Data Collection
This topic has a brief overview and covers:
As with all major asset management improvement projects, it is important to continually refer back to the objectives or the purposes for which the work is being undertaken and the data collection phase is no exception to this rule.
In the overall sense, it is handy to return to the mission statement, which might be something like:
"To create, operate, maintain, renew, replace and dispose of our assets in a most cost effective manner to meet the required levels of service for present and future generations of customers/users and the community."
This mission statement ties together all the relevant elements that are essential to asset management such as:
- Efficiency and effectiveness needed to provide a cost effective service
- A customer service relationship in providing the level of service required by customers or ratepayers
- An inter-generational equity arrangement that ensures that both present and future generation meet their adequate costs of owning and operating these assets.
The degree of data required to complete asset management is a complex issue impacted on by:
- The type of asset
- The age and condition of the asset
- The criticality of the asset to the business or its owner
- The key business drivers or objectives of the organization.
The benefits that will be derived from having this data need to exceed the costs of collecting it and maintaining it.
There is an interrelationship between the benefits that will be derived and the costs of collecting this data, as shown below:
In general terms more detailed data can be justified for:
- Older assets and those that are in poor condition and have a high probability of failure
- Assets whose historical performance has shown them to be unreliable
- Assets whose failure has a high consequence to the business concerned
- Assets that have a high cost and benefits could be derived through optimized renewal investments.
- The level in the asset hierarchy that represents an individual maintenance managed item (MMI).
- The level at which we determine the individual maintenance managed items is the main driver in the cost of data capture.
- The lower this level is set in the hierarchy of assets will have considerable effect on the data capture cost.
This is shown below:
The detail of physical data collected on the asset, its condition and performance varies with the sophistication of the management of the asset.
The number of attributes that we wish to collect against each of the hierarchical levels and in particular against the maintenance management item will significantly impact on the cost of data capture.
Generally the types of attributes include:
- Asset identifier
- Base parameters
- Secondary parameters
- Tertiary parameters.
Organizations should determine the attributes they require at each hierarchical level, down to the maintenance managed item or component, and record these so that staff and data collectors can easily recognize the attributes required.
The accuracy or validity of the data collected will impact on the cost of data capture.
A major factor in the cost of data collection is the level of accuracy or validity that we require for the different attributes or data information.
In some cases accuracy may be critical to the way in which we operate, maintain or manage the asset; in others an appropriate estimate may be completely adequate.
The method of data capture is impacted on by the:
- Environment in which the asset exists e.g. visible and exposed or underground and hidden
- Type of asset e.g. electricity pole, water main, building asset
- Function for which the data is required e.g. asset identification, asset value, life cycle functions.
It may also be more cost effective to use specialized contractors for the data capture where the setting up and training factors are insignificant elements when compared to the use of in-house staff or untrained or inexperienced personnel.
The type of data that is required to be collected varies with the outputs or the life cycle functions that are going to be required.
The key functions that are necessary for advanced asset management include:
Identification
The organization needs to be able to say what they own and where it is located and this can involve both spatial or descriptive data.
Value and Costing of Assets
This information involves sufficient data from which an accurate replacement cost and written down value can be achieved. It includes sufficient general ledger linkages to enable costs to be recorded against an asset so that we can see the full ramifications of depreciation, operations and maintenance.
Maintenance Management
This involves the setting of planned maintenance procedures against the asset and all the associated data while undertaking a planned program including scheduling, time estimates etc. Unplanned data can be recorded as it occurs.
Job/Resource Management
The textural data generally involves key elements of time and scheduling for work, including planned maintenance together with the integration of any spares and materials that are required for the replacement or repair or maintenance of the asset.
Life Cycle Cost Analysis
Specialized data sets are required to enable the organization to properly manage the life cycle of the asset.
Prior to implementing the system a visit to a nearby utility is recommended to see what has been achieved and how the system has been installed. This will greatly reduce the learning curve.
Assess whether it is economic to manipulate data or transfer data onto input sheets, and then have the data typed into the computer. For example, with only 500 records the second option is preferable.
Decide on the scoring ratings, weightings and category ranges before starting the implementation. The weightings and category ranges can be amended once data input is completed.
A plan of the region should be created with the catchments placed on this plan for future reference.
List all assets owned or maintained. This will give you your basic checklists so that when data collection is completed you haven't missed anything. This may seem an obvious mistake but has occurred in the past.
Make a sub list of all components that are contained within those facilities. Visual inspection is also recommended at this stage on a representative sample.
A complete set of plans and records of each of the catchments should be kept in a central file.
Develop an asset numbering system that ensures each component has a unique number.
Document the asset numbering system that you propose to use with all its variations so that the user of the system can quickly and easily understand how it works. Typically this information should be summarized onto one page.
Develop a suitable list of abbreviations for asset type, asset finish and material type.
You will now need to determine a plan of attack for each individual catchment, which components to collect and in what order.
Prepare your data collection sheets by placing them on a clipboard or something similar so that the user when walking around can mark in the details. The data collection sheets should be set out in a format to match the order in which the data is required in the software system used. This will facilitate speedy data entry. Before starting the data collection you should also identify which particular asset details you will be collecting and which ones you will be leaving for a later date and also those ones that you will not be collecting at all.
Select a suitable pilot scheme to trial your data collection methodology. Typically this would be one catchment.
Based on the time taken to complete the pilot study and any subsequent modifications, you can now estimate how long it will take to complete the data collection exercise for the remainder of the assets. This will be useful for large numbers of assets, which may take a number of months or years to complete.
Once you have collected all the data and input it into your software system, analysis of that data can produce estimates for future cash flow requirements and problem assets that will require remedial works.
During the data collection exercise noting down of any assets that require backlog maintenance is recommended, as this will allow you to kill two birds with one stone. Recording of the assets' condition, whether as new or requiring renewal will also be of great benefit and will allow future cash flow requirements to be accurately predicted.
The lists of assets that come out of this data collection exercise will form an excellent base for developing up maintenance management practices.
During the data collection exercise it is recommended that the data collectors have periodic reviews. As organizations vary in length to complete the data collection these reviews are recommended at:
- pilot study completion
- 20% completion
- 40% completion
- 100% completion.
The amount of data to be collected will vary depending on the proposed use.
The table below presents the typical data requirements and some of the sources. Purpose 1 and 2 is usually the minimum information required to establish an effective asset management model.
Purpose |
Data Requirements |
Source of Information |
Compilation Plans of System |
Pit locations, pipe lengths, dia., material (pipes greater than 300 mm) |
Existing plans
Field staff knowledge
Field investigation |
“Age Profile” of System |
Year constructed (to nearest 10 years)
Replacement Cost |
Existing plans
When area developed
Local resident
Field staff knowledge
Recent construction works
Current cost estimate |
Hydraulic Modelling of System |
Invert levels, surface levels plus above information
Measured flows in system |
Existing plans, detail, survey
Photogrammetry and measured pit depths
Flow and flood level records |
Condition Assessment of System |
Defects compromising structural of functional integrity of system |
Visual inspection
CCTV inspection
Failures in system
Maintenance expenditure trends |
Level of Service |
History of complaints, maintenance requirements, flooding occurrences |
Complaints book
Maintenance staff and records
Local residents knowledge |
Risk Assessment |
Combination of all factors and damage assessment |
|
Additional (Extended Attribute) Database Field
Sewerage Reticulation U/S MH & Sewer
No. |
Description |
Entry Field |
Suggested Staged
Priority |
1 |
U/S Node (MH No) (Asset No) |
9999 (ii) |
1 |
2 |
D/S Node (MH No) |
9999 (ii) |
1 |
3 |
Invert Level U/S |
9999.99 |
3 |
4 |
Invert Level D/S |
9999.99 |
3 |
4 |
Cover Level U/S |
9999.99 |
3 |
6 |
Cover Level D/S |
9999.99 |
3 |
7 |
Depth U/S |
99.99 |
2 |
8 |
Length (m) |
999.9 |
1 |
9 |
Diameter Internal (mm) |
999 |
1 |
10 |
Diameter Ext. Collars (mm) |
999 |
3 |
11 |
Shape of Sewer |
A Code |
2 |
12 |
Material |
A Code |
2 |
13 |
Manufacturer |
A Code |
3 |
14 |
Joint Type/Ring Type |
A Code |
3 |
15 |
HC Points |
99 |
2 |
16 |
Properties Served |
99 |
2 |
17 |
Properties Connected |
99 |
2 |
18 |
Equivalent Domestic Connections (EC) |
999 |
2 |
19 |
Replacement Cost $/M |
999 |
1 |
20 |
Roughness Coefficient |
99 |
3 |
21 |
U/S Manhole Type (Brick) etc |
A Code |
3 |
22 |
U/S Manhole Shape |
A Code |
3 |
23 |
U/S Manhole Type of Cover |
A Code |
3 |
24 |
Step Irons Y/N |
A Code |
3 |
25 |
Drop Structures |
(2) No |
3 |
26 |
Code for additional data files |
A Code |
3 |
Sewerage Pumping Stations Data Collection (Macro Level)
Location Sewerage P/Stn |
Building |
Structure |
Substructure |
Ventilation |
Ligating |
Fire |
Access Stairs |
Services |
Power Supply |
Water Supply |
Electrical |
Switchboards |
Control |
Control Plant |
Instrumentation |
Level indicators |
Data Monitoring |
Lifting Devices |
Block & Tackle |
Monorail |
Pumps |
Motors |
Telemetry |
Plumbing |
Others |
|
|
|
|
Data Collected |
|
Data Checked |
|
Data Input |
Asset attribute
Overall Listing |
Priority |
Description |
Asset Identifiers |
1 |
Allows system to become operational |
Base Parameters |
2 |
Allows initial age profile, valuations, depreciation (straight line), simple works program to be developed |
Secondary Parameters |
3 |
Allows assets to be classified and broken into categories for sampling and initial analysis. TAMP (3) and (4) production possible |
Tertiary Parameters |
4 |
Allows detailed analysis and TAMP (5) production to be undertaken |
Data capture priorities ("generic assets")
Parameters |
Description |
Priority |
Asset Identifiers |
|
|
Asset number |
Corporate identifier, linked to other corporate systems |
1 |
Other identifiers |
Locaters, functional descriptors |
1 |
Asset descriptor |
Textural entry to ensure ambiguity |
1 |
Base Parameters |
|
|
Capacity characteristics |
Planning information defining service limit |
2 |
Size characteristics |
Includes dimensions, length |
2 |
Material characteristics |
Base material used in asset |
2 |
Replacement schedule ($/m etc.) |
Rate for determination of replacement cost, depreciated value |
2 |
Date of construction |
Determinant of current life consumed |
2 |
Estimate of effective life |
Total life for depreciation purposes |
2 |
Replacement cost |
Current cost to replace the asset described |
2 |
Other information |
More detailed than priority 1 data e.g. model numbers etc. |
2 |
Secondary Parameters |
|
|
Condition data |
Information used to prepare decay curves, revision of effective life and current valuation |
3 |
Performance data |
Information recording capacity performance. All unplanned maintenance activity is recorded against MMI including cause and costs. Planned maintenance procedures adopted for critical assets. |
3 |
Enhanced data |
Verified and upgraded base parameter data |
3 |
Component or subsystem details |
Allows evaluation of assets by aggregation of information. eg. valuation of components aggregated to asset level |
3 |
Tertiary Parameters |
|
|
Consequence of failure items
and risk exposure |
Information which assists in the identification of consequence of failure e.g. number of properties connected; availability of redundancy; probability of failure |
4 |
Items that allow modeling
of capacity/utilization failures |
Information, which assists in modeling variation for asset capacity performance e.g. friction coefficients (network models), road width and number of lanes (traffic models) |
4 |
Items assisting maintenance activities |
Information, which contributes to better maintenance performance eg. Information necessary for RCM (failure modes, effects and criticality analysis |
4 |
Additional asset information |
Information which will help individualize this asset from similar assets |
4 |
Job/resource data |
Allocate resources to asset activities |
4 |