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Analysis, Modeling & Simulation
Joe AdamoDepartment Head - Operations Analysis
Joyce WheelerManager – Operations Analysis
This document does not contain technical data as defined in the International Traffic in Arms Regulations (22 CFR 120.10) or the Export Arms Regulations (15 CFR 779.1).
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Agenda
Intro to Operations Analysis
What is Analysis, Modeling, and Simulation (AM&S)?
Case Studies
Summary
Questions & Discussion
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Operations Analysis
Operations Analysis is the analytical arm of
the Systems Engineering discipline. It is
the discipline of applying advanced
analytical techniques and processes to
provide information for better decision
making.
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Who Does Operations Analysis?
Operations Analysts come from a variety of disciplines Aeronautical Engineering Mechanical Engineering Electrical Engineering Computer Science and Engineering Mathematics, Physics Operations Research
Key Traits are Analytical Skills, Problem-Solving Capability, and Communication Skills
Degree
Masters53%
BS/BA42%
PhD5%
Approximately Approximately 600 Operations 600 Operations
Analysts in Analysts in Boeing IDS Boeing IDS
Approximately Approximately 600 Operations 600 Operations
Analysts in Analysts in Boeing IDS Boeing IDS
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What Do Operations Analysts Do?
The Realm of Designers – Measures of Performance Range Speed Payload
The Realm of Ops Analysts – Measures of Effectiveness
Survivability Number of Targets Detected Lethality – Number of Targets Destroyed Number of Information Packets Sent/Received
and Cost/Affordability
Ops Analysts Work with the Design Team to Ops Analysts Work with the Design Team to Ensure the System Can Do It’s Intended JobEnsure the System Can Do It’s Intended Job
An Aircraft Example:
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Tools and Methods
Commonly Used Techniques Modeling and Simulation Linear and nonlinear programming Queuing and other stochastic-
process models
Mathematical Modeling - Nearly all of these techniques involve the construction of a model that attempts to capture the behavior of the system being studied
Statistical methods
Econometric methods
Decision analysis
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Analysis Modeling and Simulation Defined
Analysis: Evaluating and assessing system performance, processes, and relationships to determine measures of importance such as effectiveness, performance, and reliability; typically using the results from models and simulations
Modeling: Creating representations (models) of systems including their processes, behaviors, and interactions
Simulation: Using (executing) models over time to investigate system performance
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Model vs. Simulation
Simulation - Execution of model over time
Example: Simulating the Earth’s Rotation
Model - Representation of the physical entity
Example: Static Model of the Earth
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Modeling and Simulation
Allows the analyst to conduct trade studies and answer “What if?” questions
Can assign values to the different model components and clarify the relationships among them
Values can be altered to examine what may happen to the system under different circumstances.
Inputs are modified and the model re-run to identify the best of levels for variables or combinations of design features
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Voice of the
Customer
DecisionAnalysis
ConstructiveSimulation
Interactive DigitalSimulation
VirtualEnvironment
Requirements DefinitionCustomer InvolvementManagement Understanding
Quick ToolsCustomer-approved simulations
Workload AssessmentSelected Controls/ DisplaysPilot in the Loop
Spectrum of Models and Simulations
IWARS
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Benefits of AM&SP
erc
ent
Product Life Cycle Phases
10
20
30
40
50
60
70
80
90
100
0
15% Cost Expended 85% of Cost Committed
70
8595
5
30Brief Window of Opportunity
Percent of Life-CycleCost Committed
Percent of ProgramCost Expended
ConceptRefinemt.
TechDevelop.
System Develop and Demonstration
Production and Operations and Support
Early Emphasis on Analysis Prevents Costly Early Emphasis on Analysis Prevents Costly Design Changes Later in The Development Design Changes Later in The Development
CycleCycle
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Demo
CheapFoods Distribution Center
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CheapFood Supermarkets has several stores in the St. Louis area.
However, each is supplied from a different warehouse out of state.
To cut costs, the owner of CheapFoods has decided to build a warehouse in the St. Louis area.
CheapFoods Distribution Center
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Ice Cream
Meat
Twinkies
CheapFoods only sells three items. However, each has to travel on its own truck because of certain constraints.
Requires freezer truck.
Requires refrigerator truck and is perishable.
Doesn’t require special truck and lasts forever.
Item Requirements: Supply Cost:
3x$
2x$
1x$1
2
3
Copyright©2006 Boeing. All Rights Resrved.
CheapFoods Products
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CheapFoods Territory
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Great! Now, supply costs for the supermarkets are at a minimum.
The owner can go home and buy that Ferrari he’s been wanting and the operations engineer can go back to his desk.
This was a VERY simplified example but it shows how a This was a VERY simplified example but it shows how a model can help provide insight into problem and identify model can help provide insight into problem and identify
a solutiona solution
Problem Solved!
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When Do You Use AM&S?
Customer Needs
Analysis
Define/DevelopConcept
Define Mission/ Function
Requirements
Define System Requirements &
Concepts
Perform Preliminary Definition
Production Support
Voice of the Customer / Needs Analysis
Requirements Analysis / Trade StudiesCost & AffordabilityEffectiveness Analysis / Trade Studies
Analysis of AlternativesAdvanced Supportability
Impact of TechnologiesCompetitive Assessment
Create New Business Capture New
Business Keep It Sold
AM&S is Needed Across the Product Life CycleAM&S is Needed Across the Product Life Cycle
PerformDetailed
Definition
Product Life CycleProduct Life Cycle
Test & Evaluation
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Decision AnalysisDecision Analysis
Decision Analysis Provides More Customer Interaction and a Better Product
Decision Analysis Provides More Customer Interaction and a Better Product
Multiple Suppliers
MultipleMultipleCustomersCustomers
ConflictingInterests
MultipleObjectives
ConsensusCommon TerminologyList of Potential Trades
PrioritiesDocumentation
Wants
Needs Desires
Wishes
Must Haves
Decision Analysis Techniques Are ToolsUsed to Solve Complex Problems
Through a Structured Process
Decision Analysis Techniques Are ToolsUsed to Solve Complex Problems
Through a Structured Process
CompetingAlternatives
Multiple Disciplines
Customer Needs Analysis / Requirements Definition
Understand Customer Needs Operational Requirements Budget constraints Network Environment (FAA, DOD, etc.)
Begin long term Customer Relationship
Deriving Requirements Developing plans for product design Ensuring Customer involvement throughout product life cycle
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PointEstimates
Ris
k F
acto
r
Low
Med
Hig
h
UCAV ATDPhase I
UCAV ATDPhase II
RR&OE EMD
1998
1Q 2Q 3Q 4Q
1999
1Q 2Q 3Q 4Q
2000
1Q 2Q 3Q 4Q
2001
1Q 2Q 3Q 4Q
2002
1Q 2Q 3Q 4Q
2003
1Q 2Q 3Q 4Q
2004
1Q 2Q 3Q 4Q
2005
1Q 2Q 3Q 4Q
Phase II Start EMD Start
Flt Demo 1 Flt Demo 2 Flt Demo 3 Flt Demo 4
RR&OE StartLast revision:
Flt Demo 5
Phase II End
UCAV decision aids flight demo
Deliver B-2 weapondelivery GWIS
JSF/UCAV Commonality Study
Establish Common AvionicsDevelopment Group
DEMPC UDS Formation Taxi/Flight (fixed geom, pos sep algorithms)
UDS Coordinated motion, variablegeometries / deconfliction algorithms
Global theater multi-level networking demo
BOLDSTROKE demos
Single simulatedvehicle distributedcontrol lab demo
Real-time software architecture& design demo
UCAV decision aids lab demo(contingency management)
Real-time distributed processing
AJ/LPI LOS C2 Demo
Software reuse metrics tracking
Demo of OMP & IntelligentMaintenance Aids /PMT & IMSS
Lab & flight demo - OMP/mission/vehiclesystems integration
AT3 or PLAID test on UCAV
Software reuse metrics tracking
SAR flight teston UCAV
Multi-sensor multi-source data fusion
AJ/LPI BLOS C2 -AJ GPS Demo
Air traffic mgt demo
Decision aids foroperator handofflab demo
Automated dynamic missionreplanning flight test demo
Drop multiple pre-planned smallbombs from MBR with full SMS
UDAS Algorithmic Control Flight Test Demo(Multi-Vehicle Coordinated Flight, CollisionAvoidance, Sensor Planner, Autorouter)
Loss of comm contingency flight demo Supplier software productivity demo
PHM/OMP
Fallback:
SuppliersBoeing
UCAV ATD RR&OEGov’t S&T
UCAV ATD Phase II
UCAV ATD Phase I
} UTP
Primary: Fully integratedsoftware functionality.
Decreased softwarefunctionality.
Unmanned Combat Air VehicleAdvanced Technology Demonstration
UCAV - ATD
Phase II - Affordability / LCC Plan
Prepared by:
David McCaughey (Boeing)
Concurred by:
Kurt Bausch (Boeing)
Steve Rast (SAIC)
Approved by:
Phil Panagos (Boeing)
Lt Col Michael Leahy (USAF)
AffordabilityPlan
$ $
HistoricalRegression
SupplierOptions
Unit C
ost JSF
UCAV
1/3 the cost of JSF
O&
S C
ost F-16
UCAV
75% Reduction from F-16
Time
$
CostTargets
Time
$
Time
$
Development /Investment Plans
Time
$
Focus:•System Cost Drivers
•Figures of Merit
•Effectiveness & Affordability Balance
• Investment Planning
CostUncertaintySimulation
LCC Probability
0%
20%
40%
60%
80%
100%
EMDProdO&S
$$
Kurt Bausch314-232-6917
PointEstimates
Ris
k F
acto
r
Low
Med
Hig
h
UCAV ATDPhase I
UCAV ATDPhase II
RR&OE EMD
1998
1Q 2Q 3Q 4Q
1999
1Q 2Q 3Q 4Q
2000
1Q 2Q 3Q 4Q
2001
1Q 2Q 3Q 4Q
2002
1Q 2Q 3Q 4Q
2003
1Q 2Q 3Q 4Q
2004
1Q 2Q 3Q 4Q
2005
1Q 2Q 3Q 4Q
Phase II Start EMD Start
Flt Demo 1 Flt Demo 2 Flt Demo 3 Flt Demo 4
RR&OE StartLast revision:
Flt Demo 5
Phase II End
UCAV decision aids flight demo
Deliver B-2 weapondelivery GWIS
JSF/UCAV Commonality Study
Establish Common AvionicsDevelopment Group
DEMPC UDS Formation Taxi/Flight (fixed geom, pos sep algorithms)
UDS Coordinated motion, variablegeometries / deconfliction algorithms
Global theater multi-level networking demo
BOLDSTROKE demos
Single simulatedvehicle distributedcontrol lab demo
Real-time software architecture& design demo
UCAV decision aids lab demo(contingency management)
Real-time distributed processing
AJ/LPI LOS C2 Demo
Software reuse metrics tracking
Demo of OMP & IntelligentMaintenance Aids /PMT & IMSS
Lab & flight demo - OMP/mission/vehiclesystems integration
AT3 or PLAID test on UCAV
Software reuse metrics tracking
SAR flight teston UCAV
Multi-sensor multi-source data fusion
AJ/LPI BLOS C2 -AJ GPS Demo
Air traffic mgt demo
Decision aids foroperator handofflab demo
Automated dynamic missionreplanning flight test demo
Drop multiple pre-planned smallbombs from MBR with full SMS
UDAS Algorithmic Control Flight Test Demo(Multi-Vehicle Coordinated Flight, CollisionAvoidance, Sensor Planner, Autorouter)
Loss of comm contingency flight demo Supplier software productivity demo
PHM/OMP
Fallback:
SuppliersBoeing
UCAV ATD RR&OEGov’t S&T
UCAV ATD Phase II
UCAV ATD Phase I
} UTP
Primary: Fully integratedsoftware functionality.
Decreased softwarefunctionality.
Unmanned Combat Air VehicleAdvanced Technology Demonstration
UCAV - ATD
Phase II - Affordability / LCC Plan
Prepared by:
David McCaughey (Boeing)
Concurred by:
Kurt Bausch (Boeing)
Steve Rast (SAIC)
Approved by:
Phil Panagos (Boeing)
Lt Col Michael Leahy (USAF)
AffordabilityPlan
$ $
HistoricalRegression
SupplierOptions
Unit C
ost JSF
UCAV
1/3 the cost of JSF
O&
S C
ost F-16
UCAV
75% Reduction from F-16
Time
$
CostTargets
Time
$
Time
$
Development /Investment Plans
Time
$
Focus:•System Cost Drivers
•Figures of Merit
•Effectiveness & Affordability Balance
• Investment Planning
CostUncertaintySimulation
LCC Probability
0%
20%
40%
60%
80%
100%
EMDProdO&S
$$
Kurt Bausch314-232-6917
Life Cycle Cost/Total Ownership Cost Design to Cost
Best Value
AffordabilityAffordability
Cost-Effectiveness Trades
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Analysis of Alternatives
Work with customer to identify design, configuration, or approach alternatives
Evaluate operational effectiveness of each alternative
Evaluate cost considerations for each alternative Compare cost and performance for each
alternative Provide customers with insight to desired options Provide justification and support for selecting the
preferred alternative
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National Air Space - Wide Delay / Capacity Analysis for BCA Flight Operations Strategy
Analysis of Alternatives
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Statement of Problem and Alternatives
• Quantify, in terms of reduced system delays, the benefits of the alternative airport capacity-increasing concepts
Alternative 1: Navigation improvements
Alternative 2: Alternative 1 plus landing system improvements
Alternative 3: Alternative 2 plus Air Traffic Control (ATC) improvements
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Modeling Approach
Boeing National Flow Model (NFM)
National Air Space (NAS)-wide traffic analysis for a single day
Simulation with a network of queues
Queues for capacitated elements
Input flight schedules and capacities
Output delay statistics
Directly addressed delay propagationNFM Network of
Queues
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Assumptions
Used Current Market Outlook-based future schedule generation capability to analyze traffic levels for y2000, 2010, 2015, and 2020
Annualized results by taking the weighted average of six “representative” days
Assumed no airline schedule re-planning, including no flight cancellations
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Conclusion and Recommendations
Successfully supported benefits analysis comparing the relative effectiveness of the alternatives
ATC improvements (associated with Alt 3) were shown to have the greatest benefit
The 20-25% capacity increases of Alt 3 are magnified into a 50% reduction in delays when confronted with y2020 traffic
0
10
20
30
40
50
60
70
80
2000 2010 2015 2020
Year
Av
e A
rriv
al D
ela
y (
min
)
baseline
alt1
atl2
alt3
Better
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Benefits to Stakeholders
Methodology can be used to show how capacity increases translate to end-user benefits in terms of decreased delays
Methodology is more credible than alternative approaches because it considers delay propagation, airport inter-dependencies and weather conditions correlated between airports
Helps direct executive-level decision making in terms of which alternatives are most cost-effective to pursue
Helps BCA to price avionics products Helps influence air traffic service providers to improve system
performance so Boeing can sell more airplanes Provides analytical evidence of benefits that may be used
in presentations to airline customers
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• Prognostics & Health Management
• Opportunistic maintenance
• Interactive Tech Manuals
• Prognostics & Health Management
• Opportunistic maintenance
• Interactive Tech Manuals
• Flexible support• Flexible support
• Proactive manufacture
• Proactive supply
• Autonomic distribution
• Spares usage & trends
• Projected spares needs
POLPipelines
CODResupply
GroundDeliveries
Repair&
Overhaul
AircraftVehicle
EquipmentGeneration &Maintenance
IntermediateRepairOEM
• 24/7 Response centers
• Digital Engineering Links
• 24/7 Response centers
• Digital Engineering Links
Advanced Supportability AM&S
Supply Chain Management
Maintenance Management
Analysis
Supply Management
Analysis
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NASA Cargo Processing for the Shuttle and Space Station
Multi-Purpose Logistics Module(MPLM)
Assembly Process
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Statement of Problem
With the elements of the International Space Station being delivered to Earth orbit, Multiple cargo missions were needed
NASA experienced complex delays and problems in loading the MPLM and processing cargo for the Shuttle missions
Needed to find the problem areas and test potential solutions
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Potential Alternative Solutions
Current process had not yet impacted a Shuttle launch date Excessive overtime and “last minute
heroics” to meet schedule
Either continue current process or find alternative
Complete “re-write” of current procedures and processes at high cost
Determine problem areas and test solutions
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Modeling Approach
Developed model to replicate current processes including current delay factors
Used Monte Carlo to replicate process performance ranges
Showed sensitivity of each process step to change and effect on overall process efficiency
Tested potential changes in process and formulated course of action for correction
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Conclusion and Recommendations
Determined a 60% increase in efficiency to meet established schedules was possible
Identified process areas to target and tested possible solutions
Replicated new process changes
Recommended four significant changes in cargo processing – low cost with high return
Increased Efficiency Led to Boeing Win on Renewal of Increased Efficiency Led to Boeing Win on Renewal of Cargo Processing Contract at Kennedy Space CenterCargo Processing Contract at Kennedy Space Center
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Advanced Supportability AM&S Benefits
Help identify, evaluate and integrate new technologies to aid support concepts
Identify candidate new support options to improve response time and reduce cost
Explore Sustainment options early Identify required spares and staging requirements Experiment with and predict support requirements Ensure support options are well explored Demonstrate to customer benefits of support plan
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Test & Evaluation (T&E): Virtual Integrated Simulation Network
Concept of Operations Systems-of-Systems Operators Interoperability Tactical S&R/C2/BM\ Linked to FCS Joint
Virtual Battlescape
Level 3: Operational Level 3: Operational LevelLevelBICBIC
Level 3: Operational Level 3: Operational LevelLevelBICBIC
FAA Advanced NCO
Command & Control BMC4ISR Operators Interoperability
Level 2: Tactical Level 2: Tactical Level Level VWCVWC
Level 2: Tactical Level 2: Tactical Level Level VWCVWC
Level 1: Systems LevelLevel 1: Systems LevelFlight Sim., Mesa, ITDL ,VWC Flight Sim., Mesa, ITDL ,VWC Huntsville, Philadelphia, CoSHuntsville, Philadelphia, CoS
Level 1: Systems LevelLevel 1: Systems LevelFlight Sim., Mesa, ITDL ,VWC Flight Sim., Mesa, ITDL ,VWC Huntsville, Philadelphia, CoSHuntsville, Philadelphia, CoS
Operators AWACS Canard Rotor Wing Space Based Radar /
Space Assets Unmanned Combat Air
Vehicle / UAV
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Virtual T&E Benefits
Work with customer to anticipate problems with design parameters
Verify that detailed design meets customer requirements
Understand sensitivity to performance and cost
Anticipate problems before flight test
Predict Test & Evaluation performance
Minimize live test through virtual T & E and reduce overall test and evaluation cost
F/A-18 Saved 155 Test Flights F/A-18 Saved 155 Test Flights through Judicious Use of Virtual through Judicious Use of Virtual
T&ET&E
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Production Design AM&S
Paint Prep Facility Layout
Graphite Lay-upProduction Area
Process Simulatio
n
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Anticipate and correct Producibility problems Model production flow Identify bottlenecks Identify recommended changes to production
line Experiment with production improvements
without interfering with current production schedule
GP42656027.ppt
Production Design AM&S Benefits
This document does not contain technical data as defined in the International Traffic in Arms Regulations (22 CFR 120.10) per 125.4(b)(13) or the Export Arms Regulations (15 CFR 779.1) APPROVED FOR PUBLIC RELEASE 12/13/2004
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AM&S Summary
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Benefits of AM&S
Economical method of testing a broad array of “What Ifs”
Provides information to help balance Performance and Cost
Enables the demonstration of baseline capabilities under a wide variety of environments/scenarios
Provides the customer a consistent and transparent basis for your decisions
Strengthens the customers perception of how decision are made at Boeing
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Competitive Advantage
AM&S provides an early understanding of system capabilities, performance, and effectiveness
AM&S provides information as to which design features or system capabilities “buy” their way on to the system - Cost as an Independent Variable (CAIV)
Simulation allows head to head comparison of competitive designs before downselect
Simulation provides the customer with the opportunity to experience how the product will perform
AM&S Allows the Customer to “See” How the System Will AM&S Allows the Customer to “See” How the System Will PerformPerform
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Questions?