How manufacturers can unlock new value from existing data
In
an
industry
buffeted
by
constant
pressure
on
margins,
shifting
trade
patterns,
and
supply
chain
uncertainty,
manufacturing
companies
are
looking
for
any
edge
they
can
get.
The
good
news?
It
can
often
be
found
in
innovative
uses
of
data.
In
an
industry
buffeted
by
constant
pressure
on
margins,
shifting
trade
patterns,
and
supply
chain
uncertainty,
manufacturing
companies
are
looking
for
any
edge
they
can
get.
The
good
news?
It
can
often
be
found
in
innovative
uses
of
data.
Here’s
how
manufacturers
can
harness
data
analytics
to
improve
performance
across
three
critical
areas
of
their
businesses.
-
Reduced
downtime
Factories
generate
enormous
amounts
of
data
from
sensors,
controllers,
and
other
assembly
line
equipment
–
but
that
data
is
typically
thrown
away
or
readily
available
if
it
doesn’t
indicate
an
immediate
problem.
When
combined
and
analyzed
over
time,
however,
it
can
be
a
treasure
trove
of
operational
savings.
Predictive
or
condition-based
maintenance
uses
historical
data
about
equipment
performance
to
predict
the
likelihood
of
future
failures.
Downtime
costs
manufacturers
billions
of
dollars
per
year,
yet
recent
studies
have
found
that
many
companies
don’t
have
formal
systems
for
tracking
equipment
maintenance
or
replacement
schedules.
Predictive
maintenance
saves
money
in
two
ways:
-
It
uses
sensor
data
to
monitor
for
conditions
that
indicate
that
equipment
is
going
to
fail,
such
as
excessive
vibration
or
heat. -
Analytics
can
also
look
across
past
or
similar
situations
to
pinpoint
when
equipment
is
in
perfect
health
and
doesn’t
need
scheduled
maintenance.
Top-tier
automotive
supplier
Faurecia
built
an
enterprise
data
hub
to
bring
together
data
from
thousands
of
machines
and
millions
of
sensors
to
enable
it
to
perform
predictive
maintenance
and
improve
product
quality.
The
company
can
now
spot
quality
issues
early,
reduce
unnecessary
labor
and
material
costs,
and
improve
customer
satisfaction.
What’s
more,
data
analytics
is
moving
Faurecia
closer
to
its
goal
of
zero
defects.
“If
you’re
a
logistics
company,
the
last
thing
you
want
is
to
have
delivery
vehicles
go
out
of
commission,”
said
Cindy
Maike,
Vice
President
of
Business
and
Product
Solutions
at
Cloudera.
“Sensors
on
vehicles
information
back
to
the
fleet
management
group
indicating
the
performance
of
various
component
parts
to
determine
either
early
warning
indicators
or
overall
performance.
These
signals,
along
with
past
service,
are
used
to
help
avoid
downtimes.”
-
Enhanced
customer
engagement
The
data
a
manufacturing
company
collects
about
its
products
in
the
field
can
fortify
relationships
with
customers
and
channel
partners.
For
example,
a
maker
of
factory
equipment
can
harvest
sensor
data
to
predict
failures
and
alert
customers
to
the
need
for
preventive
maintenance.
Software
updates
delivered
over
the
air
can
save
buyers
of
cars,
security
cameras,
and
other
smart
devices
from
having
to
make
time-consuming
trips
to
a
dealer.
Vodafone
Automotive
developed
an
innovative
program
to
help
insurance
companies
tailor
policies
more
precisely.
It
equips
fleet
vehicles
with
a
device
that
collects
data
about
vehicle
location,
speed,
and
acceleration.
It
then
translates
that
information
into
driver
profiles
that
insurance
companies
can
use
to
tailor
policies
and
save
their
customers
money.
The
company’s
data
fabric
has
also
laid
the
foundation
for
real-time
services
to
improve
driver
safety
as
well
as
drive
maintenance
efficiency
for
vehicles
in
the
field.
-
Improved
safety
and
compliance
Manufacturers
in
fields
like
pharmaceuticals
and
food
are
keenly
aware
of
the
need
to
keep
their
customers
safe.
Quality
problems
that
go
undetected
can
have
consequences
that
not
only
threaten
public
health
but
can
incur
large
regulatory
penalties.
“If
you’re
a
pharmaceutical
manufacturer,
you
need
to
have
the
right
security,
governance,
and
data
lineage
tracking
to
take
a
drug
to
market,”
Maike
said.
“Everything
from
R&D
to
clinical
trials
to
yield
optimization
needs
to
be
tracked.”
Sensors
can
be
employed
to
monitor
product
status
and
quality
throughout
the
supply
chain.
For
example,
a
maker
of
perishable
foods
can
use
smart
thermometers
to
ensure
that
its
products
are
never
exposed
to
unsafe
temperatures.
Quest
Diagnostics
built
a
big
data
platform
to
store
the
results
of
more
than
20
billion
lab
tests
conducted
over
the
past
decade.
Quest
combines
its
data
with
other
unstructured
and
structured
sources
to
derive
new
clinical
insights
that
improve
operational
efficiency,
enrich
clinical
reporting,
and
support
the
growing
need
to
manage
population
health
and
lab
utilization.
With
the
right
data
management
platform,
manufacturers
can
unlock
new
sources
of
value.
Visit
Cloudera
to
learn
more.
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