Design of a Decision-Support for the Scheduling of …...1 Design of a Decision-Support for the...

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Design of a Decision-Support for the Scheduling of a Workflow Process for a

Water Utility Company Christopher F. Pertsch V, Jomana Bashatah, Wisal Mohamed, Jose Soberanis

Before Solution After

Projected Backlog Decrease

Website: www.castorea.pythonanywhere.com

Increase in Work Order Backlog

Solution: Smartphone

Scheduling App

Table of Contents

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1.0 Context Analysis

2.0 Stakeholder Analysis

3.0 Problem and Need Statements

4.0 CONOPS and Requirements

5.0 Design Alternatives

6.0 Simulation/Castorea

7.0 Utility

8.0 Scheduling Tool Design

9.0 Business Plan

Table of Contents

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7.0 Utility


9.0 Business Plan

America's Water Crisis

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• Water prices are expected to increase by 41% in the next five years to cover the costs of replacing aging water infrastructure

• Water utility companies, such as our sponsor D.C Water, need to find novel ways in order to prevent these projection from happening

https://www.vox.com/science-and-health/2017/5/9/15183330/america-water-crisis-affordability-millions

Context Analysis- DC Water

Service area is approximately 725 Square miles.

Provides service for more than 672,000 residents and 21.3 million visitors annually.

Water Distribution System (WDS) is composed of:

◦ 48,979 valves

◦ Delivers water through 1,350 miles of pipes

◦ 9,462 fire hydrants

◦ 130,000 service connections

Average age of pipe is 77 years old.

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https://www.dcwater.com/dc-water-glance

Context Analysis- DC Water Maintenance Branch

DC Water repairs more than 400 water main breaks per year

During the winter, crews repair an average of 9 breaks a day

A simple water main repair can be completed in six to eight hours, but large or complicated repairs may take several days to a week.

There are other failure types that need repair such as valves, meters and water service pipe

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https://www.dcwater.com/cycle-water-break

Context Analysis- Distribution & Maintenance Branch

The team will focus efforts on Distribution and Maintenance Branch (DMB), subdivision of greater DC Water company

◦ Responsible for repairs and maintenance on aging pipeline infrastructure

◦ Made up of three Foremen:

◦ Each foreman is referred to as Omega # (10, 20, or 30)

◦ Each foreman has 3 crews.

◦ A crew consists of 5-7 personnel, costing DC Water $8-10k daily

◦ Each crew is required to always have at least one equipment operator.

◦ General Foreman is in charge of investigating, directing and coordinating repair work for DMB.

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Context Analysis – Work Orders

•Work orders are created once a customer reports an incident.

•In 2014, a new priority system that categorizes work orders was introduced.

•The team conducted data analysis of 14,000 data point form 2014- 2017, and the following graph was obtained:

•5 needs to be done immediately

•4 needs to be done in 24 hours

•3-2-1 can be done at the foreman's time

High Priority

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Context Analysis - Backlog Backlog is any work order open for more than 90 days

An average of 33 work orders are completed per week.

Since February of 2017, the amount of work orders that have increased resulting directly from the renovation project is 1,100 per year.

For

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-20

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Gamma(4.59, 0.567)

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Workflow for processing work orders

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Source: DC Water Work Orders for 2014-2016

14,000 data points

Gamma(0.882, 3.15)

Gamma(3.34, 1.52)

Gamma(0.882, 3.15)

Gamma(1.88, 2.45)

Gamma(2.48, 2.42)

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Work Order Rates Increase

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Increase in work orders open 90 days or more

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•As of January of 2017, approximately 30 additional work orders per week have been created because of AMR • Meter housing, which is a low priority work order is currently 67.63% of all backlog priority 3 work orders

•Meter housing increase in backlog is a result of the AMR

•As the old meters are being replaced the meter housing are being damaged

Breakdown of Work Orders

Travel Time in Ad-Hoc Scheduling

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•Currently, foreman allocate work randomly amongst the repair crews.

•This is leading to work being spread around with no focus on distance between each work order.

•Average travel time between work orders: ~19 minutes.

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Depo

Schedule for WO #17-28864

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Delays Resulting in Wait Time • After starting repairs, there are

steps that need to be taken to complete the repair, which causes on-site wait time.

• Examples such as: Pre-site preperation, Urban Forestry, Miss Utility markings, and waiting for valve crews for delays

• During the delays, The crew is completely idle until the delay cause is resolved

Priority 5 work order shutting down

valve M Street, Washington

D.C 10/13/2017

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Schedule for Work Order #14-82587

Table of Contents

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7.0 Utility


9.0 Business Plan

Stakeholder Analysis

•Water Consumers: Clients who desire reliable and clean, drinking water from a water distribution source at an affordable price with exceptional customer service

•3rd Party Contractors: Repair crews who serve to assist DMB crews with equipment, external labor, AMR, etc.

•Department of Transportation: Government entity that issues work permits for maintenance and repairs needed in public areas.

•Win-Win Analysis: So long as there are 3rd party contractors, there are additional resources on site that'll help in completing work thus DMB completes tasks and consumers will be satisfied.

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Table of Contents

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7.0 Utility


9.0 Business Plan

Problem and Need Statements

Problem Statement:

•A 40% increase of backlogged work orders caused by the current meter renovation project • An average of 30 work orders added to the existing

backlog per week over the year 2017

• Also an increased the mean time in system of a work order to 62 days.

Statement of Need:

•DC Water must reduce the backlog and time in system to 10 work orders and 30 days respectively.

•They have to schedule by location

•Minimize idle time

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Gap

Table of Contents

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4.0 ConOps



7.0 Utility


9.0 Business Plan

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CONOPS

Note: The name of our workflow efficiency system is Castorea

Table of Contents

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4.0 ConOps



7.0 Utility


9.0 Business Plan

Design Alternative #1: Dedicated Low Priority Crews

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Dedicated Crew for Low Priority

1 crew dedicated for low priority in the summer

1/No crew dedicated for low priority in the winter

2 crews dedicated for low priority in the summer

• 1-2 Crews will be assigned solely low priority work depending on season

• 94.3 % of all work orders in backlog are Low Priority

• 5.68% of all work orders in the backlog are High Priority

• Winter season has the most high priority

Current Method Alternative Design

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Design Alternative #2: Schedule based on travel time minimization

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• Create a scheduling system • Currently there is no dispatching system in place • The General foreman uses an equal sequential

allocation of tasks • Based on completion time

Actual addresses extracted from database and geo-batched.

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Before

After

Work Order #14-84591

Wrench Time Maximization Support System

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•A decision support system will be created to support each team's foreman on deciding whether to fix nearby work orders during their idle time

•Uses google maps to calculate travel times •Uses work order repair distributions to calculate repair time

•Some work orders are delayed creating idle times of 2-4 hours and sometimes even more.

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Original Schedule

Maximize Wrench Time Schedule

Table of Contents

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4.0 ConOps



7.0 Utility


9.0 Business Plan

Simulation Inputs, Parameters and Outputs

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• Inter-arrival time of work orders

• Time to complete repair

• Travel time

• Preparation time

Random Variables:

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Repair Time Distributions

Repair Type Meters Valves Services Mains

Distribution Gamma(0.882, 3.15) Gamma(3.34, 1.52) Gamma(1.88, 2.45) Gamma(2.48, 2.42)

Interarrival Times Gamma(4.59,0.567)

Type Meters Valves Services Mains

Average 2.77 5.07 4.6 6.01

StDev 1.53 4.21 2.84 3.35

Meters, Services distribution had a lot of noise. P-value < 0.005

Source: DC Water Work Orders for 2014-2016

14,000 data points

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Petri-Net Workflow Model – Work Order Arrival and Assignment

Steps being modeled: 1. Arrival of Work Orders 2. Foreman Inspection with priority queue 3. Prioritization of Work Orders

Petri-Net Workflow Model – Repair Dynamics

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Baseline Simulation Verification Results

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Work order in Work order out

Simulation 1550 per year 1431 per year

Actual 1556 per year 1515 per year

% Error 0.4% 5%

Avg. Time in system (Hours) Stdev (Hours)

Simulation 1454.99 1320.06

Actual 1488 1383.432

% Error 2.3% 5%

Verification for Time in System

Verification for Work Order In and Out

Design Alternative #1 One & Two Dedicated Crews Process Improvement results

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One Crew

Two Crew

Time in system 5.2% decrease

Backlog 100% decrease

Closed Work orders per year 31% increase

Time in system 0.5% decrease

Backlog 100% decrease

Closed Work orders per year 34% increase

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+10 per month

-18 per month

-12 per month

3 1

D.C Water will implement a Pilot test starting on April 1st

Design Alternative #2 Travel Time Reduction Simulation Results

Average sigma T-Test (alpha = 0.05) Percent Improvement

Time in System 1523 557 Significant 4.8

number in 1551 16 Not Significant

backlog 413 /-6 per month 187 Significant 6.2

closed 1472 187 Significant 2.8

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Time in system 4.8%

Backlog 6.2%

Closed Work orders per year 2.8%

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Travel Time Reduction Results

Current System

Travel Time Alternative

Expected Travel Time Between Work Orders

Expected Travel Time Between Work Orders

μ = 20 minutes

μ = 9 minutes

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Simulation Results Design Alt Work Order

Time in System (Averag

e)

Work Order Time in

system (St dev)

Backlog increase

Per month

Travel Time in hours (St dev)

Travel Time in hours (Mean

# of closed work orders per year

(mean

Baseline 1599 567

+10/month 0.186 0.320

1431

Travel Time Scheduling

1523 557 -6/month

0.081 0.163 1471

One low-Priority Dedicated crew

1514 1133 -12/month 0.186 0.320 1877

Two low-Priority Dedicated

crew

1589 1254 -18/month 0.186 0.320 1922

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Table of Contents 1.0 Context Analysis



4.0 ConOps



7.0 Utility


9.0 Business Plan

Value Hierarchy

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U(t)= 0.769*closed work orders+ 0.154*backlog+ 0.077*average time in system.

Cost Vs Utility Design Alternative Utility

Current Method 0

Crew Focus 1 0.878

Crew Focus 2 0.932

Travel Time 0.1403

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• Crew Focus 1: to be pilot tested by DC Water starting April 1st 2018.

• Marginal Utility: -3.29E-6/$1

in Dollars

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4.0 ConOps



7.0 Utility


9.0 Business Plan

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Scheduling Tool - Castorea

◦ Multi-purpose application 1. Scheduling System based on Travel Time

2. Wrench Time Maximization

◦ Development of Castorea: ◦ Coded in Python, HTML, CSS and Bootstrap, Javascript

◦ Flask web development tool

◦ Google Maps API Directions library

◦ Deployed through PythonAnywhere

◦ In association with Amazon Web Services

◦ ~1400 lines of code

Castorea - Requirements

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Input Requirements: 1.1.1.1 User Log-in and Password: Shall Correctly accept Users' Log-in and password 99% of the time 1.1.1.2 Database Shall Correctly accept Users data 99% of the time 1.1.1.2.1 Excel Files Shall be able to read excel files 99% of the time 1.1.1.2 Wrench Time Maximization Address The system shall be able to correctly accept users' address 99% of the time.

Output Requirements: 1.1.2.1 Return closest work orders The systems shall return top 10 work orders closes to inputted address in ascending address correctly 99% of the time 1.1.2.2 Display Crew Schedules The system shall display crew schedules 1.1.2.3 Estimated Time The system shall output the estimated time that the crew will be working for the day.

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Desktop Site

Wrench Time Maximization Website: Castorea

Mobile Site

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Castorea: Wrench Time Maximization

Note: All screenshots were taken from the mobile site.

Usability Test for Castorea

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Usability Test

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Experimental Control

• Within subject design

• 3 Tasks

• Tasks were randomized

• Sample:

• 4 all foremen

Tasks

1. Setting Schedules

2. Wrench Time Maximization

3. Viewing Schedules

Usability Test – Goal Requirements

1. Setting Schedules The user shall be able to set a schedule with three work orders in under 3 minutes (180 sec)

2. Wrench Time Maximization The user shall be able to find the closest work order and add it to the schedule in under 2 minutes (120 sec)

3. Viewing Schedules The user shall be able to find the and view the schedules in under 20 seconds.

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The goal requirements elicitation was done with the foremen and managers at D.C. Water

Usability Test - Results Task 1 – Setting Schedules

Task 2 – Wrench Time Maximization

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Mean 105.05 sec

Standard Dev 55.53 sec

P-Value 0.03743

Null Hypothesis: Setting a schedule will take more than 180 seconds

Null Hypothesis: Setting a schedule will take more than 120 seconds

Mean 77.75 sec


P-Value 0.006892

Usability Test - Results Task 3 – View Schedules

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Null Hypothesis: Viewing a schedule will take more than 20 seconds

Mean 5.25 sec


P-Value 0.0002114

Usability Test Questionnaire

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Usability Test – Satisfaction Results

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Null Hypotheses:

The true mean of question X is less than 3

Where X = {1,2,3,4,5,6}

Question # Mean SD P-Value

1 (Scheduling) 4 1.15 0.09085

2 (Viewing Schedules) 4.5 0.577 0.006923

3 (Website Navigation) 4.25 0.95 0.0398

4 (Sorting Work Orders) 4 0.816 0.04586

5 (Overall Satisfaction) 4.75 0.5 0.002993

6 (Would you use the tool?) 4.75 0.5 0.002993

All of the questions were statistically larger than 3 except for

question 1 (Scheduling)

Usability Test - Conclusion

1. The system was able to meet all the goal requirements

2. The system was able to meet all of the satisfaction requirements except for creating a schedule (Question 1)

3. Some changes regarding the ordering of the Web-app when creating a schedule were done in order to improve the user experience (Question 1)

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4.0 ConOps



7.0 Utility


9.0 Business Plan

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Business Plan For Castorea Lead Customer - DC water

Business Model: $100,000 purchase cost

$299/month for support and maintenance

Break Even: Break Even in in the first year.

ROI: 6292% in 5 years

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Conclusion – Projected Results $2,976,000 was added in value to D.C. Water using our scheduling system

Productivity increased by 31% in terms of work orders closed

Backlog of work orders decreased by 100% within 8 months

Travel time was reduced by 55%. The amount of a crew’s days spent travelling dropped from 20% to 7%

Future Work System Delivery and Presentation to D.C. Water Senior Leadership

Analysis of pilot project results

D.C Water started implementing a Pilot test

starting on April 1st

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THIS FANTASTIC TOOL AND THIS PROJECT REALLY DOES A LOT TO MOVE US FORWARD!"

- CHRISTOPHER COIT (DC WATER PROJECT MANAGER)

Return on Investment

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ROI in 5 years is 6292%

Costs Startup Costs:

◦ $36,000 development

◦ $5,000 marketing

◦ $5,000 sales

◦ $17,400 Startup expenses (rent,

supplies)

◦ Total of $63,400

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DMB Primary Stakeholders •Manager: oversee the operations

•General foreman: distributes work to foreman FIFO w/ equal distribution

•Foreman: deal with outside sources in charge of initiating work to be done on low priority work orders

•Repair Crews: personnel that go out to the site to complete the necessary repairs to close a work order.

•Win-Win Analysis: If foreman balances complexity of work amongst repair crews, crews will not be overwhelmed/stressed thus avoiding decrease in quality

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Context Analysis - Budget Operating budget of $561,947,000 .

Water services budget for FY 2018 is $24,094,000.

On-going project: repairing water main break, replacing valves...

The budget for on-going projects for FY 2018 is $6,886,000.

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Petri-Net Workflow Model – Part 2

Steps Being Modeled: 1. Work Order Prioritization 2. Crew Assignment Priority Queue

Utility Function Tradeoffs method

Weight were given by the program manager of DC water

Closed work works has most weight

Average time in system rated the lowest

U(t)= 0.769*closed work orders+ 0.154*backlog+ 0.077*average time in system.

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Context Analysis – Distribution Maintenance Branch

Dedicated Low Priority Crews Simulation Results

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Avg. Time in system (Hours)

StDev (Hours) Average Number of Closed Work Orders

Average Rate of Backlog Increase

Baseline 1599 567 1431 +10/month

Alternative #2 – Dedicate 1 Resource

1514 1133 1877 -12/month

Alternative #2 – Dedicate 2 Resources

1589 1254 1922 -18/month

3 1

Sensitivity Analysis

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Travel Time Simulation – SYSML Activity Diagram

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2

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Context Analysis • Factors influencing "perfect

storm": • Social:

• Increasing Population • Economic:

• Ensuring budget remains constant

• Technological: • AMR Project • Degrading

Infrastructure • Maintain WO Closure

Rate Confluence Diagram

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Context Analysis – Automated Meter Reading (AMR) Replacement project

AMR Meter that collects water flow data via satellite.

As of February 2017 backlogs of low priority work orders have been rising.

◦ Three possible scenarios

◦ (1) The meter is successfully changed No new work orders

◦ (2) The meter replacement causes damages to the meter housing New work orders

◦ (3) In the process of meter replacement damages to the main are discovered New work order

Travel Time Minimization – Activity Diagram

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Wrench Time Maximization – Activity Diagram

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Simulation Requirements

◦ 1.2.4 Model current workflow ◦ The simulation shall model the current

workflow of work orders used by D.C Water. with 95% accuracy

◦ 1.2.4.1 Foreman Low Priority Assignment ◦ The system shall simulate the workflow

from the moments the general foreman is given work order until a foreman starts a work order with 95% accuracy

◦ 1.2.4.2 Delay simulation ◦ The system shall simulate the travel time

delays in workflow of work order

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Repair Type Meters Valves Services Mains

Distribution Gamma(0.882, 3.15) Gamma(3.34, 1.52) Gamma(1.88, 2.45) Gamma(2.48, 2.42)

Interarrival Times Gamma(4.59,0.567)

Type Meters Valves Services Mains

Average 2.77 5.07 4.6 6.01

StDev 1.53 4.21 2.84 3.35

· Meters, Services distribution had a lot of noise. P-value < 0.05

Design Alternative #3 Wrench time– Preliminary Results

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Schedule

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SPI: 0.94

CPI: 0.93

Validation Test Procedures Baseline

1. Use interarrival time of total work orders of given data to simulate the current workflow

2. Use time distributions of repairs by each Omega team as delays.

3. Verify the total time in system for a work order in baseline matches the actual time in system by 95%

Alternative design- Resource focus test

1. Modify the baseline simulation structure in foreman queue to have one or two of the teams focus on low priority work orders.

2. Compare results to the baseline results.

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Cost

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Year 1 2 3 4 5 6 7 8 9 10

Cost 365691 370925 390175 378425 492675 541850 582675 705925 720050 729175

Revenue 1440 144000 432000 720000 1008000 1440000 2160000 2448000 2592000 2736000

Profit -364251 -226925 41825 341575 515325 898150 1577325 1742075 1871950 2006825

Cum Profit -364251 -591176 -549351 -207776 307548 1205698 2783023 4525098 6397048 8403873

ROI -100% -61% 11% 90% 105% 166% 271% 247% 260% 275%

Initial Investment

365691 365691 365691 365691 365691 365691 365691 365691 365691 365691

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Verification Test Plan Test Plan Requirement Pass/Fail/In-Progress

1. Run simulation for 4000 replications

2. Calculate waste time to verify that it has been reduced by 45%

3. Calculate backlog to verify that it has reduced by 90%

4. Calculate time in system, verify that it is within 5% error of real workflow

S.O 1.1.2 The system shall minimize waste in delay time by 45% S.O 1.1.3 The system shall reduce backlog by 90% S.R 1.2.4.1 The system shall simulate the workflow from the moments the general foreman is given work order until a foreman starts a work order correctly with a margin of error of 5%. S.R 1.2.4.2 The system shall simulate the major delays in workflow of work order 95% of the time.

Pass Fail Pass Pass

Simulation Objectives

SO 1.1.1 Resource Maximization: ◦ The system shall maximize the usage of

resources so that no resource has less than 60% usage at any given time.

SO 1.1.2: Minimize Wait Time: ◦ The system shall minimize waste in delay

time by 45%.

SO1.1.3: Reduce Backlog ◦ The system shall reduce backlog by 90%

since January 2017 (AMR)

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10 Year Projection detail

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Year 1 2 3 4 5 6 7 8 9 10

Customers/unit 1 100 300 500 700 1000 1500 1700 1800 1900

API Cost 91.25 91.25 182.5 182.5 273.75 365 456.25 638.75 912.5 1277.5

Sales 5000 5000 5000 5000 5000 8000 8000 8000 8000 8000

Computers (x4) 4800 0 0 0 0 4800 0 0 0 0

Interest Cost 28000 29000 30000 0 0 0 0 0 0 0

Loan Amount 7000000 0 0 0 0 0 0 0 0 0

Office Supplies 500 500 500 500 800 800 800 800 800 800

Office Rent 800 800 800 800 800 800 800 800 800 800

Marketing 10000 10000 10000 10000 1000 15000 15000 15000 20000 20000

Customer Support

0 0 0 0 30000 30000 30000 60000 60000 60000

Software Engineer

0 0 0 0 75000 75000 75000 150000 150000 150000

Sub-Fee 300000 30000 30000 30000 30000 30000 30000 30000 30000 30000

Dedicated Low Priority Crews

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High Priority Work Orders are the highest in the colder season

Data analysis of 12000 points was

conducted, and high priority work order make 54% of all work orders in the winter, so the low priority crew focus is not feasible during winter


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Team

Meters Services Mains Valves

O-11 ERLA(1.35, 2) TRIA(1, 1.01, 10) 2 + EXPO(5.29) NORM(4.48, 2.66)

O-12 ERLA(1.56, 2) ERLA(2.34, 2) NORM(7.46, 4.72) 1 + 17 * BETA(0.941, 1.18)

O-13 GAMM(2.67, 1.28) WEIB(5.03, 1.16) 13 * BETA(0.546, 0.728) 0.999 + EXPO(3.74)

O-21 LOGN(3.47, 2.4) 0.999 + EXPO(4.56) 12 * BETA(1.17, 1.22) 1.45 + 0.551 * BETA(0.348, 0.296)

O-22 LOGN(2.62, 1.73) -0.001 + ERLA(2.59, 2) NORM(5.8, 2.93) GAMM(8.98, 0.915)

O-23 LOGN(2.62, 1.73) -0.001 + ERLA(2.59, 2) NORM(5.8, 2.93) GAMM(8.98, 0.915)

O-31 LOGN(3.33, 2.53) ERLA(2.35, 2) TRIA(2, 8.3, 11) 9 * BETA(1.15, 2.04)

O-32 GAMM(0.816, 3.83) 0.999 + 34 * BETA(0.465, 2.37)

0.999 + LOGN(23.1, 138) 0.999 + WEIB(1.17, 0.645)

O-33 NORM(2.65, 1.22) 1 + LOGN(4.71, 5.6) WEIB(7.35, 0.956) 0.999 + EXPO(7.05)

• K-S Test was used with an alpha of 0.05 • Those distributions in red passed the test



3.0 Problem and Need Statement

4.0 CONOPS


6.0 Simulation/Verification/Validation

7.0 Design of Experiment

8.0 Project Plan

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Verification Plan

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Requirement Verification Plan

The system shall simulate the actual workflow with a ±5% error

Manual calculations will be performed using random number generators from the distributions and verifying that they are within the acceptable percent error.

The system shall reduce the amount of work orders from 100 to 10

Manual calculations will be performed to corroborate that the amount of work orders is being reduced by applying the different alternatives.

The system shall increase the wrench time from 50% of the day to 60% of the day

Manual calculations will be performed to verify that the amount of wrench time increased.

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Castorea: Wrench Time Maximization

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• Mann-Whitney-Wilcoxon Test was performed to test if the two samples came from the same population

• The P-Value was less than 0.05

Method of Analysis To identify alternatives:

• Simulations will be developed

• Bottlenecks and deficiencies will be recognized through simulation.

Design Alternatives

1. Baseline

2. Travel time reduction

3. Crew Resource Focus

4. Wrench time maximization support system

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Input/output Diagram

Travel Time

Reduction

Repair Distribution

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Mains Meters

Valves Services

Context Analysis- backlog by type

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• Meter housing is currently 67.63% of all backlog priority 3 work orders

• Meter housing increase in backlog is a result of the AMR

• As the old meters are being replaced the meter housing are being damaged

METER HOUSING

Validation

Requirement Validation Plan

The system shall correctly receive and analyze work order arrival data 95% of the time in no more than 60 seconds.

Validate the simulation outputs with the real workflow outputs with error ±5% using calculated interarrivals

The system shall minimize waste in delay by 45%. Minimizes delay time from 4 to 2 hours

The system shall reduce backlog by 90% since January 2017 (AMR)

The backlog of work orders reaches 10 within 8 months starting April 2018

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Statement of Work Scope of Work - The system will be directly working with the DMB.

Period of Performance - The period of performance for the DC Water project is beginning on Aug 29th through May 18th.

Place of Performance - The place of performance will be at GMU Fairfax campus for the majority of the time and on site with DC Water team. The team will also have monthly on-site meetings and research to analyze the workflow process.

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Milestones Date

Project Planning Finalized 9/13/17

Project Research Finalized 9/13/17

Requirements Finalized 10/12/17

Simulation Finalized 3/15/18

Testing Finalized 3/15/18

Deliverables and Presentations Finalized 05/07/18

Work Breakdown Structure (WBS)

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Preliminary results of baseline simulation Work order in Work order out

Simulation 1580 per year 1680 per year

Actual 1556 per year 1733 per year

% Error 1.5% 4%

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Avg. Time in system (Hours) Stdev (Hours)

Simulation 1454.99 1320.06

Actual 1488 2400

% Error 2.3% 55%

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WBS Items in the Critical Path: 1. 1.4.1 Analyze Work Order Data 2. 1.6.3 Modelling 3. 1.6.4 Sensitivity Analysis 4. 1.8.1 Unit Testing 5. 1.8.2 Sub-system Testing 6. 1.8.3 System Testing 7. 1.8.4 System Acceptance

Wrench time Maximization Website– SYSML Activity Diagram

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Budget

Calculated budget based on:

◦ Systems Engineer Lead: 40$/hour

◦ Systems Engineers: 35$/hour

◦ "Work" trips: 20$/person

Total hours of work: 8,659.40

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• Total budget: 317,159.00

• Upper bound

• Total work hours: 8779.4


• Lower Bound

• Total work hours: 8539.4


• Weighted Average = (O + 4M + P)/6

Project Risks & Mitigation plan

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Context Analysis - Distribution Maintenance Branch (DMB)

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In-house Crew VS. Contrators

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In-house Contractors

Simulation Requirements 1.2.1 Input Requirements

All of the requirements regarding the inputs the system shall receive

1.2.1.1 Work Order Arrival

The system shall correctly receive and analyze work order arrival data 95% of the time. The work orders shall include data relating to the type, category, and time.

1.2.2 Output Requirements

All the requirements regarding the outputs of the system

1.2.2.1 Work Order Time Distribution

The system shall output a distribution with the mean and standard deviation of the work orders.

1.2.2.1.1 Cost Estimations

The system shall calculate the costs of the new work order distributions.

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Work Order Failure Class Types

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Verification Test Procedures Alternative design- Task duration

1. Fill each crew's day based on time to complete each failure.

2. Compare results to baseline and alternatives

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Sequence Diagram for LP with Tree Delay

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Functional Requirements F.R 1.2.3 Analyze Alternatives

◦ The system shall statistically compare the different alternatives of the business process and correctly select the best one 95% of the time.

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Verification Test Procedures Alternative design- Idle time minimization test

1. Calculate available work time

2. Calculate lost time due to delay

3. Calculate actual work time

4. Calculate productivity rate % = (Actual work/ available work)

5. Idle time <= 5% of total time

6. Calculate population and businesses density in DC wards

7. Modify baseline simulation to have teams perform at least two work orders in close area proximity.

8. Compare results to baseline and alternatives.

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Workflow System Requirements W.R 1.5.1 Recommendation

◦ The system shall correctly make feasible recommendations 95% of the time.

W.R 1.5.2 Third Party Contractors ◦ The system shall NOT use third party

contractors for the closure of work orders.

W.R 1.5.3 Work Order Outliers ◦ The system shall disregard outlier work

order data

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Miss Utility Markings

•Once a work order is called in and investigating crew assesses the site

•Utility markings identify any underground line that is directly in the way of construction

•There are different types and colors of markings based on the kind of work done

•The ones marked in blue is the water lines

•They take up to 2 hours to finish marking

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Backlog Data Analysis by Failure Class

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Design of Experiment

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Experiment Input (Interarrivals) Output

Baseline Alt 1 Alt 2 Alt 3 µ (hours) St.Dev

# of Work Order In

# of Work Orders Out

Rate of Backlog Increase

1 T F F F 1454.99 1320.06 1580 1680 +20/month

2 F T F F

3 F F T F 1514.32 1132.87 -12/month

4 F F F T

5 F T T F

6 F F T T

7 F T F T

8 F T T

T

We will begin by testing the baseline simulation to see what the output generated is. Then, in every run afterwards a different combination of alternatives will be applied to the simulation and then every factor (average time in system, # of WO in and out, etc.) will be taken into consideration to determine best combination of alternatives.

Alternative #2 Focuses 1 resource to backlogged work orders

Alternative #1 creates a schedule for the crews

Alternative #3 uses a decision support system to reduce idle time

Functional Requirements F.R 1.2.1 Input Requirements

◦ All of the requirements regarding the inputs the system shall receive

◦ F.R 1.2.1.1 Work Order Arrival ◦ The system shall correctly receive and analyze work

order arrival data 95% of the time. The work orders shall include data relating to the type, category, and time.

F.R 1.2.2 Output Requirements ◦ All the requirements regarding the outputs of the

system.

◦ F.R 1.2.2.1 Work Order Time Distribution ◦ The system shall correctly output a distribution with

the mean and standard deviation of the work order 90% of the time.

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Non-Functional Requirements These are all the non-functional requirements for the developments of this system

NF 1.3.1 Compliance ◦ The system shall comply with all the

regulations for which D.C. Water has not control over.

NF 1.3.2 Delivery ◦ The system shall be able to produce

optimization recommendations by April 1st, 2018

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Added value breakdown Daily cost for crew = 8000

◦ Cost for 6 crews = $8,000 *6 crews * 200 workdays = $9,600,000

In FY 17, DC Water closed 1600 work orders

◦ $9,600,000 / 1600 work orders =$6,000 / work order

Using Castorea:

DC Water is able to close 2096 work orders

◦ 2096 – 1600 = 496 work order increase

◦ 496 work orders * $6,000 = $2,976,000

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