North American Special - Trenchless International

Risky business
by Roderick Lovely
asset management
April 2009 - Trenchless International
1%
20%
36%
3%
Total miles of pipe by material
9%
52%
3%
Managing assets
in Las Vegas
Trenchless Technology contributes substantially to asset management across the world. Charles Scott
from the Las Vegas Valley Water Department spoke with Trenchless International about their asset
management program.
Las Vegas is the most populous
city in the USA state of Nevada. The
Las Vegas Valley, a 600 square mile
(1600 km²) basin and surrounding area, is
part of Clark County in southern Nevada.
Mr Scott says the Las Vegas Valley
Water District (LVVWD) is responsible for
over 4,500 miles of pipe in Las Vegas and
unincorporated Clark County. Mr Scott
says “We also manage over 100 miles of
pipe in separate small water systems in
the communities of Jean, Searchlight, Blue
Diamond, Laughlin, and Kyle canyon.”
The breakdown of total miles of pipe by
material is shown below.
The largest steel pipe, including mortar
lined steel pipe, bar wrapped steel pipe
and pre-tensioned wire wrapped pipe is
102 inches in diameter. Most pipe in this
class ranges from 24-48 inches in diameter.
PVC pipe ranges from 4 inches up
to 42 inches and ACP from 4 inches to
60 inches. Most PVC and ACP pipe are
from 6 – 8 inches.
Mr Scott says that because of Las Vegas’
phenomenal population growth over the
past ten years, the average age of all pipes
in the distribution system is only about 18
years. The average age for PVC pipe is
eight years compared to ACP, which has
an average age of between 29 and 34
years.
ACP has the highest break rate per mile
compared with all other pipe materials.
When asked what portion of assets the
LVVWD inspects every year, Mr Scott says
they are currently focusing assessment
activities on ACP and steel pipe. “For ACP,
our assessments are prioritised based on
our CARE-W [computer aided rehabilitation
of water networks] model that ranks pipe in
terms of risk of failure – based on statistical
failure modelling and hydraulic criticality –
based on hydraulic modelling tool re-net.
Asbestos cement
Cast Iron
Unknown
Ductile iron
PVC
Polyethylene
Mortar lined steel
“We also try to employ the
best available technology
and use non-invasive
techniques as much as
possible.”
“Other criteria such as impact to customers,
potential damage to rods and
types of customer served are also important
considerations,” says Mr Scott.
For steel, the LVVWD assessments are
prioritised based on corrosion potential
information collected from the Cathodic
Protection system, as well as the potential
consequences of failure, impact to customers
and break history.
“We have just this year implemented
our CARE-W model, and have started a
full-blown assessment program,” says Mr
Scott. “This year we will assess approximately
10 miles of ACP, and from 10 up to
15 miles of steel pipe.”
Mr Scott says that the total amount of
ACP to be assessed each year will vary
depending on the output of the model. The
LVVWD plans on assessing approximately
20 miles of steel pipe annually.
Trenchless International asked if the
District has adequate funding to conduct
the inspection and repair programs. Mr
Scott answered “Funding is a challenge
for all utilities, this is why we are careful to
assess only those pipes at the most risk.”
The LVVWD is just beginning to investigate
the advantages of Trenchless
Technology following a successful CIPP
project. The District will be evaluating the
applicability of Trenchless solutions on a
case by case basis.
Quantifying risk is fundamental to any physical asset management program, the following article
presents how this information can be obtained and used to assess risk.
Water and wastewater infrastructure
managers make decisions every day
that are aimed at reducing the risk of costly
failures. For most, the decision process is
ingrained, based on years of experience
and knowledge in system management.
But over time systems change, people
retire, the knowledge base is lost, assets
age, and the probability of costly failures
increases. This is especially true in
developed countries where underground
utilities have been in place for over a hundred
years, and the people who manage
them are nearing retirement.
As a new generation of managers
emerges, they are being asked to manage
assets that are nearing the end of
their useful life with fewer resources, and
tougher regulatory requirements, such as
California’s Sanitary Sewer Management
Plan, or SSMP. To cope with these challenges,
savvy managers are turning to
computer applications with physical asset
management (PAM) features to allocate
limited resources more strategically.
Fundamental to PAM is prioritisation of
assets based on a risk model. At a minimum,
this involves knowing how assets
might fail and what would happen if a
failure were to occur. In PAM we define
‘how assets might fail’ as the probability
of failure (PoF) and ‘what would happen a
failure were to occur’ as the consequence
of failure (CoF). Risk is simply the product
the PoF and CoF:
Risk = PoF x CoF.
Probability of failure
To determine the PoF of any asset we
must first determine how it may fail in terms
of failure modes. When we categorise how
an asset may fail there are at least four
failure modes to consider that are common
to all assets.
Condition
Condition may be put in terms of a
Condition Rating by quantifying the number
and extents of defects, or by direct measures
such as a vibration analysis. It may be
helpful to measure condition in both O&M
Condition and Physical Condition. O&M
Condition can be addressed through tasks
such as cleaning and lubrication, while
Physical Condition may call for capital remedies
such as overhaul and replacement.
Probability
What it means
100 per cent Failure likely to occur within a year
90
90 per cent chance of Failure in any year – Failure likely within 2
years
50 50 per cent chance of Failure within any year
20 20 per cent chance of Failure within any year
10
2
10 per cent chance of Failure within any year – 90 per cent
chance it won’t
2 per cent chance of Failure within any year - 98 per cent
chance it won’t
Age
For age to have meaning we must
first determine the life expectancy of any
asset. Life expectancy can be influenced
by many factors such as the surrounding
environment, construction material, and
installation techniques. Although age is
often a good predictor of condition, an
asset that appears to be in good condition
may start to deteriorate rapidly or suddenly
fail as it approaches the end of its
useful life. Knowing how close your assets
are to the end of their life expectancy may
influence how often you inspect them or
how you develop a replacement strategy
to avoid costly failures.
Capacity
Does the demand placed on the asset
exceed its original design capacity
Influences such as population increases
can certainly affect capacity. You must
know what the demands are on your
assets to measure capacity. Bear in mind
that assets that are substantially underutilised
could also lead to a higher PoF.
Level of Service
Perhaps the asset was put into place
before new regulatory requirements were
enacted. Stakeholder expectations for
issues such as noise, odour, and safety
may be more stringent now. Or it may
be that newer alternatives have been
developed that reduce the cost of operation
to the point that it will be less costly
to replace than to continue to operate.
Establishing acceptable levels of service
will help you make these determinations.
Your actual list of failure modes will vary
depending on the asset types that you
are rating, but they will all most likely fall
into one of these four categories. As you
develop your criteria, take into account
that ‘failure’ does not always mean a
catastrophic failure, but it does mean that
continuing to operate the asset without
taking action will be more costly than
doing something about it.
Quantifying probability of failure
When it comes to age, we humans
inherently know that the probability of end
of life increases as we grow older, and that
probability increases at an accelerating
rate. However, we have no way of determining
precisely when the end will occur.
The same is true for physical assets. But
what we can do is apply a probability
based on experience and historical data
when available. Below is a sample table
that shows how one might interpret levels
of probability in a risk model.
For the failure mode of age, the graph
for static assets such as pipes and manholes
where failure rarely occurs early in
life can be illustrated in an age based
curve.
Mechanical and electrical assets are
more prone to failures early in life and
hence the probability of failure curve
associated with these types of assets is
often referred to as a ‘bathtub’ curve.
If reliable historical data is available
then the PoF should be based on the percentage
of failures actually experienced.
Similar curves can be created for other
failure modes such as capacity where
asset management
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