[With the Factory Information System]
were also actually going from a segment-based or major element- or line-based data
flow to being able to look at an individual
piece of machine-level data. Data on a robot, for example, moves to a programmable
logic controller, to an application server,
and then to the end user. We actually measure and have analytics and data flow and
visibility on all the individual steps that a
robot takes. It streamlines our maintenance system and increases our uptime
throughput because, if that robot begins
to slow down, we can measure the lulls, we
can see the specific steps, and we can use
[the data] to increase our predictive maintenance and to move data much faster, in a
condensed and cleansed manner, to people
that can take business actions and make decisions. It’s really, really powerful.
The next example I wanted to share
is around quality. All of our assemblies
now have birth codes, they have part
traceability, they have torque scans or
torque traces, really a birthing document.
This gives us the capability to understand
what the [torque] level of an individual
part or a sub-assembly is across the world.
The power of the data is it comes organized, it comes fast, it comes immediate.
As we move to analytics, it comes with
recommended behaviors on what the ap-
propriate adjustment is in the manufac-
turing process, up to and including having
the recommended behavior transferred
to the controllable logic of the equipment
and doing the adjustments without hav-
ing human intervention.
Another example is in freight and customs, and duty. We’re spending a lot of time
in this space, because a lot of costs in the
business are here, particularly as we move to
global platforms and export centers in our
low-cost manufacturing sites. The Internet
of Things really enables us to lean out the
supply chain. Weusedata analyticstoreally
optimize our freight and customs processes
[such as] route selection.
What’s really cool and different in this
space is we’re moving to what I call “
dynamic material flow,” on both inbound
material to our plants and outbound completed goods to our customers. [This approach recognizes that] the world always
has events that go on. The nature of this
business is you’re often required to make
changes and continue to move your goods.
In the past, as an industry, we’ve been too
quick to pay the cost penalties associated
with those late changes. Now we’re bringing data sense and analytics in to help us
recommend the lowest-cost solution when
we have to make an adjustment.
Another example is a little closer to
the plant. It’s around flexibility. We call
it “mixed model flexibility,” which is basically a batch of one. For many of our
manufacturing sites – take an F-150
plant, for example – our gross volume is
“When I visit
a plant and I
go to a ne w line
or a line we’re
launching, I of-
ten find myself
standing at a
laptop or hold-
ing an iPad,
live-looking
at the data
system. We re-
ally believe it’s
important for
our competi-
tiveness.”
— BRUCE HE TTLE
.................... .................... .................... ................... .................... .................... ....................
“[We] spend a whole lot of time
now thinking ‘What’s next?’
For us, it’s clearly the expansion
of data and the availability of data.”
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— BRUCE HETTLE
