Risk Based Predictive Maintenance Solutions for Cleaning Sewer Mains

01 05 02 06 03 07 04 Background and Goals Visualization and Grouping Cleaning Philosophies Cleaning Optimization Tools 03 07 Cleaning Frequency Optimization Results 04 Code-based Data Collection

01 Background and Goals

CCU System Background Winston Salem Forsyth County – City/County Utilities Commission 1,750 miles of sewer 50 lift stations 2 WWTPs

Winston Salem Program Goals Reduce SSOs Reportable and Non-Reportable Use Limited Resource Efficiently Develop a Risk Based Schedule Clean the right pipe at the right time Clean the Entire System Move from reactive to proactive Leverage Data Collected

Historical SSOs Total SSOs SSOs by Cause State Reportable Non-Reportable SSOs by Cause High Percentage of O&M caused SSOs

Data Review Pull Available Data to Develop a Risk Based Schedule SSOs Cleaning History Service Requests CCTV Annual Cleaning “Heat” Maps Contractor Work Cleaning Root Control

Cleaning Philosophies 02 Cleaning Philosophies

Cleaning Performance Indicators Production Footage cleaned Set-ups performed Effective SSO reduction Cleaning QC (pass rate) Efficient Cleaning at the right time Crew A Crew B Crew C

Route-based Cleaning

Asset-based Cleaning

Route vs Asset Based Route Cleaning Asset Cleaning Pro’s Con’s Productivity Based Cleaning pipe based on need Clean more footage Better use of limited resources Less windshield time Not “over-cleaning” Limited data needs Con’s “Over-cleaning” Potentially less productive Damaging Pipes More windshield time Not an effective use of resources DATA NEEDS

Cleaning Schedule Optimization Strategic Goal: Reduce SSOs Primary Cause: Maintenance Related Tactic: Use data to maintain assets at “right time”: Benefits: Focus limited resources where they are needed most Reduce LOE to make decisions Utilize data that already exists or is being collected Extend useful lifetimes of pipeline assets

Schedule Optimization Each pipe has an optimum cleaning frequency Too Little Just Right Too Much Efficient use of resources Limit risk of overflow Extend useful life SAVE MONEY Risk of overflow Inefficient Resource Use Increase wear

Keys to SSO Reduction VIA Sewer Cleaning Office Frequency optimization process Optimized Work Order creation and assignment process Field Quality Equipment SOPs – techniques and data collection Training – techniques and data collection QA/QC Program – techniques and data collection Both Balance between quantity and quality of cleaning

Asset Based Cleaning Tools Needed Measure the maintenance condition of a pipe Determine asset cleaning frequency Group assets onto work orders in geographic clusters

Code-based Data Collection 03 Code-based Data Collection

Code-Based Cleaning Data Findings Severity Grease Clear Roots Light Debris Medium Heavy

One-to-One Work Orders Before After Steve – First thing we had to change was the way work orders were generated/completed. Need to collect code based findings on every asset rather than entire work order. Data isn’t very accurate if the same findings are used for a group of pipes. One may have Heavy Grease and the other 5 pipes on the work order may be clear. Existing system would assume all 6 pipes have Heavy Grease.

Cleaning Frequency Optimization 04 Cleaning Frequency Optimization

Cleaning Optimization Premise Based on two concepts: Data driven decisions Pipes have cleaning “windows” Data System Recommendation User Decision

CLEAR LIGHT MEDIUM HEAVY DECREASE FREQUENCY FREQUENCY IS RIGHT Data Driven Decisions CLEAR DECREASE FREQUENCY Any bullets here? LIGHT FREQUENCY IS RIGHT MEDIUM INCREASE FREQUENCY HEAVY INCREASE FREQUENCY

Cleaning Schedule Windows Target Complete Last Completed Date Next Date Target Start Date Date 1 Month 6 Month 12 Month 60 Month Time Time

Visualization and Grouping Tool 05 Visualization and Grouping Tool

Visualize Pipes to Schedule Benefit: Allow the User to quickly and effectively balance risk and geographic location when assigning work Facilitates balance between WO risk and location

Cleaning Optimization Tools (COTools) 06 Cleaning Optimization Tools (COTools)

Cleaning Optimization Tools Setup Target Complete

COTools User Interface

Steve – Now it is all in the new Cityworks system Steve – Now it is all in the new Cityworks system. Can create a single work order with many pipes and get findings for each pipe. The planner scheduler uses this GIS view to select groups of pipes that need to be cleaned. Planner scheduler looks for red pipes first and any other colors surrounding it to increase efficiency and limit windshield time.

07 Results

SSOs

HDRs Practical Approach has Led to Successful Programs

Questions? kimd@cityofws.org O: 336.771.5106 M: 336.462.1765 alex.palmatier@hdrinc.com O: 336.955.8255 M: 619.726.3219