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Streamlining Urban Water Utility Maintenance Workflow

Design a system to reduce repair backlogs for low-priority water main repairs, optimizing workflow efficiency for DC Water. The project involves queuing simulations and failure prediction systems.

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Streamlining Urban Water Utility Maintenance Workflow

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  1. Design of a Workflow Streamlining System for Urban Water Utility Maintenance GMU Systems Engineering and Operations Research Department SYST 495 - Spring 2017 Advisor: Dr. Lance Sherry Sponsor: DC Water Improved Repair Response & Reduced Backlog! Team Members Adnan Khan Rebekah Orozco Mohamed Khattab Fahad Alqahtani Water Main Repair Low Priority Repair Backlog Current Workflow Proposed Workflow

  2. 1. Context 2. Stakeholder Analysis 3. Problem/Need Statements 4. Concept of Operations 5. Requirements 6. Design Description 7. Verification 8. Design of Experiment 9. Results & Recommendations Agenda

  3. DC Water - Missions and Regional Areas Served

  4. DC Water Organization Chart **Note: AGM = assistant general manager Source: https://www.dcwater.com/investor_relations/2013Engineering_Feasibility_Report.pdf

  5. Assistant General Manager (AGM) Customer Care & Operations Breakdown Chart Source: https://www.dcwater.com/investor_relations/2013Engineering_Feasibility_Report.pdf

  6. DMB Organizational Chart

  7. Distribution Maintenance Branch (DMB) Responsible for performing repairs on water supply system that serves the District. Median age of pipe 78 years Original distribution system built in 1800’s Early water mains were bored logs Responds to about 1700 incidents per year Source: https://www.dcwater.com/sites/default/files/2016annual_1.24.17_lo.pdf

  8. Size and Complexity of DC Water Distribution Road Network of the District Distribution Maintenance Branch (DMB) is responsible for maintaining the following in DC: 1,350 miles of water mains 40,000 valves 9,500 fire hydrants 130,000 service connections Source: https://www.dcwater.com/sites/default/files/2016annual_1.24.17_lo.pdf

  9. Common Water Distribution Assets source: http://www.smarthomewaterguide.org/isolation-method-for-continous-leaks

  10. Annual Failures (2015)

  11. MAXIMO Dashboard - Backlog and Completed Orders

  12. Delays Compared to Repair Durations (2014 - 2016) For low priority work orders, 98% of the delay is experienced before the repair begins.

  13. Low Priority Failures by Type with Duration (2015) Among low priority orders, meters, services, mains, and valves have highest composition (83%) and among the longest response times. Specialized workflows should be made for these incidents.

  14. 1. Context • 2. Stakeholder Analysis 3. Problem/Need Statements 4. Concept of Operations 5. Requirements 6. Design Description 7. Verification 8. Design of Experiment 9. Results & Recommendations Stakeholder Analysis

  15. Stakeholder Analysis

  16. Win-Win Analysis

  17. 1. Context 2. Stakeholder Analysis • 3. Problem/Need Statements 4. Concept of Operations 5. Requirements 6. Design Description 7. Verification 8. Design of Experiment 9. Results & Recommendations Problem and Need Statements

  18. Problem Statements P.1 Low priority work orders are subject to large delays (µ = 84 days, σ = 142 days) that reduce service quality. P.2 Unanticipated failure surges increase reliance on contracted repair crews (20%) at additional cost.

  19. Need Statements N.1 There is a need for the DMB to streamline the scheduling process for low priority work orders. N.2 There is a need to acquire a short-term main break forecasting ability.

  20. 1. Context 2. Stakeholder Analysis 3. Problem/Need Statements • 4. Concept of Operations 5. Requirements 6. Design Description 7. Verification 8. Design of Experiment 9. Results & Recommendations Concept of Operations

  21. Concept of Operations 1.0 Workflow Streamlining System (WSS): WSS is a queuing simulation that models the utility’s workflow and determines which processes cause the largest impact on total response times. 2.0 Failure Prediction System (FPS): FPS is a web-based application developed to provide daily and weekly main break volume forecasts. Forecasts are to be used for dynamically adjusting repair crew schedules.

  22. Simulation Concepts

  23. 1. Context 2. Stakeholder Analysis 3. Problem/Need Statements 4. Operational Concept • 5. Requirements 6. Design Description 7. Verification 8. Design of Experiment 9. Results & Recommendations Requirements

  24. Requirements MR 1.0 The Workflow Streamlining System shall reduce the total duration of low priority work orders by 20% when compared to the base year 2015. MR 2.0 The Failure Prediction System shall ensure that on an annual basis, no more than 20% of work orders utilize contracted crews. WSS SR 5.0 The simulation shall contain as many replications required to calculate a 4% half width and 95% confidence interval. FPS 1.0 The Failure Prediction System shall provide weekly and daily main break forecasts with an R2 equal to or greater than 0.50.

  25. 1. Context 2. Stakeholder Analysis 3. Problem/Need Statements 4. Concept of Operations 5. Requirements • 6. Design Description 7. Verification 8. Design of Experiment 9. Results & Recommendations Design Description

  26. Data properties

  27. Workflow Streamlining System - Overview

  28. METERS Workflow (submodel) *NOTE: UFA = Urban Forestry Administration

  29. 1. Context 2. Stakeholder Analysis 3. Problem/Need Statements 4. Concept of Operations 5. Requirements 6. Design Description • 7. Verification 8. Design of Experiment 9. Results & Recommendations Verification

  30. Verification Testing – all work orders • Simulation outputs are consistent with historical data.

  31. 1. Context 2. Stakeholder Analysis 3. Problem/Need Statements 4. Concept of Operations 5. Requirements 6. Design Description 7. Verification • 8. Design of Experiment 9. Results & Recommendations Design of Experiment

  32. WSS Design of Experiment Length: 365 days

  33. 1. Context 2. Stakeholder Analysis 3. Problem/Need Statements 4. Concept of Operations 5. Requirements 6. Design Description 7. Verification 8. Design of Experiment • 9. Results& Recommendations Results & Recommendations

  34. Total Response Time Average response time reduced to 45 days

  35. Difference in Means (paired t-test) • Paired t-test compares baseline mean with final mean • Means are statistically different

  36. Recommendations • Implement proposed workflows for each failure type • Improve workflow processes with the largest impacts by: • Improve information sharing • Individualize UFA investigations if time open > 60 days • Optimize parts inventory • Implement quality control for investigative reports • Incorporate status system into work order scheduling process

  37. Failure Prediction System (FPS)

  38. FPS Output Regression

  39. FPS Forecasts

  40. References https://www.dcwater.com/news/presskits/Digester/DCWaterFactsAtAGlance.pdf https://www.dcwater.com/investor_relations/investor_relations.cfm https://www.dcwater.com/investor_relations/2013Engineering_Feasibility_Report.pdf http://www.missutility.net/callcenterinformation/faq.asp http://ddot.dc.gov/node/495872 http://ddot.dc.gov/node/544432 https://www.dcwater.com/business/faq.cfm http://www.indeed.com/jobs?q=Water+Utility+Worker&l=Washington,+DC&rbc=DC+Water&jcid=bc1796c7996e4b11 https://www.dcwater.com/about/gen_information.cfm

  41. Questions?

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