Asset Management and Condition Index


Here is an example of getting to a condition assessment with limited data using power point slides.  Note that where there are categorical variables (type of pipe for example), these need to be converted to separate yes/no questions as mixing.  Categorical and numerical variable do not provide appropriate comparisons = hence the need to alter.  Take a look – but the concept is to predict how well this model explains the break history on this distribution system.  Call me and we can try it on yours….

Step 1  Create a table of assets (this is a small piece of a much larger table).

Asset Dia
water main 2
water main 2
water main 2
water main 2
water main 4
water main 6
water main 6
water main 6
water main 6

 

Step 2  Create columns for the variables for which you have data (age, material, soil type, groundwater level, depth, traffic, trees, etc.)

 

Asset breaks in 10 year Dia Age soil traffic Trees depth pressure material Filed estimate of cond.ition
water main 17 2 45 1 1 2 1 55 4 3
water main 11 2 45 2 1 2 1 55 4 3
water main 12 2 45 1 1 2 1 55 4 3
water main 10 2 45 1 1 2 1 55 4 3
water main 2 4 50 1 1 2 1 55 1 2
water main 3 6 60 2 2 2 1 55 1 2
water main 1 6 60 2 2 2 1 55 1 2
water main 1 6 60 2 2 2 1 55 1 2
water main 0 6 20 1 1 2 1 55 3 1

 

Step 3  All variables should be numeric.  So descriptive variables like pipe material need to be converted to binary form – i.e. create a column for each material and insert a 1 or 0 for “yes” and “no.”

Step 4 Run Linear regression to determine factors associated with each and the amount of influence that each exerts.  The result will give you a series of coefficientcoefs:

Step 5 – Use this to predict where your breaks will likely be in the next 5-10 years.

Pred breaks

The process is time consuming but provides useful information on the system.  It needs to be kept up as things change, but exact data is not really needed.  And none of this requires destructive testing.  Not bad for having no information.

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