| Product(s): | WaterSight |
| Version(s): | 10.00. |
| Area: | Documentation |
Overview
The first step when calculating likelihood of failure (LOF) or consequence of failure (COF) involves the user defining which are the key criteria or aspects that can drive both LOF and COF, taking into consideration both the data available as well the specific context of the utility and the region. Some common aspects amongst water utilities that can drive LOF can include for example pipes age, material, break history, etc. Some common aspects that can drive COF can include for example number of affected customers, proximity to main roads, repair costs, etc. Nevertheless, the user is able to create any aspect he finds relevant for the analysis.
There are two different methods available for creating aspects or consequences:
- Through a new Decision Tree
- Through a new Predefined Aspect or Consequence (this page)
The main goal of the predefined aspect is to give the user an option to quickly, easily and in a simple way create aspects. The scores can be still completely user driven (as in the decision tree method) or the user can rely on the data driven approach to have the scores being automatically calculated by the solution.
Creating or Editing a Predefined Aspect
To create a new pre-defined aspect or consequence, the user should click on the “New” button >> Predefined, located in the top of the Likelihood of Failure or Consequence of Failure page.
Once clicking on New > Predefined, a pop-up dialog will appear in order to configure several fields.
To edit an existent predefined aspect, just click on the more button (...) located in the aspect tile listed under the Aspects section on the Likelihood or Consequence of Failure pages. From there click "Edit Logic". A pop-up dialog will appear in order to configure several fields.
Name
Name given to the Predefined. The name should be as much intuitive as possible, as it will be used in the rest of the application to identify the created aspects or consequences.
Add Condition
The user defines which is the property (or column) of the pipe shapefile for which results will be calculated. The user can choose any property that exists in the pipe shapefile. Some examples of properties can be Material, Age, break rate, diameter, length, etc.
Score Type
User can select continuous score or discrete score.
If continuous score is defined, scores for each pipe will be automatically calculated by the software using linear interpolation method. If discrete is defined, user will define the scores that will be the same for the user defined range of values. More information below.
Continuous vs Discrete Score
Continuous score only applies to property fields that are numeric type. The intent is that the individual scores for each pipe are on a scale of 0 to 100 (100 being the worst). The user needs to define the minimum and maximum values as well their respective scores. After those extreme points are defined, scores for all other values are linearly interpolated between the minimum and maximum defined.
This approach can be successfully used for most numeric field properties such as (but not limited to):
- pipe age: older pipes usually tend to break more than new pipes;
- break rate: pipes with higher break rates tend to break more than pipes with lower break rates;
- customers affected: pipes that affect a higher number of customers when they are closed cause a higher impact or consequence than pipes that affect few or no customers at all;
- diameter: pipes with bigger diameter usually tend to cause more impact than smaller pipes when they fail (customers affected, potential flooding, repair costs, etc)
Discrete score can be applied to numeric or string (text) property fields and it uses a stepwise scale, from 0 to 100 (100 being the worst) where the steps (range of values) as well as respective scores are defined by the user. Please note that in case the property field is a string (text) only Discrete type score is available.
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Continuous Score | Discrete Score |
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Continuous Score: Extreme Values Method
When selecting Continuous Score, the user needs to define how he wants the extreme values to be calculated:
Absolute Method
Minimum and maximum absolute values are automatically calculated by the software from the full range of values contained inside the property chosen by the user (in Add Condition). For those minimum and maximum absolute values the user needs to define a score. Scores for all other values are then linearly interpolated.
Most of the times the logic is that higher values are worst meaning higher score (for example pipe age, break rate, pressure, etc) however user can also score lower values as being worst (for example very low velocities can induce water quality issues).
Percentiles Method
Statistical analysis is used to automatically calculate the maximum value and minimum value using the percentile 95 and 5 calculated from the full range of values contained inside the property chosen by the user (in Add Condition).
For those minimum and maximum values, the user needs to define a score. Scores for all other values between min and max are then linearly interpolated. Values below the minimum value defined (percentile 5) will share the same score as the minimum value. Values above the maximum value defined (percentile 95) will share the same score as the maximum value.
Most of the times the logic is that higher values are worst meaning higher score (for example pipe age, break rate, pressure, etc) however user can also score lower values as being worst (for example low velocities can also induce water quality issues).
Percentile method corresponds to the default one when selecting continuous score and it’s demonstrated to be, most of the time, the most appropriate method due to the usual large disparity of the usual values associated with the chosen property. For example, one single outlier value (that can represent wrong/bad data, or even a correct value but that only happened once, representing an outlier that should be ignored) can influence all the scores given to the other values if the Absolute Method approach is used. For more information about when to use percentiles method and the difference to the absolute method, please take a look at this article: Prioritizing pipes using data driven methods.
Custom Method
When using the custom method, the user can define both the minimum and maximum values as well as the respective score.
For those minimum and maximum user defined values the user needs also to define a score. Scores for all other values between min and max are then linearly interpolated. Values below the minimum user defined value will share the same score as the minimum value. Values above the maximum user defined value will share the same score as the maximum value.
Discrete Score
As mentioned above, discrete score uses a stepwise scale, from 0 to 100 (100 being the worst) where the steps (range of values) as well as respective scores are defined by the user. It can be applied to both numeric and string (text) property fields. Please note that in case the property field is a string (text) only Discrete type score is available.
| Discrete score for numeric type field | Discrete Score for string type field |
Save and Close
Clicking save button below will automatically save the predefined aspect and close the pop-up dialog. The recently saved predefined aspect will then appear listed under the Aspects or Consequences Section, inside the Likelihood or Consequence of Failure page.
By clicking close, any change to the predefined is discarded and does not get saved, and the predefined pop-up dialog immediately closes.
Combining Different Predefined Aspects
Predefined aspects can be combined together, and the user can give each aspect a different weight, by creating a new cumulative. More information here.