Operations Research Enhanced Supply Chain Management at the US Coast Guard Aircraft Repair and Suppl

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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
Port Angeles 3 HH-65C
Cape Cod 4 HU-25C 4 HH-60J
Traverse City 5 HH-65C
Astoria 3 HH-60J
North Bend 5 HH-65C
Detroit 5 HH-65C
Atlantic City 10 HH- 65C
Humboldt Bay 5 HH-65C
Washington 1 C-37 1 C-143
Sacramento 4 HC-130H
San Francisco 4 HH-65C
Elizabeth City 4 HC-130H 5 MH60-J 1 HC-144A
ATC Mobile 4 HU-25A 7 HH-65C 3 MH-60J

Los Angeles 3 HH-65C

Savannah 5 HH-65C
San Diego 3 MH-60J
Houston- 4 HH65C
HITRON 8 MH-68A
New Orleans- 5 HH-65C

Kodiak 5 HC-130H 4 HH-65C 4 MH-60J
Corpus Christi 3 HU-25C 3 HH-65C
Miami 6 HU-25D 9 HH-65C
Clearwater 6 HC-130H 9 HH-60J
Barbers Point 4 HC-130H 4 HH-65C

Borinquen 4 HH-65C
Sitka 3 HH-60J
HC-130 22 Operational - 5 Support / HU-2517
Operational - 8 Support / HH-60 34 Operational
- 7 Support / HH-65 84 Operational - 11 Support
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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 for
  over 6000 parts

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Scheduled Maintenance
Un-Scheduled Failures
ACMS Data
Maintenance Shop
Air Station Repair
AMMIS Data

• Warehouse
• - Air Station
• - ARSC

Item Managers Procurement Specialists
failed parts
Component Repair (Internal)
good parts
Vendors (OGA Commercial)
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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
  Forecasts and Inventory Management using
  Scheduled Maintenance Data
• 3 Main Tasks
• Integrate ACMS maintenance and AMMIS demand data
• Build Demand Forecast Models
• Policies for effective inventory management using
  maintenance data

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MIDAS Methodology and Results

• Gathered extensive maintenance and demand data on
  41 critical components consisting of 50 of
  budget
• Created a Linear Programming model to link the
  maintenance data and demand data for these 41
  components

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Database Match Example
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ACMS Data
Young Parts
Old Parts
Good parts at Warehouse
Failed parts at Warehouse
L1
IMs
L2
AMMIS Data
failed parts
good parts
re-supply order
Component Re-Supply
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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

• LP tools used to match maintenance records and
  inventory
• Part Age (accumulated flight hours) information
  improves demand forecast
• Part Age based triggers for advance orders
• Empirical results show cost reductions ranging
  from 20 to 70 for over 90 of the parts
  examined
• The advance orders enable separation of supply
  processes for replenishment and advance 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 Parts using
  Scheduled Maintenance Data
• Main tasks
• Understand current repair release approaches
  using empirical data
• Develop Component Repair Capacity Planning Models
  to choose the optimal repair mix including
  internal vs vendor repair choices.
• Estimate the impact of adjusting releases on
  performance of the repair shops

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Components vs TSO
The data shows that as part age increases, the
number of components to be replaced and labor
content increases
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Role of LP Models

• The optimization models try to minimize costs
  while maintaining safety stock of parts and
  completing contracted number of part repairs in
  the shop
• Models capture the impact of shop costs using
  vendor capacity, using overtime, coordinating
  repair releases with IMs etc.

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REAP Optimization Model
Minimize Sum of in- house repair, vendor repair
and overtime capacity costs
Resource availability constraint
Demands composed of advance and regular orders
Safety stock only needed for regular orders
Budget constraint
Where i is for NIIN and j for shop or resource.
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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

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REAP Project Organizational Impact

• Developed 2 bill of material (BOM) lists based on
  TSO (young vs old failures)
• Linked BOM to extended work order
• Used BOM to assist with budget builds
• Shadow price of 6500 per hour for specific
  resources
• 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

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Upgrade of HH65 Dolphin Helicopter
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Restore Unrestricted Ops

• Restore safety, increase payload and operational
  flexibility
• Retrofit HH65 with Turbomeca engines
• Improve gearbox durability upgrade 135 units
• Urgent requisition - 2 year completion mandate
• How do we accomplish this?

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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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States and Transitions
NRFI G2 NRFI G4 In Repair G2 In Repair
G4 RFI G2 RFI G4 G2 on B Aircraft G2 on
C Aircraft G4 on C Aircraft Grounded
B Grounded C In mod-line In PDM line
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Features of the MIP Model

• Model possible states of individual aircraft and
  individual 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

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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 part
  availability constraints on upgrade process
• Quantified impact of
• level of aircraft operation flexibility on
  performance
• manufacturer suggested mean time to overhaul for
  new components
• spare parts availability

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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
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Project 4 OPT (June 2005-Present)

• 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

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Impending Disaster

• The HH-60 deferred maintenance burden on USCG
  reached 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
  Product Line needed to rapidly increase its
  throughput

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Original PDM Line Base Case
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OPT Project Goals

• Capture the links between decisions regarding
• resources
• inventory
• repair rules
• lead times
• Identify bottlenecks and the benefits of
  implementing 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 and
  repair
• 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, repair
  triggers, etc.

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OPT Methodology

• Closed-loop Queuing and Inventory simulation
  model 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

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Original PDM Line Base Case
9.14
9.64
Assembly stations 3
Hull stations 3
9.14
8.06
6.55
2 Hull Repair VV 2 Assembly 0 hull
inventory 6aircrafts
4 aircrafts
5 aircrafts
9.31
1 hull
CC
9.29
9.33
7 aircrafts
9.29
Module life 500
2 hulls
9.2
8 aircrafts
Module life 0
9.31
9.2
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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 a
  cost of 10 million (low throughput impact)
• This resulted in an increase in throughput by 80
  and a drop in deferred maintenance burden from
  23.6M to a mere 6.5M

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Four Projects
Missions
Air-station
CRISP
OPT
Aircraft Type
MIDAS
Upgrade
Repair
ARSC/E-city
Inventory
ARSC Repair
Vendor
REAP
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Research Impact

• Each project led to an innovative idea with solid
  OR analysis as summarized in the table

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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

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Organizational Impactof OR Projects

• Establishment of an Operations Research cell
• Several new employees and interns hired
• Provides critical decision support tools for
  planning repair and maintenance 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
  implemented to leverage information sharing and
  OR applications across the enterprise
• Future Initiatives Aircraft availability
  simulation

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Social Impactof 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
  mission execution drop to 4.
• The social cost would have been our inability to
  respond to natural disasters such as Hurricane
  Katrina
• 33,000 rescues, 5,000 by the HH-60

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Questions?