Background
The City of La Mesa, California employs a highly rigorous cleaning process as part of its preventive maintenance program. The city has 153 miles of sanitary sewer pipes and 53 miles stormwater pipes to maintain. Both the storm and the gravity pipe systems are cleaned on an annual basis. All of this work is performed by a small, highly efficient group of eight field technicians. Adding to their annual workload, 100 sites are cleaned monthly due to roots and fats oils and grease (FOG).
Demands of the Maintenance Process
The City’s preventive maintenance program has led to their excellent track record of preventing sanitary sewer overflows (SSOs). However, the City recognised that regular, high frequency cleaning is more than likely promoting over-cleaning where, in addition to taxing the field staff, it also increases pipe wear, potentially causing the necessity for premature asset replacement. Further, in older parts of the City’s system, over-cleaning may threaten damage to already high-risk pipes. As a result, the City looked for a new approach to reduce operational demands, alleviate premature pipe wear, and continue to prevent overflows.
A New Vision
Partnering with ADS Environmental Services, ten sites were selected to install ECHOs, continuous remote site level monitors. Each site had been on the monthly cleaning schedule.
These new generation monitors, with five configurable alarms, advanced LTE-M communications and continuous, cloud-based access to real-time data, gave the City assurance that this change in cleaning protocol would maintain their exemplary SSO record and provide the new efficiencies that they sought.
The Four Major Benefits
Moving forward, the City will now start to integrate monitoring into its maintenance program realising four benefits.
- Reduction of pressure on operations to clean.
- Acquiring continuous monitoring to prevent SSOs where none existed previously.
- Reducing pipe wear and thus extending asset life.
- Acquisition of data for further analysis of collection system behaviours e.g., dry vs. wet weather.
