Merging top-down and bottom-up planning approaches

This
blog
series
discusses
the
complex
tasks
energy
utility
companies
face
as
they
shift
to
holistic
grid
asset
management
to
manage
through
the

energy
transition
.
The
first
post
of
this
series
addressed
the
challenges
of
the
energy
transition
with
holistic
grid
asset
management.
The
second
post
in
this
series
addressed
the
integrated
asset
management
platform
and
data
exchange
that
unite
business
disciplines
in
different
domains
in
one
network.

Breaking
down
traditional
silos

Many
utility
asset
management
organizations
work
in
silos.
A
holistic
approach
that
combines
the
siloed
processes
and
integrates
various
planning
management
systems
provides
optimization
opportunities
on
three
levels:

  1. Asset
    portfolio
    (AIP)
    level:
    Optimum
    project
    execution
    schedule
  2. Asset
    (APMO)
    level:
    Optimum
    maintenance
    and
    replacement
    timing
  3. Spare
    part
    (MRO)
    level:
    Optimum
    spare
    parts
    holding
    level

The
combined
planning
exercises
produce
budgets
for
capital
expenditures
(CapEx)
and
operating
expenses
(OpEx),
and
set
minimum
requirements
for
grid
outages
for
the
upcoming
planning
period,
as
shown
in
the
following
figure:

Asset
investments
are
typically
part
of
a
grid
planning
department,
which
considers
expansions,
load
studies,
new
customers
and
long-term
grid
requirements.
Asset
investment
planning
(AIP)
tools
bring
value
in
optimizing
various,
sometimes
conflicting,
value
drivers.
They
combine
new
asset
investments
with
existing
asset
replacements.
However,
they
follow
different
approaches
to
risk
management
by
using
a
risk
matrix
to
assess
risk
at
the
start
of
an
optimization
cycle.
This
top-down
process
is
effective
for
new
assets
since
no
information
about
the
assets
is
available.
For
existing
assets,
a
more
accurate
bottom-up
risk
approach
is
available
from
the
continuous
health
monitoring
process.
This
process
calculates
the
health
index
and
the
effective
age
based
on
the
asset’s
specific
degradation
curves.
Dynamic
health
monitoring
provides
up-to-date
risk
data
and
accurate
replacement
timing,
as
opposed
to
the
static
approach
used
for
AIP.
Combining
the
asset
performance
management
and
optimization
(APMO)
and
AIP
processes
uses
this
enhanced
estimation
data
to
optimize
in
real
time.

Maintenance
and
project
planning
take
place
in
operations
departments.
The
APMO
process
generates
an
optimized
work
schedule
for
maintenance
tasks
over
a
project
period
and
calculates
the
optimum
replacement
moment
for
an
existing
asset
at
the
end
of
its
lifetime.
The
maintenance
management
and
project
planning
systems
load
these
tasks
for
execution
by
field
service
departments.

On
the
maintenance
repair
and
overhaul
(MRO)
side,
spare
part
optimization
is
linked
to
asset
criticality.
Failure
mode
and
effect
analysis
(FMEA)
defines
maintenance
strategies
and
associated
spare
holding
strategies.
The
main
parameters
are
optimizing
for
stock
value,
asset
criticality
and
spare
part
ordering
lead
times.

Traditional
planning
processes
focus
on
disparate
planning
cycles
for
new
and
existing
assets
in
a
top-down
versus
bottom-up
asset
planning
approach.
This
approach
leads
to
suboptimization.
An
integrated
planning
process
breaks
down
the
departmental
silos
with
optimization
engines
at
three
levels.
Optimized
planning
results
in
lower
outages
and
system
downtime,
and
it
increases
the
efficient
use
of
scarce
resources
and
budget.

Read
more
about
IBM®
Maximo®
APM
for
Energy
and
Utilities

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