovations in manufacturing,
explore what it means for a factory to be smart,
(05:42):
and meet an entrepreneurs using technology to improve workers safety.
I'm as Velosian. Welcome to this time tomorrow. Kara I
really pointed out that companies make things because people want
or need to buy something. But when you're buying something,
how often do you think about how it's made. I
(06:04):
think it's something we're all becoming more conscious of, you know,
making sure that products we use aren't causing too much
environmental damage and that the workers who make them have
decent working conditions. That's right. I joke with Irene that
manufacturing is not exactly a clickbait topic, but it is
so fundamental to how we live. From cars to clothes
to robots, they're all manufactured in some capacity, and as
(06:27):
technology gets more advanced, new manufacturing techniques are created and
deployed at massive scale. Yeah, and you mentioned that Irene
works in the Internet of Things group at Intel, which
is a wild title. It is, you know, we think
of IoT in terms of meaning a smart speaker or
a connected fridge, but industrial machinery can also be a
(06:49):
part of that same connected future for sure, And as
we've spoken about before, there's a lot of enthusiasm that
the internd of things could really be enabled by future
five G networks because what about extracting and processing data
from those connected things? And that's something I discussed with
Pat mccuska, the CEO of fast Radius, which is a
company that's using three D printing on an industrial scale
(07:12):
to reimagine the supply chain. And I spoke with a
really cool guy named Sean Peterson who started a company
called strong Arm Technologies, which is a platform that's using
data to help improve workers safety and reduced workplace injuries
for factory and warehouse workers. Before we get to that,
let's go back to Irene, who introduced me to the
intriguing concept of dark data. I was always curious about
(07:38):
how things work and how things are put together. A
logical extension to that if you're a systems engineering which
is some of my background training, is how did these
systems fit together? And how can we improve to produce
better outputs. The kinds of things I work on now
are really looking at the problem spaces in the industrial
(07:58):
production environments in three to five to eight years out,
and then I bring that information back to our developers
and designers in the Industrial Solutions division, and then we
use that information to project out the kinds of solutions
that will be required and the way in which will
have to go to market with those solutions. Over time,
(08:19):
we've gotten pretty accustomed to the notion of a smart product.
You can have a smart fridge that tells you when
you're out of milk, or a smart coffee maker that, well,
I'm not untidy sure what they do, but they're out there.
And in the manufacturing world, experts of building and preparing
for smart factories, we talk about making factories smarter. It's
(08:41):
not that we have dumb factories now, it's that we
have factors that were set up to be very, very predictable.
Those factories are going to have to become much better
at dealing with ambiguity and dealing with variability. I'm not
just cranking out the same thing millions and millions of times.
I'm now having to think about how do develop inventory
(09:02):
control systems that bring me exactly what I need when
I need it. I've got to have material handling systems
that are completely agile and that really aren't like conveyor
belts of old. As we look towards the future, I
was curious as to how the next generation of wireless
connectivity and all the promise of future five G networks
could change manufacturing. If I had unlimited bandwidth, then I
(09:25):
could track a lot more things. So, for example, I
could instrument all of my workers in a way that
I could maximize their safety. I would understand their current
health status in terms of temperature, respiration, in terms of
the breathing environment around them. I could also merge data
in a way that would be more useful, particularly in
(09:47):
complex environments where the safety issue is very important. If
I had unlimited bandwidth, really understanding a lot of those
internal operations would be very useful. So five G offers
a lot of opportunities, particularly if I'm trying to work
in difficult environments where I have something moving, for example,
a mobile robot then flight. She has a lot of opportunities,
(10:10):
but it's going to require careful thought, and it's going
to require other things. Other technology used to be brought
along with it. It turns out that the future of
manufacturing is all about variability, which puts a premium on
collecting datamonitor machine health. I've got to have machines where
I know their health, I know their status, and I
(10:31):
can predict when they're likely to fail. If I understand
machine health before that tool breaks, I can actually schedule
a machine for maintenance so that I'm maximizing the uptime.
There's a lot of stuff going on around Internet of
Things related to what we call releasing dark data. Machines
are doing a lot of things. We just haven't always
(10:51):
had access to the data that describes what that is,
and so when we think about the Internet of things,
it's really about putting sensors in a lot of places
where we really don't have a lot of insights into
what the machine is doing or what the machines health is.
We're still going to have workers, they're going to be
doing different things, though. In the I T industry, for example,
(11:12):
the fastest growing jobs right now are jobs that didn't
have titles five or eight years ago. We're going to
see the same thing in manufacturing systems. Engineering is going
to become much more important. Simulation and digital design is
going to become much more important. Those are two that
come to mind that don't have as bigger role right
now that will five years from now or ten years
(11:33):
from now. Karl, I like what Irene was saying in
terms of augmented intelligence, reminding me a little bit of
what Gary Kasparoff, the chess grandmaster, once said after he
got beaten by IBM's Computed Deep Blue. Kasparov said that
the future will belong to centaurs human machine hybrids. I mean,
(11:54):
I use machines every day to get me or I
need to go. That's right, but you know, the future
is closer than we think in that regard. In our
episode on sports and gaming, you remember we talked to
Charlie Hahn, who helped build Hollow Lens at Microsoft, and
he explained how they're are headset can be used by
someone who's repairing the part of an airplane, and in
real time they can receive information and instructions directly in
(12:17):
their field of vision. So I can imagine a world
where every factory worker is getting information about what they're
making or their environment. Yeah. I think Charlie Hahn was
talking about a partnership between Microsoft and quantas doing exactly
what you described and Charlie talked about how hollow lens
and augmented reality in general could be powered by future
(12:37):
fight G networks with more bandwidth and lower latency, allowing
for steamless toggling between the real and virtual worlds mixed reality.
He calls it in terms of industry that a our
future couldn't make workers more informed, more efficient, and even safer,
And we're actually going to talk about that with Sean
Peterson of strong Arm a little bit later on the show.
(12:57):
Right before that, though, I do want to spend a
at more time exploring this notion of the smart factory
to better understand it. Ice, but with the CEO of
fast Radius, Pat mccuske, about advanced manufacturing techniques that are
being pioneered right now. Fast Radius is a manufacturing technology firm.
We help companies launch and develop new products and business
(13:22):
models uniquely enabled by advanced manufacturing. Companies who want to
go embrace a new innovative product, be at a consumer
device or a medical device, or an aerospace or industrial device,
and they want a partner to go figure out the
best way to design and manufacture that product. That's where
fast Radius comes in, and then we actually produce products
(13:44):
at our factor here in Chicago and in Louisville. We
have a software platform that we've built from the ground
up that helps customers through this entire journey from the
design stage all the way through to production. The fast
Radius Chicago plant was named one of the nine best
factories in the world by the World Economic Forum in
because of its use of new manufacturing technologies, specifically what's
(14:08):
called additive manufacturing. Though you may know it by a
different name, three D printing and additive manufacturing are kind
of synonymous terms, and three D printings has been around
for thirty forty years now. You know, you have maker
bot and the kind of consumer thing that kids have
at their school or you may have as a hobbyist,
and so we typically refer to that as three D
printing additive manufacturing, while conceptually the same thing kind of
(14:33):
connotes more industrial grade, so you're really making real end
us parts. This is parts that are going on to
the engine of an airplane or a car. So there's
subtractive manufacturing, which is a traditional you know, start with
a block of steel and and carve something out of
that block of steel to create the shape and geometry
you're trying to produce additive is adding layers of material
(14:54):
one at a time to sort of build up additively
the product that you're making. These new advanced manufacturing techniques
like additive, they're really hard. It's not like your two
D printer where you just plug it in and hit
a button and press print and outcomes a beautiful part.
It's actually a really difficult process that you have to
control all kinds of variables, from the humidity in the room,
(15:14):
to the vibration to the temperature of the resident, etcetera.
To be honest, I didn't know that three D printing
had been around for decades or how transformative additive manufacturing
could be an industrial context. But it turns out the
supply chains of the future could be entirely digital. Today,
if you want to have a set of spare parts
for your product, you make, you know, a hundred thousand
(15:37):
of them, a million of them, whatever you think you need,
and you store those in a warehouse for years, in
some cases decades. Now what you can do is move
those parts into a digital warehouse that's managed by fast radius,
and we produced the parts on demand when you need them,
no more, no less than you need We like to
say we're creating the world's biggest warehouse, a billion square feet,
(15:58):
but it's all digital, right, There's no a coal warehouse
that paints a picture of an entirely different design process. Today,
the normal process is to design a product and then
put in a giant order for parts. Tomorrow, more and
more businesses will be able to develop products in real
time and manufacture the necessary parts as the product evolveds.
(16:19):
So what makes all of this possible. We're gathering all
this data which allows us to build what many would
consider a quote unquote smart factory. We use a term
called the digital thread. So having that data all the
way from the materials formulation to the production and every
piece of data right the temperature in the room, the vibration,
(16:40):
who was a technician who worked on it, What is
the diversion of the design, What is the machine number
that was run on? What time? How long do it think?
What are the data points that you need to collect
in order to drive real value in a factory environment.
Just as Irene outlined, the flexible manufacturing of the future
will be underpinned by stint class data gathering and processing. Today,
(17:03):
WiFi and hard wired networks player b ruling factories. The
future five G networks promised to be faster and more
reliable and support more connected devices. Right now, we're using
just traditional WiFi, but we can absolutely envision an environment
where we would have a five G network that would
allow us to gather even more data more quickly, more efficiently,
(17:24):
and so we're keeping an eye on that and exploring,
you know, what are the limits of WiFi and how
do we think about maybe transitioning to five G. So
not going to happen tomorrow, but we're excited about just
this greater bandwidth and what we may be able to
do with regard to gathering even more data intensive points
of capture that would allow us to drive even richer insight.
(17:49):
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(18:09):
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(18:30):
for business dot com. So Carrot, this idea of the
digital warehouse is interesting. If more companies moved to that model,
we might be able to replace a lot of these
traditional warehouses that store products with trees and forests, or
at the very least, to reduce the environmental cost of
(18:52):
shipping pots around the world. I actually think that the
definition of factory might change in the near future, especially
when so much is store it in the cloud. We'll
see three D printing on an industrial scale, and I
had no idea that three D printing technology had been
around for so long or what it could even enable.
Actually learned that some of the new breed of antennas
(19:13):
that will underpin future five G are actually being three
D printed, so we sort of see the wheel coming
full circle. Of course, all of this talk of three
D printing and automated manufacturing does raise questions about what
happens to factory workers who are being displaced. Irene talked
about developing new skills, but that might not be available
(19:33):
to everyone. That's true, and it's part of a bigger
conversation about what happens to labor in an age of automation.
But in the meantime, there are some bright spots for
the workers of today when it comes to technological innovation.
I spoke with Sean Peterson, who is using technology, but
his goal is to improve worker safety for what he
calls industrial athletes, and industrial athlete is so what we
(20:00):
like to call em manual labor. The way that we
look at blue collar work is the same that we
look at professional athletes. You go out, you put your
body on the line to put bread on the table.
Professional athletes do that for a few hours a day
with the best equipment in the world. But there's guys
that go out and do it for eight hours a
day and they do it for the course of forty years,
six days a week. So putting your body on that
(20:21):
level of rigor just to provide for the family if
your own life, for us, earns the moniker of industrial athlete.
We're an industrial safety science company and we drive the
world's leading risk metrics for these industrial athletes to help
reduce injuries on average of thirty year of a year.
That's Sean Peterson. He didn't always think he would become
(20:41):
a tech entrepreneur. Originally he thought he would join the
family construction business. I grew up thinking I was going
to run or participate in the family construction company. And
my father passed away in the job. Sorry, I went
off and I became an entrepreneur, and along that entrepreneurial
journey fell in love with this problem. That are these injuries,
(21:02):
that are these these opportunities to provide a level of
design intent to make a better life for these people.
Not only are manufacturing and warehouse workers exposed to potential injury,
the physical nature of their job exposes them to long
term bodily risk. Just think about lifting a box over
your head thirty or forty times. How many opportunities there
(21:25):
are for something to go wrong. That's where strong arm
comes into play. We created a wearable sensor that measures
all of the risk that an industrial athlete goes through
throughout his day. It's a small center, It's like twice
the size of a TIC tech box, and you wear
it on your chests. Are you wear it in a
shirt pocket or you clip it onto your false safety
harness and we provide alerts to help avoid those injuries
(21:48):
to that individual real time, and then we drive metrics
bacted management to help them make better decisions on how
to invest in further infrastructure, in training and equipment to
help eliminate those injuries in the future. And the platform
we have is called the FUSE platform. The FUSE platform
can do things like tell you that you're twisting in
a way that is unhealthy for your back, or that
(22:09):
you're approaching an area that is especially risky. We're looking
at all of the motions that he's going through that
they're risky and how they relate to the degradation of
his lumbar spine or his lower back, or just his
chance of getting a muscule skeletal injury, and we provide
an alert before he does something risky. We then drive
further insight through other types of environmental awareness, so we
collect heat information, humidity, air quality, as well as looking
(22:33):
out for ordorless gases, things that people would be worried about,
and we provide an early alert around those exposures. That
alert would either say, hey, you should change whatever respirator
you're wearing because we've noticed you're going through higher levels
of exposure and then you previously thought you would is
an area where you should be wearing a hardhead? Is
there an area where you need a certain amount of
training on? Of course, today there are ways to communicate
(22:56):
this type of information. Think about all of those hard
hats on minds you see on construction sites. But in
the future, it may be possible to serve this information
in real time with contextual relevance. You're working in a
really hot environment, so we're gonna measure that heat and
once you hit over that exposure rate, we're gonna give
you haptic feedback to say get out of the truck
(23:17):
for fifteen minutes and go have some water. It's just
like someone tap you on the shoulder to say, hey,
watch out for this. We provide all of that information
that insight directly to the individual, and then at the
end of the day, all that information is shot up
to the cloud, where managers and the greater ecosystem in
the value chain can now get insight into that risk
and all of that data can then be used to
(23:39):
make bigger decisions about future optimizations, addressing problems before they arise.
A quick skin of our data showed us that on
this conveyor line, essentially that people were twisting so fast
that that's why they were getting hurt. It was a
sagital twisting velocity, which is one of the factors of
our GROTHM that we collect. We said, they're twisting so fast,
(24:00):
no training, there's no extoskeleton, there's no way that we
can change this. We're going to have to go for
an infrastructural change. So we recommended a conveyor belt that
had a forty or five degree bend in it to
just eliminate that twisting. What we saw was not only
a complete elimination of that injury entirely, but the uptime
and the factory was such that we're able to now
afford such a greater r y that we equipped the
(24:22):
rest of the warehouse with safer equipment. So we're just
helping them get better at getting the people who are
in the door that are doing this job, which by
injury rate, is the riskiest job in the world. And
now we're just using technology to help them retain those
individuals and then help those people be safer so they're
less problems going forward unless turnover it. The FUSE platform
collects data that can help drive decision making. But this
(24:45):
carries with it obvious privacy concerns, So Sean says that
strong Arm is thoughtful about the kind of data they collect.
Our devices are built with that industrial athlete in mind,
all the way down to the way the information is
not only delivered, but what's also collected. We don't touch
anything over Hippo. We're not driving any biometrics individually on
this person. It's all externally monitable information, and the information
(25:09):
is built on a compliant database that can allow us
to anonymize that individual's risk profile at the drop of
the hat. Sean believes that that risk profile can help
keep workers safe, ultimately creating more efficiency and productivity. In
the same way that the industry of the future may
allow us to create individualized products, it could also allow
(25:30):
manufacturers to tailor work to individual workers. What we're really
trying to get clients to understand is that you can't
just drive people through through print metric. You have to
focus on the capabilities of that individual and what is
safe for them. Otherwise it's like filling a bucket with
a hole in the bottom. You can't just work these
people to the bone. You need to be incredibly sensitive
(25:50):
to what the individual capabilities are in higher additionally or
trained additionally in and around that. The greater good here
is just we want to continue to honor workforce in
order to create a better network of innovation inside of
a safety angle, and that's what we're driving for. So
if anyone hates it, it's never gonna work, and that's
(26:10):
the truth of it. Many of the initiatives Sewn describes
are already possible today, so I was curious what might
be possible when future five G networks have been fully deployed.
In the future, we are really excited about the potential
for things like five G to enable us to deliver
that insight in real times athlete and also go back
up to management. So if that person is a remote
(26:32):
worker and they're down, we can now send someone to
where they are to help assist or see what the
problem is. As well as allowing for real time response.
Five G that is widely used could allow companies like
strong Arm to partner with new industries in areas where
connectivity is challenging. Better networks enable us to reach further
outside of industries, both in higher risk and more constrained areas.
(26:56):
So we primarily operate through geologistics and light manufacturing. I
started this company because of my personal connection and construction.
So our next vertical is construction, then remote work, then
oil and gas um and then heavy manufacturing. Available now
(27:17):
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that a machine needs to be repaired to on demand
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(28:22):
That seems to be a surprising amount to get excited
about in the future of manufacturing. I didn't even know
I could get excited about the future of manufacturing now,
but it's for It is really cool, and so much
of what we talked about comes down to data and
making better decisions in real time. It reminds me of
one of the early episodes of This Time Tomorrow, when
we talked to the Menlo Park fire chief. He explained
(28:43):
that the lower latency and higher bandwidth promised by future
five G networks could enable him to keep track of
his firefighters as they entered burning buildings, and that idea
of monitoring and optimization is exactly what Sean was talking about.
Personalization is such a key theme of the new economy,
and the personalization of products is something everyone can understand
(29:05):
fairly easily. But I love what Sean was talking about
in terms of personalizing worker responsibilities in a factory. To
make this vision real, though, factories and businesses will have
to adapt to become more agile. In Irian's words, well,
how will I get customized sucks otherwise. I think one
(29:26):
of the biggest takeaways that I learned while researching this
episode is that, well, we don't know exactly how things
will change. That there are too many technical and cultural
drivers converging for manufacturing to kind of stay as it
is today. Yeah, and whether it's the expansion of the
Internet of Things, or robotics or three D printing, industry
is becoming more digital and the new infrastructure of future
(29:49):
five gen networks could be the platform that digital future
is built upon. On the next episode of This Time Tomorrow,
we'll look how technology is changing one of the world's
oldest businesses, agriculture. From robots suerial imaging, we explore how
technology is changing the way we farm and the role
(30:11):
that five G could play. I'm as vlachen see you
next time. No matter what you're after, T Mobile for
Business is here with a network born mobile and built
from the ground up for the next wave of innovation,
from mobile broadband to IoT to workforce mobility, and everything
(30:35):
in between. T Mobile for Business is committed to helping
you move your business forward with the products and services
you need, as well as the dedicated, award winning customer
service you'd expect from America's most loved wireless company. Business
is changing. Learn more at T Mobile for Business dot com.
Last week's episode, we discussed the future of connected transportation
and the future of connected mass transit. We heard from
Arthur douna Chief Innovation officer of Avis Budget Group, the
global car rental company that also earned the popular car
sharing service zip car, on the Cameron, co founder and
CEO of the startup Voyage, which is testing and expanding
(00:22):
the use of autonomous vehicles in retirement communities, and Marcus Velts,
he leads the Siemens Intelligent Traffic Systems business in North America,
which is actively innovating to change the way we use
public transportation. Everything is getting smarter, from our watches, to
(00:45):
our homes to our cars. In a more connective future,
even the way our favorite things get processed and made
will be getting smarter. Factories where machines can tell their
teams in real time their status and eventual need for
repairs or a future and manufacturing worker safety can be
bolstered by real time data collected from new perspectives. The
(01:08):
next generation of wireless innovation with future five G networks
will create new opportunities for connected factories and the ever
changing landscape of manufacturing. Thanks to support from team Able
for Business Today will explore our advancements in five G
connectivity will enable innovations in the manufacturing industry that could
shape the future of production. In general, consumers want the
(01:44):
products exactly customized to their needs, to their body type,
to their foot size, etcetera. And so Henry Ford's you
can have any car if you want, as long as
it's black, just doesn't fit anymore. So the future is
a lot more digital, it's a lot more short term
in terms of having to respond to orders more quickly.
(02:06):
That's Irene Patrick. She is the senior director of Industrial
Innovation in the Internet of Things Group at Intel. Intel
is one of the world the largest manufacturers of computer chips.
All kinds of companies use those chips to power their businesses,
including other manufacturers. It's Irene's job to understand the challenges
(02:27):
those companies face so Intel can build solutions to help
the industry adapt to the future. The economies of scale
production that we've been living off of for the last
several decades really don't meet the needs of customization, highly
personalized kinds of products, and so we've got to find
ways to help factories become a lot more agile. Factories
(02:49):
are not often thought of as being agile, but several
technologies are coming together to make production lines far more responsive.
This is often referred to as industry full point oh.
Industry four dot O is really giving workers from the
factory floor clear to the C suite a very real
(03:10):
presentation of the operating environment in real time that's derived
from data that's collected from sensors throughout the factory. Eventually
this will reach clear into the supply chain, into the
enterprise resource systems, and so industry four dot O is
really saying, do we have a digital model of the
physical world. Can I use that digital model to simulate
(03:33):
what might happen if I change something in the physical world?
And then how can I improve things in the physical
world based upon those digital simulations. So it's really all
based on data, and that data is connected through an
intricate system of senses and connected machines. As complicated as
it sounds, is all driven by something rather simple. Manufacturing
(03:55):
only happens because somebody wants to buy something, and as
people's ideas about what they want to buy change, our
production has to change also, and we've been very slow
to do that. By the way, in the industrial space,
Intel is in the business of enabling the manufacturing ecosystem,
so irone is focused on understanding challenges facing the entire industry,
(04:16):
so Intel can create solutions at scale. We don't sell
the manufacturers, We sell to their suppliers, and so much
of the power behind things, much of the compute power
is provided by Intel, but it takes an ecosystem to
deliver that. The ecosystem as it sits today, where individual
companies provide an ingredient, is not going to be effective
(04:39):
into the future. We can't project Intel's thirty year journey
toward digitization into an existing manufacturer who hasn't been on
that same journey, and so we really have to understand
what the pressing problems are at a whole bunch of
levels of digital maturity, today's manufacturing landscape, increasingly driven by automation,
(05:00):
robotics and three D printing, might well look unrecognizable to
Henry Ford. According to Irene, the factories of the future
will be more efficient, faster, and increasingly data driven. Of course,
to make data actionable, you have to collect it, process
it and deliver results, and that's where future five G
(05:22):
networks could play a crucial role. More bandwidth, faster, networks
and lower latency could allow more manufacturers to make better
decisions in real time, increasing efficiency and improving products. In
this episode, we'll look at the latest innovations in manufacturing,
explore what it means for a factory to be smart,
(05:42):
and meet an entrepreneurs using technology to improve workers safety.
I'm as Velosian. Welcome to this time tomorrow. Kara I
really pointed out that companies make things because people want
or need to buy something. But when you're buying something,
how often do you think about how it's made. I
(06:04):
think it's something we're all becoming more conscious of, you know,
making sure that products we use aren't causing too much
environmental damage and that the workers who make them have
decent working conditions. That's right. I joke with Irene that
manufacturing is not exactly a clickbait topic, but it is
so fundamental to how we live. From cars to clothes
to robots, they're all manufactured in some capacity, and as
(06:27):
technology gets more advanced, new manufacturing techniques are created and
deployed at massive scale. Yeah, and you mentioned that Irene
works in the Internet of Things group at Intel, which
is a wild title. It is, you know, we think
of IoT in terms of meaning a smart speaker or
a connected fridge, but industrial machinery can also be a
(06:49):
part of that same connected future for sure, And as
we've spoken about before, there's a lot of enthusiasm that
the internd of things could really be enabled by future
five G networks because what about extracting and processing data
from those connected things? And that's something I discussed with
Pat mccuska, the CEO of fast Radius, which is a
company that's using three D printing on an industrial scale
(07:12):
to reimagine the supply chain. And I spoke with a
really cool guy named Sean Peterson who started a company
called strong Arm Technologies, which is a platform that's using
data to help improve workers safety and reduced workplace injuries
for factory and warehouse workers. Before we get to that,
let's go back to Irene, who introduced me to the
intriguing concept of dark data. I was always curious about
(07:38):
how things work and how things are put together. A
logical extension to that if you're a systems engineering which
is some of my background training, is how did these
systems fit together? And how can we improve to produce
better outputs. The kinds of things I work on now
are really looking at the problem spaces in the industrial
(07:58):
production environments in three to five to eight years out,
and then I bring that information back to our developers
and designers in the Industrial Solutions division, and then we
use that information to project out the kinds of solutions
that will be required and the way in which will
have to go to market with those solutions. Over time,
(08:19):
we've gotten pretty accustomed to the notion of a smart product.
You can have a smart fridge that tells you when
you're out of milk, or a smart coffee maker that, well,
I'm not untidy sure what they do, but they're out there.
And in the manufacturing world, experts of building and preparing
for smart factories, we talk about making factories smarter. It's
(08:41):
not that we have dumb factories now, it's that we
have factors that were set up to be very, very predictable.
Those factories are going to have to become much better
at dealing with ambiguity and dealing with variability. I'm not
just cranking out the same thing millions and millions of times.
I'm now having to think about how do develop inventory
(09:02):
control systems that bring me exactly what I need when
I need it. I've got to have material handling systems
that are completely agile and that really aren't like conveyor
belts of old. As we look towards the future, I
was curious as to how the next generation of wireless
connectivity and all the promise of future five G networks
could change manufacturing. If I had unlimited bandwidth, then I
(09:25):
could track a lot more things. So, for example, I
could instrument all of my workers in a way that
I could maximize their safety. I would understand their current
health status in terms of temperature, respiration, in terms of
the breathing environment around them. I could also merge data
in a way that would be more useful, particularly in
(09:47):
complex environments where the safety issue is very important. If
I had unlimited bandwidth, really understanding a lot of those
internal operations would be very useful. So five G offers
a lot of opportunities, particularly if I'm trying to work
in difficult environments where I have something moving, for example,
a mobile robot then flight. She has a lot of opportunities,
(10:10):
but it's going to require careful thought, and it's going
to require other things. Other technology used to be brought
along with it. It turns out that the future of
manufacturing is all about variability, which puts a premium on
collecting datamonitor machine health. I've got to have machines where
I know their health, I know their status, and I
(10:31):
can predict when they're likely to fail. If I understand
machine health before that tool breaks, I can actually schedule
a machine for maintenance so that I'm maximizing the uptime.
There's a lot of stuff going on around Internet of
Things related to what we call releasing dark data. Machines
are doing a lot of things. We just haven't always
(10:51):
had access to the data that describes what that is,
and so when we think about the Internet of things,
it's really about putting sensors in a lot of places
where we really don't have a lot of insights into
what the machine is doing or what the machines health is.
We're still going to have workers, they're going to be
doing different things, though. In the I T industry, for example,
(11:12):
the fastest growing jobs right now are jobs that didn't
have titles five or eight years ago. We're going to
see the same thing in manufacturing systems. Engineering is going
to become much more important. Simulation and digital design is
going to become much more important. Those are two that
come to mind that don't have as bigger role right
now that will five years from now or ten years
(11:33):
from now. Karl, I like what Irene was saying in
terms of augmented intelligence, reminding me a little bit of
what Gary Kasparoff, the chess grandmaster, once said after he
got beaten by IBM's Computed Deep Blue. Kasparov said that
the future will belong to centaurs human machine hybrids. I mean,
(11:54):
I use machines every day to get me or I
need to go. That's right, but you know, the future
is closer than we think in that regard. In our
episode on sports and gaming, you remember we talked to
Charlie Hahn, who helped build Hollow Lens at Microsoft, and
he explained how they're are headset can be used by
someone who's repairing the part of an airplane, and in
real time they can receive information and instructions directly in
(12:17):
their field of vision. So I can imagine a world
where every factory worker is getting information about what they're
making or their environment. Yeah. I think Charlie Hahn was
talking about a partnership between Microsoft and quantas doing exactly
what you described and Charlie talked about how hollow lens
and augmented reality in general could be powered by future
(12:37):
fight G networks with more bandwidth and lower latency, allowing
for steamless toggling between the real and virtual worlds mixed reality.
He calls it in terms of industry that a our
future couldn't make workers more informed, more efficient, and even safer,
And we're actually going to talk about that with Sean
Peterson of strong Arm a little bit later on the show.
(12:57):
Right before that, though, I do want to spend a
at more time exploring this notion of the smart factory
to better understand it. Ice, but with the CEO of
fast Radius, Pat mccuske, about advanced manufacturing techniques that are
being pioneered right now. Fast Radius is a manufacturing technology firm.
We help companies launch and develop new products and business
(13:22):
models uniquely enabled by advanced manufacturing. Companies who want to
go embrace a new innovative product, be at a consumer
device or a medical device, or an aerospace or industrial device,
and they want a partner to go figure out the
best way to design and manufacture that product. That's where
fast Radius comes in, and then we actually produce products
(13:44):
at our factor here in Chicago and in Louisville. We
have a software platform that we've built from the ground
up that helps customers through this entire journey from the
design stage all the way through to production. The fast
Radius Chicago plant was named one of the nine best
factories in the world by the World Economic Forum in
because of its use of new manufacturing technologies, specifically what's
(14:08):
called additive manufacturing. Though you may know it by a
different name, three D printing and additive manufacturing are kind
of synonymous terms, and three D printings has been around
for thirty forty years now. You know, you have maker
bot and the kind of consumer thing that kids have
at their school or you may have as a hobbyist,
and so we typically refer to that as three D
printing additive manufacturing, while conceptually the same thing kind of
(14:33):
connotes more industrial grade, so you're really making real end
us parts. This is parts that are going on to
the engine of an airplane or a car. So there's
subtractive manufacturing, which is a traditional you know, start with
a block of steel and and carve something out of
that block of steel to create the shape and geometry
you're trying to produce additive is adding layers of material
(14:54):
one at a time to sort of build up additively
the product that you're making. These new advanced manufacturing techniques
like additive, they're really hard. It's not like your two
D printer where you just plug it in and hit
a button and press print and outcomes a beautiful part.
It's actually a really difficult process that you have to
control all kinds of variables, from the humidity in the room,
(15:14):
to the vibration to the temperature of the resident, etcetera.
To be honest, I didn't know that three D printing
had been around for decades or how transformative additive manufacturing
could be an industrial context. But it turns out the
supply chains of the future could be entirely digital. Today,
if you want to have a set of spare parts
for your product, you make, you know, a hundred thousand
(15:37):
of them, a million of them, whatever you think you need,
and you store those in a warehouse for years, in
some cases decades. Now what you can do is move
those parts into a digital warehouse that's managed by fast radius,
and we produced the parts on demand when you need them,
no more, no less than you need We like to
say we're creating the world's biggest warehouse, a billion square feet,
(15:58):
but it's all digital, right, There's no a coal warehouse
that paints a picture of an entirely different design process. Today,
the normal process is to design a product and then
put in a giant order for parts. Tomorrow, more and
more businesses will be able to develop products in real
time and manufacture the necessary parts as the product evolveds.
(16:19):
So what makes all of this possible. We're gathering all
this data which allows us to build what many would
consider a quote unquote smart factory. We use a term
called the digital thread. So having that data all the
way from the materials formulation to the production and every
piece of data right the temperature in the room, the vibration,
(16:40):
who was a technician who worked on it, What is
the diversion of the design, What is the machine number
that was run on? What time? How long do it think?
What are the data points that you need to collect
in order to drive real value in a factory environment.
Just as Irene outlined, the flexible manufacturing of the future
will be underpinned by stint class data gathering and processing. Today,
(17:03):
WiFi and hard wired networks player b ruling factories. The
future five G networks promised to be faster and more
reliable and support more connected devices. Right now, we're using
just traditional WiFi, but we can absolutely envision an environment
where we would have a five G network that would
allow us to gather even more data more quickly, more efficiently,
(17:24):
and so we're keeping an eye on that and exploring,
you know, what are the limits of WiFi and how
do we think about maybe transitioning to five G. So
not going to happen tomorrow, but we're excited about just
this greater bandwidth and what we may be able to
do with regard to gathering even more data intensive points
of capture that would allow us to drive even richer insight.
(17:49):
The future with five G is coming today. T Mobile
is leading the five G charge with thirty billion dollars
invested in their network to deliver new capabilities in proved
connectivity and true mobility provided by an advanced network from
T Mobile for Business could change the way we all
live and work. The five G era will take the
(18:09):
best technologies available today in the wireless space so that
you can offer new capabilities to your business customers. T
Mobile for Business knows that the future of business will
be powered by advancements in wireless networks, with these new
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job done. Business is changing. Learn more at t Mobile
(18:30):
for business dot com. So Carrot, this idea of the
digital warehouse is interesting. If more companies moved to that model,
we might be able to replace a lot of these
traditional warehouses that store products with trees and forests, or
at the very least, to reduce the environmental cost of
(18:52):
shipping pots around the world. I actually think that the
definition of factory might change in the near future, especially
when so much is store it in the cloud. We'll
see three D printing on an industrial scale, and I
had no idea that three D printing technology had been
around for so long or what it could even enable.
Actually learned that some of the new breed of antennas
(19:13):
that will underpin future five G are actually being three
D printed, so we sort of see the wheel coming
full circle. Of course, all of this talk of three
D printing and automated manufacturing does raise questions about what
happens to factory workers who are being displaced. Irene talked
about developing new skills, but that might not be available
(19:33):
to everyone. That's true, and it's part of a bigger
conversation about what happens to labor in an age of automation.
But in the meantime, there are some bright spots for
the workers of today when it comes to technological innovation.
I spoke with Sean Peterson, who is using technology, but
his goal is to improve worker safety for what he
calls industrial athletes, and industrial athlete is so what we
(20:00):
like to call em manual labor. The way that we
look at blue collar work is the same that we
look at professional athletes. You go out, you put your
body on the line to put bread on the table.
Professional athletes do that for a few hours a day
with the best equipment in the world. But there's guys
that go out and do it for eight hours a
day and they do it for the course of forty years,
six days a week. So putting your body on that
(20:21):
level of rigor just to provide for the family if
your own life, for us, earns the moniker of industrial athlete.
We're an industrial safety science company and we drive the
world's leading risk metrics for these industrial athletes to help
reduce injuries on average of thirty year of a year.
That's Sean Peterson. He didn't always think he would become
(20:41):
a tech entrepreneur. Originally he thought he would join the
family construction business. I grew up thinking I was going
to run or participate in the family construction company. And
my father passed away in the job. Sorry, I went
off and I became an entrepreneur, and along that entrepreneurial
journey fell in love with this problem. That are these injuries,
(21:02):
that are these these opportunities to provide a level of
design intent to make a better life for these people.
Not only are manufacturing and warehouse workers exposed to potential injury,
the physical nature of their job exposes them to long
term bodily risk. Just think about lifting a box over
your head thirty or forty times. How many opportunities there
(21:25):
are for something to go wrong. That's where strong arm
comes into play. We created a wearable sensor that measures
all of the risk that an industrial athlete goes through
throughout his day. It's a small center, It's like twice
the size of a TIC tech box, and you wear
it on your chests. Are you wear it in a
shirt pocket or you clip it onto your false safety
harness and we provide alerts to help avoid those injuries
(21:48):
to that individual real time, and then we drive metrics
bacted management to help them make better decisions on how
to invest in further infrastructure, in training and equipment to
help eliminate those injuries in the future. And the platform
we have is called the FUSE platform. The FUSE platform
can do things like tell you that you're twisting in
a way that is unhealthy for your back, or that
(22:09):
you're approaching an area that is especially risky. We're looking
at all of the motions that he's going through that
they're risky and how they relate to the degradation of
his lumbar spine or his lower back, or just his
chance of getting a muscule skeletal injury, and we provide
an alert before he does something risky. We then drive
further insight through other types of environmental awareness, so we
collect heat information, humidity, air quality, as well as looking
(22:33):
out for ordorless gases, things that people would be worried about,
and we provide an early alert around those exposures. That
alert would either say, hey, you should change whatever respirator
you're wearing because we've noticed you're going through higher levels
of exposure and then you previously thought you would is
an area where you should be wearing a hardhead? Is
there an area where you need a certain amount of
training on? Of course, today there are ways to communicate
(22:56):
this type of information. Think about all of those hard
hats on minds you see on construction sites. But in
the future, it may be possible to serve this information
in real time with contextual relevance. You're working in a
really hot environment, so we're gonna measure that heat and
once you hit over that exposure rate, we're gonna give
you haptic feedback to say get out of the truck
(23:17):
for fifteen minutes and go have some water. It's just
like someone tap you on the shoulder to say, hey,
watch out for this. We provide all of that information
that insight directly to the individual, and then at the
end of the day, all that information is shot up
to the cloud, where managers and the greater ecosystem in
the value chain can now get insight into that risk
and all of that data can then be used to
(23:39):
make bigger decisions about future optimizations, addressing problems before they arise.
A quick skin of our data showed us that on
this conveyor line, essentially that people were twisting so fast
that that's why they were getting hurt. It was a
sagital twisting velocity, which is one of the factors of
our GROTHM that we collect. We said, they're twisting so fast,
(24:00):
no training, there's no extoskeleton, there's no way that we
can change this. We're going to have to go for
an infrastructural change. So we recommended a conveyor belt that
had a forty or five degree bend in it to
just eliminate that twisting. What we saw was not only
a complete elimination of that injury entirely, but the uptime
and the factory was such that we're able to now
afford such a greater r y that we equipped the
(24:22):
rest of the warehouse with safer equipment. So we're just
helping them get better at getting the people who are
in the door that are doing this job, which by
injury rate, is the riskiest job in the world. And
now we're just using technology to help them retain those
individuals and then help those people be safer so they're
less problems going forward unless turnover it. The FUSE platform
collects data that can help drive decision making. But this
(24:45):
carries with it obvious privacy concerns, So Sean says that
strong Arm is thoughtful about the kind of data they collect.
Our devices are built with that industrial athlete in mind,
all the way down to the way the information is
not only delivered, but what's also collected. We don't touch
anything over Hippo. We're not driving any biometrics individually on
this person. It's all externally monitable information, and the information
(25:09):
is built on a compliant database that can allow us
to anonymize that individual's risk profile at the drop of
the hat. Sean believes that that risk profile can help
keep workers safe, ultimately creating more efficiency and productivity. In
the same way that the industry of the future may
allow us to create individualized products, it could also allow
(25:30):
manufacturers to tailor work to individual workers. What we're really
trying to get clients to understand is that you can't
just drive people through through print metric. You have to
focus on the capabilities of that individual and what is
safe for them. Otherwise it's like filling a bucket with
a hole in the bottom. You can't just work these
people to the bone. You need to be incredibly sensitive
(25:50):
to what the individual capabilities are in higher additionally or
trained additionally in and around that. The greater good here
is just we want to continue to honor workforce in
order to create a better network of innovation inside of
a safety angle, and that's what we're driving for. So
if anyone hates it, it's never gonna work, and that's
(26:10):
the truth of it. Many of the initiatives Sewn describes
are already possible today, so I was curious what might
be possible when future five G networks have been fully deployed.
In the future, we are really excited about the potential
for things like five G to enable us to deliver
that insight in real times athlete and also go back
up to management. So if that person is a remote
(26:32):
worker and they're down, we can now send someone to
where they are to help assist or see what the
problem is. As well as allowing for real time response.
Five G that is widely used could allow companies like
strong Arm to partner with new industries in areas where
connectivity is challenging. Better networks enable us to reach further
outside of industries, both in higher risk and more constrained areas.
(26:56):
So we primarily operate through geologistics and light manufacturing. I
started this company because of my personal connection and construction.
So our next vertical is construction, then remote work, then
oil and gas um and then heavy manufacturing. Available now
(27:17):
from my Heart a new series presented by Tembile for business,
The Restless Ones join host Johnson Strickland as he explores
the upcoming five Year Revolution and the business leaders who
stand right on the cutting edge. There are certain decision
makers who are restless. They know there is a better
way to get things done, and they're ready, curious and
excited for the next technological innovation to unlock their vision
(27:40):
of the future. These restless Ones are in pursuit of bigger, better, smarter, stronger.
They seek new partners, new strategies, new processes. They pursue
innovative platforms and solutions to propel their teams, businesses, and
industries forward. In each episode, we'll learn more from the
restler Ones themselves and dive deep into how they think
(28:02):
the five Year Evolution could propel that business forward. The
Restless Ones is now available on the i Heart radio
app wherever you listen to podcasts. Soka from knowing beforehand
that a machine needs to be repaired to on demand
product printing and analyzing data to drive work is safety.
(28:22):
That seems to be a surprising amount to get excited
about in the future of manufacturing. I didn't even know
I could get excited about the future of manufacturing now,
but it's for It is really cool, and so much
of what we talked about comes down to data and
making better decisions in real time. It reminds me of
one of the early episodes of This Time Tomorrow, when
we talked to the Menlo Park fire chief. He explained
(28:43):
that the lower latency and higher bandwidth promised by future
five G networks could enable him to keep track of
his firefighters as they entered burning buildings, and that idea
of monitoring and optimization is exactly what Sean was talking about.
Personalization is such a key theme of the new economy,
and the personalization of products is something everyone can understand
(29:05):
fairly easily. But I love what Sean was talking about
in terms of personalizing worker responsibilities in a factory. To
make this vision real, though, factories and businesses will have
to adapt to become more agile. In Irian's words, well,
how will I get customized sucks otherwise. I think one
(29:26):
of the biggest takeaways that I learned while researching this
episode is that, well, we don't know exactly how things
will change. That there are too many technical and cultural
drivers converging for manufacturing to kind of stay as it
is today. Yeah, and whether it's the expansion of the
Internet of Things, or robotics or three D printing, industry
is becoming more digital and the new infrastructure of future
(29:49):
five gen networks could be the platform that digital future
is built upon. On the next episode of This Time Tomorrow,
we'll look how technology is changing one of the world's
oldest businesses, agriculture. From robots suerial imaging, we explore how
technology is changing the way we farm and the role
(30:11):
that five G could play. I'm as vlachen see you
next time. No matter what you're after, T Mobile for
Business is here with a network born mobile and built
from the ground up for the next wave of innovation,
from mobile broadband to IoT to workforce mobility, and everything
(30:35):
in between. T Mobile for Business is committed to helping
you move your business forward with the products and services
you need, as well as the dedicated, award winning customer
service you'd expect from America's most loved wireless company. Business
is changing. Learn more at T Mobile for Business dot com.
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