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Shifting from a Reactive Approach to Proactive Planning: Asset Management for an Aging Treatment Facility


*Jessica Brown, P.E., Freese and Nichols, Inc., (817) 312-6980; [email protected]

ABSTRACT The City of Arlington maintains two treatment plant facilities with a total estimated treatment capacity of 202.5 MGD. The historical approach to asset maintenance at each plant has typically been reactive in nature, but as these facilities have continued to age, the City determined that a more proactive approach was needed for maintaining facilities going forward. The City had collected a lot of data over time but did not have a comprehensive program to leverage this data and maximize maintenance and renewal CIP dollars. The first step was to develop an overall Asset Management Implementation Plan for all facilities which included evaluation of the GIS and CMMS programs and how these systems could be utilized into developing an overall program. The key to the Asset Management Implementation Plan was that it had to be applicable at the treatment plants, pump stations and storage facilities. The second step was to apply this asset management approach to the oldest facility, the Pierce-Burch Water Treatment Plant. The Pierce-Burch Water Treatment Plant was originally constructed in 1956 and expanded and renovated multiple times over the past 50+ years. There is not presently any comprehensive mapping or GIS of the plant infrastructure and piping, instead relying on institutional knowledge and multiple sets of plans. As a result of this asset management approach, the first phase of the implementation plan accomplished developing a GIS of all of the yard piping, clearwells, pump stations and raw water facilities; an updated CMMS that links with the GIS and captures data needed to do trend analysis, provide input to the risk based assessment for the renewal CIP and reduce life cycle costs through increased preventive maintenance activities; and a risk based renewal CIP for buried assets and pumping and storage facilities. This paper will discuss how the overall asset management program was developed through gap analysis of existing systems, business process evaluation and workshops with City staff, along with the full implementation of Phase 1 at the Pierce-Burch WTP from the GIS development through the renewal CIP development.

INTRODUCTION An overall Asset Management Implementation Plan was developed for the City of Arlington for its facilities. The purpose of the plan was to provide Arlington Water Utilities (AWU) staff with a guide to implement asset management across all of the facilities using the work currently being done as a part of Phase 1 of the Pierce-Burch WTP asset management program as a guide. The capacity of the Pierce-Burch WTP is 75 MGD. Phase 1 of the facility asset management program focuses on the Pierce-Burch Water Treatment Plant (WTP) and consists of the following above ground facility assets: Clearwells 1 through 6, the raw water pump station, raw water pumps, high service pump stations, and high service pumps. In addition to the above ground facility assets, Phase 1 also includes the following buried assets: yard piping, raw water piping, valves, manholes, meters, and vaults. The Asset Management Implementation Plan consisted of six components:

Gap Analysis

Asset Inventory

Risk Based Assessment

Key Performance Indicators

Optimize Capital and O&M Investments

Implementation Schedule The drivers for starting at the Pierce-Burch WTP were that no comprehensive mapping existed, significant portions of the WTP were over 40 years old, and the work order system for facilities wasn’t being used to make rehabilitation/renewal decisions. AWU has had a successful rehabilitation/renewal program implemented in the distribution and collections systems for several years.


METHODOLOGY Gap Analysis The first component of the Asset Management Implementation Plan was to perform a gap analysis, both on data and processes. The gap analysis included reviewing available asset data, modifications needed to the data, and the structure of systems used to manage asset data, such as the Computerized Maintenance Management System (CMMS) and Geographical Information System (GIS), to identify enhancements required to facilitate implementation of the asset management program. AWU had historically utilized the Maximo work order system to track corrective and preventive maintenance at facilities, such as WTPs, booster pump stations, and elevated storage tanks. As part of the asset management plan, AWU migrated to the Cartegraph work order system software used by the City’s Public Works Department to better manage facility assets. FNI performed a detailed gap analysis on the existing Pierce-Burch WTP asset data including the work order system used to track maintenance performance of assets at the plant. Asset Inventory The asset registry specifies how the asset inventory will be organized and structured. This is an important component of the asset inventory for the GIS and CMMS systems integration. The asset registry also specifies what asset data will be stored in either the GIS or CMMS database. Through the analysis of the existing GIS geodatabase structure, it was determined that the overall structure of the existing feature classes would be used for facility assets. Additional feature classes and sub types were added to represent the different asset types found at a water treatment plant or pump station. Several options were analyzed to incorporate facility assets into the existing water and wastewater datasets, including adding new feature classes for facility assets and expanding the subtypes in the existing feature classes. Maintaining security of facility assets was paramount to consider, with WIS setting permissions to control access to facility GIS data within the City. A separate dataset with the same structure as the existing water dataset was created within the existing GIS geodatabase. A separate dataset for facility assets allows AWU to restrict access to facility data separately from the water and sewer datasets. This option has a minimal impact on the users of the existing water and sewer dataset during the testing and rollout phase of the asset inventory. The final component of the asset registry was to determine what asset data would be stored in the GIS geodatabase and what would be stored in the CMMS database. The fields captured in the GIS geodatabase include primarily physical attributes that do not change over time. The CMMS database pulls asset data from the GIS and includes additional information on those assets, such as O&M manuals. The CMMS database breaks down each asset further into components, such as electrical components, and subcomponents, such as a motor or impeller for a pump, that link back to GIS assets using the unique identifier. Figure 1 illustrates an example of the asset hierarchy. Assets owned and maintained in the GIS geodatabase are highlighted red, and assets maintained in the CMMS database are highlighted green. Assets shown in red are also included in the CMMS but will pull the information from GIS.


Figure 1: Sample Asset Registry for the Pierce-Burch WTP Facilities

GIS Geodatabase The GIS geodatabase structure was developed by FNI based on the existing WIS geodatabase. The hierarchy and naming convention of the geodatabase were developed and reviewed with AWU staff through a series of meetings and workshops. The as-built plans used to attribute a facility asset were hyperlinked to the asset in the GIS geodatabase. The asset hierarchy was based on the existing water dataset and modified to include facility assets. This allows WIS to easily expand the dataset using business processes already in place. Figure 2 illustrates the hierarchy of the asset in the GIS geodatabase. The existing unique ID structure was expanded to include WTP location as an option. Assets at pump stations in the distribution system will still follow the existing unique ID naming convention.

Figure 2: GIS Geodatabase Hierarchy

Yard piping at WTP facilities, with the exception of chemical lines, are captured in the Waterlines feature class. The water line feature class contains several subtypes organizing water line assets by flow stream, so a standardized naming convention was developed to be used across all WTP facilities.


Risk Based Assessment Once a utility knows what assets it owns, the next questions to arise are what condition those assets are in, how critical each asset is to the overall operation, and what assets expose the utility to the most risk. The risk based assessment is a straightforward approach to answering these questions and laying the ground work to make educated capital and O&M investments. The risk based assessment consists of three components: condition, criticality, and risk assessments of both buried and above ground assets. The condition assessment component consists of defining scoring parameters and the weighting for each one to develop a condition score for each asset. The criticality assessment component consists of defining scoring parameters and the weighting for each one to develop a criticality score for each asset. Both the condition and the criticality scores are combined to develop an overall risk based score for each asset. Assets can be ranked by the overall risk based score to develop business cases for capital and O&M investment decisions. The risk based assessment for buried assets was originally developed based on assumed condition; however, the weighting between assumed condition data and actual condition data will change over the next five years was AWU collects work order data. The condition parameters for pipelines included pipe age and material, with a placeholder for pipe repairs from the work order database. The condition parameters for facilities were specific to facility type, and scoring was assigned based on field site visits. An example of the scoring for pump stations is shown in Table 1. Due to the small number of above ground assets, each item was evaluated individually. Pumps and motors were evaluated individually, as were storage facilities. Electrical systems and pump station structures were evaluated per facility. The same criticality parameters were utilized for both facilities and pipelines and consisted of capacity affected (based on percent of entire plant capacity lost), public image/regulatory impact, and outage duration. The criticality scoring parameters and weighting are included in Table 2.

Table 1: Pump Station Condition Scoring Components, Parameters and Weighting


Table 2: Criticality Scoring Parameters and Weighting

RESULTS Gap Analysis Findings Because the existing GIS stopped at the WTP boundaries, the GIS gap analysis focused on the geodatabase structure and how it could accommodate expanding to include the facilities. The results of the GIS gap analysis were that the existing geodatabase schema didn’t accommodate detailed facility data and that the existing GIS unique ID structure needed to be expanded for treatment facilities. The work order system gap analysis findings were that the current work order system was not set-up to include key information maintenance staff needed (such as O&M manuals, warranty information and equipment manuals), did not track costs or equipment resources, was not linked to assets, did not track asset performance and was set-up to have key fields entered as free form text. The last item was key, as the free form text was not standardized; therefore, it was difficult to trend or discern what work had been performed. The following work order and GIS business processes were identified as needs during the gap analysis:

Business process for Cartegraph and Enquesta (distribution/collection system CMMS) to interface when Field Operations has been called in on a work order at a WTP

Business process for determining which work orders should be included in Enquesta or Cartegraph

Business process to capture stormwater, wastewater, and roadway assets at the Pierce-Burch WTP in the work order system

Business process for adding new assets into the work order system

Business processes for asset performance measurements, such as cost per work order, overall maintenance cost vs. budget, etc.

Business process for developing and assigning a unique identifier specifically for facility assets in GIS


Data Capture for Geodatabase AWU staff provided FNI with digitized as-built plans of the Pierce-Burch WTP to populate asset data into the asset inventory. These as-built plans were indexed and organized utilizing existing WIS business processes to allow for easy integration into the existing WIS digital as-built catalog. Asset data such as date of installation, contractor, design engineer and construction inspector were populated for each facility asset, where possible. The data captured, where available, for each feature class within the asset inventory GIS geodatabase was:

Pipelines: Pipe type, pipe manufacturer, diameter, length, material, pipe class, and pipe capacity.

Clearwells: Material, capacity, tank geometry, roof elevation, overflow elevation, and bottom elevation.

Pump Stations: Number of pumps, capacity, head, pump station type, number of pump slots and configuration.

Valves: Valve type, size, number of turns, valve function, actuator type, and normal position.

Pumps: Pump type, capacity, head, serial number, manufacturer, and pump size.

Flow Meters: Meter type, manufacturer, and size. A field survey was performed on valves, pumps, pump stations, clearwells and flow meters to tie down each asset’s exact location. Critical buried facility assets that lack adequate attribute data from available as-built plans were potholed and surveyed to determine exact alignments of the assets. GPS surveying was conducted for 886 points to tie down location, elevation and attribute data. Potholing of buried assets was performed at 26 locations. CMMS Implementation During the work order system implementation, new processes and standards were developed. Work orders are set-up to be assigned to assets based on the GIS unique ID. Standardized activity and cause codes were developed and set-up to allow AWU to better track and trend asset performance. The work order system was expanded to include work order costs for use in future condition assessment and CIP development. Important maintenance information was included in Cartegraph, including O&M manuals, warranty information and equipment manuals. Risk Based Assessment After completion of the GIS geodatabase and facility site visits, the condition and criticality scoring parameters were applied to each asset. Scoring values were grouped into condition and criticality rating categories, as shown in Table 3.

Table 3: Facility and Pipeline Condition and Criticality Ranges

Condition Rating Minimum Maximum

Very Good 0 39

Good 40 49

Fair 50 59

Poor 60 69

Very Poor 70 100

Criticality Rating Min Max

Very Low Impact 0 30

Low Impact 31 50

Medium Impact 51 72

High Impact 73 85

Very High Impact 86 100


Risk scores were assigned according to the condition and criticality of each asset. Using the categories for condition and criticality, a matrix was created to assign each asset with a risk of failure (high, medium, or low risk). Two separate risk matrices were developed for the facility and yard piping assets. Grouping each asset into categories (good condition, high impact, for example) allowed for a risk based approach to prioritize potential improvement projects. Table 4 shows the risk matrix for facilities. A similar matrix was developed for yard piping. Figure 3 illustrates the risk scores of the yard piping and clearwells of both the PB South and North WTPs.

Table 4: Facilities Risk Matrix


Figure 3: Yard Piping Risk Rankings

CONCLUSIONS To analytically determine the prioritization of capital improvement projects, each condition/criticality combination was assigned a priority within the matrix. Any assets falling in the red range were prioritized first for capital investments, while those in the yellow range should be closely monitored over time. Facilities and yard piping that were designated high risk (red) in the matrix were further prioritized based on each assets risk score as shown in Table 5. For example, the raw water pump station mechanical improvements and 17 segments of yard piping are both in the same box of their respective matrix; however, the yard piping inspection has a higher risk score and is prioritized higher than the raw water pump station mechanical improvements. Because the criticality scoring parameters for facilities and yard piping are the same, the yard piping and facility improvements can be prioritized against each other. Some assets may have individual components that need special attention despite being assigned to a lower risk category. Additional assets with lower risk score scores were added to an improvement project if they were located near assets with high risk scores to reduce construction cost. For example, Project 2 consists of raw water pump station electrical and pump improvements. This includes Pumps 1 through 3 which have either fair or poor condition score and low impact criticality score. These three pumps were included to take advantage reduced cost of contractor mobilization.


Table 5: Prioritized Capital Improvement Plan

A detailed business case for each capital improvement project was developed which identifies the project description, drivers, proposed construction alternatives, cost estimate, and a funding summary. Although several water lines ranked as high risk and in poor condition, water line inspection was recommended in lieu of replacement, as the pipeline condition was assumed, and the replacement cost would be significant. An example of a business case worksheet is shown in Figure 4. AWU has begun implementation of the CIP and has completed Project 1. Some of the pipeline inspection identified in Projects 4, 5, 8 and 10 has been performed recently, and recommendations from that inspection will be incorporated into the overall renewal CIP.


Figure 4: Business Case CIP Example

ACKNOWLEDGEMENTS Sally Mills-Wright, Arlington Water Utilities Bob Lemus, Arlington Water Utilities Mazen Kawasmi, P.E., Freese and Nichols, Inc. Steven Rhodes, Freese and Nichols, Inc.

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