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 coefficients:

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

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.