Edelman USCG Final

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    Operations Research Enhanced Supply

    Chain Management at the US Coast Guard

    Aircraft Repair and Supply Center

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    Team Members

    USCG Team CDR Carl Riedlin

    LCDR Mike Shirk LCDR Kent Everingham

    LCDR Gary Polaski

    Purdue Team Prof. Vinayak Deshpande

    Prof. Ananth Iyer

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    Cultural Transformation

    Through

    USCG ARSC + Purdue = OR ingrained

    + =

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    Route of Flight

    US Coast Guard Roles & Missions

    Logistics Network

    Ops Research & Purdue/Coast Guard Partnership Four Projects:

    MIDAS, REAP, CRISP and OPT

    Impact & Organizational Transformation

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    Aviation Facility Location &Allocations

    Humboldt Bay 5 HH-65C

    Kodiak

    5 HC-130H

    4 HH-65C

    4 MH-60J

    ATC Mobile

    4 HU-25A

    7 HH-65C

    3 MH-60J

    North Bend 5 HH-65C

    Los Angeles 3 HH-65C

    San Francisco 4 HH-65C

    Barbers Point

    4 HC-130H

    4 HH-65C

    Corpus Christi

    3 HU-25C

    3 HH-65C

    Houston- 4 HH65CNew Orleans- 5 HH-65C

    Miami

    6 HU-25D

    9 HH-65C

    Savannah 5 HH-65C

    Borinquen 4 HH-65C

    Detroit 5 HH-65C

    Traverse City 5 HH-65CAstoria 3 HH-60J

    Sacramento 4 HC-130H

    San Diego 3 MH-60J

    Sitka 3 HH-60J

    Clearwater

    6 HC-130H

    9 HH-60J

    Elizabeth City

    4 HC-130H

    5 MH60-J

    1 HC-144A

    Cape Cod

    4 HU-25C

    4 HH-60J

    Atlantic City 10 HH- 65C

    Washington

    1 C-37

    1 C-143

    HITRON 8MH-68A

    HC-130: 22 Operational - 5 Support / HU-25:17 Operational - 8 Support / HH-60: 34 Operational - 7 Support / HH-65: 84 Operational - 11 Support

    Port Angeles 3 HH-65C

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    Aircraft Repair and Supply

    Center (ARSC)

    One stop shop for all aviation logistics support Depot level maintenance

    Supply engineering

    Spare parts inventory management Component repair

    Information services

    60,000 individual parts, Inventory value over $937 million

    Annual maintenance budget over $154 million forover 6000 parts

    http://www.airliners.net/open.file?id=1197456&size=L&width=1200&height=811&sok=JURER%20%20%28nveyvar%20%3D%20%27HFN%20-%20Pbnfg%20Thneq%27%29%20%20BEQRE%20OL%20cubgb_vq%20QRFP&photo_nr=5http://www.airliners.net/open.file?id=1198118&size=L&width=1024&height=695&sok=JURER%20%20%28nveyvar%20%3D%20%27HFN%20-%20Pbnfg%20Thneq%27%29%20%20BEQRE%20OL%20cubgb_vq%20QRFP&photo_nr=3http://www.airliners.net/open.file?id=1201254&size=L&width=1200&height=812&sok=JURER%20%20%28nveyvar%20%3D%20%27HFN%20-%20Pbnfg%20Thneq%27%29%20%20BEQRE%20OL%20cubgb_vq%20QRFP&photo_nr=1
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    ScheduledMaintenance

    Air Station

    Repair

    Maintenance

    Shop

    Warehouse

    - Air Station

    - ARSC

    Item Managers

    Procurement Specialists

    Component

    Repair (Internal)

    Vendors (OGA

    & Commercial)

    failed partsgood parts

    ACMS Data

    AMMIS Data

    Un-ScheduledFailures

    http://www.airliners.net/open.file?id=1197456&size=L&width=1200&height=811&sok=JURER%20%20%28nveyvar%20%3D%20%27HFN%20-%20Pbnfg%20Thneq%27%29%20%20BEQRE%20OL%20cubgb_vq%20QRFP&photo_nr=5http://www.airliners.net/open.file?id=1198118&size=L&width=1024&height=695&sok=JURER%20%20%28nveyvar%20%3D%20%27HFN%20-%20Pbnfg%20Thneq%27%29%20%20BEQRE%20OL%20cubgb_vq%20QRFP&photo_nr=3http://www.airliners.net/open.file?id=1201254&size=L&width=1200&height=812&sok=JURER%20%20%28nveyvar%20%3D%20%27HFN%20-%20Pbnfg%20Thneq%27%29%20%20BEQRE%20OL%20cubgb_vq%20QRFP&photo_nr=1
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    Clear & Present Danger

    Highly complex supply-chain

    Various groups focused on a specific task Reliability Center Analysis

    Inventory Replenishment & Budgeting

    In-House Repairs & Capacity Management

    Procurement & Best-Value Contracting

    Need for information collaboration between groups

    Impending Brain Drain in Federal Govt Item Manager / Procurement Specialists Retirement

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    A Partnership is Formed

    Purdue a Best Value in Advanced Education Coast Guard officers in MBA & Structures programs since 1970s

    Initial contact in 2001 with 2 goals Validate OR capability with ARSC

    Lead cultural change in face of budget & people crisis

    Prof. Deshpande & Iyer form a team

    Exhaustive review of supply-maint business processes

    Concise project definition & contracting deliverables MIDAS = Turning Data into Gold

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    Project 1: MIDAS

    (June 2002-April 2003)

    Improving Aircraft Service Parts Demand Forecastsand Inventory Management using Scheduled

    Maintenance Data

    3 Main Tasks

    1. Integrate ACMS maintenance and AMMIS demand data

    2. Build Demand Forecast Models

    3. Policies for effective inventory management using

    maintenance data

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    MIDAS Methodology

    and Results

    Gathered extensive maintenance and demand data on41 critical components consisting of 50% of budget

    Created a Linear Programming model to link themaintenance data and demand data for these 41components

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    1308/08/0208/08/02TRBL

    05/08/0205/08/02TIME

    504/19/0203/05/0206/29/0107/20/01TRBL

    207/10/0106/25/0106/22/0106/29/01TRBL

    206/25/0106/15/0106/06/0106/06/01TIME

    205/23/0105/01/0108/28/0008/28/00TRBL

    208/25/0008/24/0012/14/9912/14/99TIME

    511/15/9911/08/9904/22/9904/22/99TIME

    503/22/9903/18/9904/15/9904/15/99TIME

    504/13/9903/11/9901/05/9901/05/99TIME

    512/02/9810/29/9810/28/9810/28/98TRBL

    207/07/9807/07/9807/30/9807/30/98TIME

    1211/24/9711/20/9707/09/9807/09/98TIME

    1210/17/9710/16/9711/25/9711/25/97TRBL

    pj

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    AMMIS demand DatabaseACMS maintenance Database

    Database Match Example

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    Young Parts Old Parts

    Failed parts at

    Warehouse

    IMs

    Component Re-Supply

    failed parts

    good parts

    ACMS Data

    AMMIS Data

    Good parts at

    Warehouse

    re-supply order

    L1

    L2

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    0%

    20%

    40%

    60%

    80%

    100%

    0 500 1000 1500 2000 2500 3000

    TSO

    CumulativeD

    istributio

    Oct. '98

    Oct. 2000

    Part-Age Distribution

    of Installed Parts

    Time Since Overhaul

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    SIGNAL Dependent

    BASE STOCK

    SIGNAL each period = # parts beyond Threshold age

    Correlate the SIGNAL and Demand over lead time

    Use the conditional distribution and costs to set

    BASE STOCK = Function(SIGNAL)

    Evaluate the optimal THRESHOLD

    Empirical Results showing cost impact on Inventory

    levels Proactive Inventory Management

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    Data Becomes Gold

    (1) LP tools used to match maintenance recordsand inventory

    (2) Part Age (accumulated flight hours)information improves demand forecast

    (3) Part Age based triggers for advance orders(4) Empirical results show cost reductions ranging

    from 20% to 70% for over 90 % of the partsexamined

    (5) The advance orders enable separation ofsupply processes for replenishment andadvance orders and can be used for budgeting

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    MIDAS Project

    Organizational Impact

    Establishment of OR Cell 4 new positions & summer interns

    Expanded budget planning-execution authority

    Demand forecasting & budgeting using MIDAS Partnering with Item Managers

    Supply Chain Management Business Solution Scalable, repeatable, supportable solution

    Up-to 100,000 stocking units Data warehouse

    AMMIS ACMS bridge

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    Project 2: REAP

    (June 2003-May 2004)

    Improving Scheduling of Repairs of Partsusing Scheduled Maintenance Data

    Main tasks:

    (1) Understand current repair release approaches usingempirical data

    (2) Develop Component Repair Capacity PlanningModels to choose the optimal repair mix includinginternal vs vendor repair choices.

    (3) Estimate the impact of adjusting releases onperformance of the repair shops

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    Components vs TSO

    The data shows that as part age increases, the number ofcomponents to be replaced and labor content increases

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    Role of LP Models

    The optimization models try to minimize costswhile maintaining safety stock of parts andcompleting contracted number of part repairs in

    the shop

    Models capture the impact of shop costs using

    vendor capacity, using overtime, coordinatingrepair releases with IMs etc.

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    REAP Optimization Model

    BXc

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    )(I

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    Min

    Demands composed ofadvance and regular orders

    Safety stock only needed for regular orders

    Budget constraint

    Resource availability constraint

    Minimize Sum of in-house repair, vendorrepair and overtimecapacity costs

    Where i is for NIIN andj for shop or resource.

    REAP M th d l

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    REAP Methodology

    and Key Results

    Data Analysis to link AMMIS ACMS Extended WO data

    Link TSO to labor, material data

    Optimal component repair capacity planning LP models

    Use models to project a 10% savings in repair costs

    REAP P j t

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    Developed 2 bill of material (BOM) lists based onTSO (young vs old failures)

    Linked BOM to extended work order

    Used BOM to assist with budget builds Shadow price of $ 6500 per hour for specificresources

    Adjusted resources and skills Release shop repairs to optimally use scarce shared repair

    resources Coordinate IM management

    Use material usage data to create realistic BOM

    REAP Project

    Organizational Impact

    U d f HH6 D l hi

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    Upgrade of HH65 Dolphin

    Helicopter

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    Restore Unrestricted Ops

    Restore safety, increase payload andoperational flexibility

    Retrofit HH65 with Turbomeca engines

    Improve gearbox durability upgrade 135 units Urgent requisition - 2 year completion mandate

    How do we accomplish this?

    Project 3: CRISP

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    Project 3: CRISP

    (June 2004-May 2005)

    CRISP required a model of the impact of: Availability of overhaul kits and parts

    Planned overhaul vs modification

    Associated spare parts required Overhaul interval

    Future overhaul

    Different levels of aircraft operation (C with G4, C

    with G2, switch back and forth, etc.) Resources available

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    Features of the MIP Model

    Model possible states of individual aircraft andindividual components

    Evolution of configuration over time

    Impact of overhaul or modification schedule Impact of constraints on level of flexibility (B,C-G2,C-

    G4, switchover)

    Weighted by upgrade level over horizon to maximize

    aircraft uptime Mixed Integer Program with network substructures

    Number of Flying Aircraft by

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    Number of Flying Aircraft by

    Type Over Time

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    Results of the Model

    Model results highlighted the impact of partavailability constraints on upgrade process

    Quantified impact of:

    level of aircraft operation flexibility onperformance

    manufacturer suggested mean time to

    overhaul for new components spare parts availability

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    CRISP Results and

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    CRISP Results and

    Organizational Impact

    Bottlenecks reduced by productivity changes Dual conversion paths

    Lean manufacturing

    Building block for additional analysis Spend plans

    Fleet sparing

    Catalyst for a successful on-time conversion

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    Deferred Maintenance Crisis

    Project 4: OPT

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    Coast Guards Big Iron 300 NM radius

    essential to cover EEZ Alaska and Caribbean

    Critical role in massive disaster relief

    As showcased during Hurricane Katrina ARSC HH60 Product Line

    PDM corner stone process every 4 yrs Logistics and Engineering Support

    Impending failure Mission scope creep following 9/11 Aging airframe and extensive corrosion

    Diminishing overhaul throughput Dropped from 9 in 1999 to low of 5 in 2005

    Project 4: OPT

    (June 2005-Present)

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    Impending Disaster

    The HH-60 deferred maintenance burden on USCGreached an all time high of $23.6 Million

    The Impending Train Wreck Operational Groundings Starting Mar 07

    24% of the Coast Guards operational fleet

    In order to begin a road to recovery, the HH-60 ProductLine needed to rapidly increase its throughput

    Original PDM Line

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    Start

    End

    Disassembly

    (7 days)

    Strip

    (7 days)

    Hull(58 days)

    Hull(58 days)

    Intermediate

    Paint (4 days)

    Assembly(54 days)

    Assembly(54 days)

    Final Paint

    (9 days)

    Fuel Ops(11 days)

    Ground Turns(12 days)

    Aircraft Flies in

    from Field Unit

    Aircraft Returns to

    Field Unit

    Original PDM Line

    Base Case

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    OPT Project Goals

    Capture the links between decisionsregarding resources

    inventory

    repair rules

    lead times

    Identify bottlenecks and the benefits ofimplementing improvements

    Design plans for MH-60T aircraft conversion

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    ARENA Simulation Model

    Captured three sets of flows in the system Aircraft cycles of field missions and PDM overhaul

    Component flows on flying aircraft, inventory andrepair

    Modules (within components) flow on components,field failures, inventory and vendor repair

    Each flow has different criteria Model includes component repair, vendor repair

    lead-times, contracts, priority rules, repairtriggers, etc.

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    OPT : Methodology

    Closed-loop Queuing and Inventory simulationmodel in ARENA Identified bottleneck processes

    Hull rework

    Final Assembly Capture impact of changes on the production line Impact of different rules for triggering module repair Impact of improving processing times through lean

    events Impact of inventory positioning (ARSC vs field) Impact of WIP inventory changes Impact of resource level changes

    Original PDM Line

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    2 Hull RepairVV

    2 Assembly0 hull inventory6aircrafts

    Hull stations 3Assembly stations 3

    7 aircrafts

    1 hullCC

    2 hulls

    8 aircrafts

    9.14

    9.649.14

    9.29

    9.31

    9.33

    9.31

    9.29

    4 aircrafts 5 aircrafts

    8.066.55

    Module life 500

    Module life 0

    9.2

    9.2

    Original PDM Line

    Base Case

    OPT Results and

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    OPT Results and

    Organizational Impact

    Reduced process cycle time 200 (+) working days down to an impressive 145

    Eliminated $5M annual outsourcing initiative

    Analysis used to drop plans to add 2 hulls at acost of $ 10 million (low throughput impact)

    This resulted in an increase in throughput by80% and a drop in deferred maintenance burdenfrom $23.6M to a mere $6.5M

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    Missions

    Aircraft Type

    Air-station

    Upgrade Repair

    Inventory ARSC Repair Vendor

    ARSC/E-city

    REAP

    MIDAS

    CRISP OPT

    Four Projects

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    Research Impact

    Each project led to aninnovative idea with solidOR analysis assummarized in the table

    Project Concept

    MIDAS Part Age basedInventory Levels(published in Operations

    Research)

    REAP Repair portfolio of ages

    CRISP Linking upgrade rates to

    future part demand,including effect offlexibility

    OPT Inventory, Capacity,contracts and closedloop supply chains

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    At the End of The Day

    Quantifiable, measurable, tangible benefits MIDAS inventory reduction for critical parts REAP 10% cost avoidance with $200MM budget CRISP - Unrestricted H65 Operations

    CRISP Capacity constraints highlighted Catalyst for Lean Manufacturing with $1.2MM savings

    CRISP - Redirect $9.9MM for component sparing Gear box, engine control system with long lead-time

    OPT Ended H60 deferred maintenance crisis 80% increase in overhaul throughput

    Organizational Impact

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    Organizational Impact

    of OR Projects

    Establishment of an Operations Research cell Several new employees and interns hired

    Provides critical decision support tools for planning repair andmaintenance activities

    Overwhelming increase in requests to analyze logistics issues All new projects expected to be grounded with OR analysis

    Supply Chain Management System (SCMS) being implementedto leverage information sharing and OR applications across theenterprise

    Future Initiatives: Aircraft availability simulation

    Social Impact

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    Social Impact

    of OR Projects

    Total cost savings in excess of $ 70 million CRISP returned the H-65 aircraft to a safe, reliable

    platform

    Prevented grounding of 9 HH-60 aircraft which would

    have resulted in loss of 6300 mission flight hours Replacing these aircraft would have cost USCG $270 million Long procurement lead-times and budgetary realities would

    make that infeasible

    True impact of grounded aircraft would have been a drop

    in mission readiness from 100% to 96% and missionexecution drop to 4%.

    The social cost would have been our inability to respondto natural disasters such as Hurricane Katrina 33,000 rescues, 5,000 by the HH-60

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    Questions?