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SEAri Short Course Series Course: PI.26s Epoch-based Thinking: Anticipating System and Enterprise Strategies for Dynamic
Futures Lecture: Lecture 10: Highlights of Quantitative Epoch-based Implementations Author: Adam Ross and Donna Rhodes Lecture Number: SC-2010-PI26s-10-1 Revision Date: July 24, 2010 This course was taught at PI.26s as a part of the MIT Professional Education Short Programs in July 2010 in Cambridge, MA. The lectures are provided to satisfy demand for learning more about Multi-Attribute Tradespace Exploration, Epoch-Era Analysis, and related SEAri-generated methods. The course is intended for self-study only. The materials are provided without instructor support, exercises or “course notebook” contents. Do not separate this cover sheet from the accompanying lecture pages. The copyright of the short course is retained by the Massachusetts Institute of Technology. Reproduction, reuse, and distribution of the course materials are not permitted without permission.
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Lecture 10 Highlights of Quantitative Epoch-Based Implementations
Dr. Donna H. Rhodes Dr. Adam M. Ross [email protected] [email protected]
Massachusetts Institute of Technology
[PI.26s] Epoch-Based Thinking: Anticipating System and Enterprise Strategies for Dynamic Futures
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Outline
• Buying a house • Designing a satellite radar system • Choosing an operationally responsive
multi-concept disaster surveillance system
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Buying a house (simple example)
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1. Context Definition
• Bob is buying a house • He wants a nice place
to live that won’t break the bank
Example from Viscito 2009
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2. Design Formulation
• Bob chooses two attributes
• He performs a DVM on possible attributes
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3. Epoch Characterization
• Bob also identifies two uncertainties – Increased size of
future family – Parents may move
in
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4. Tradespace Evaluation
• Bob uses his design variables to make a model
• He evaluates the model for three epochs
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Cont.
• Bob’s epochs have clusters of designs • Beds and Floors drive the design space,
baths has a small effect on cost and utility
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5. Multi-Epoch Analysis
• Bob identifies two transition rules – Add a floor – Add a room
• He also looks at the Pareto Front
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Cont.
• The Pareto Front for each epoch is similar, but not identical
• FOD and NPT for each design is calculated
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6. Era Construction
• Bob makes an era • VWFO is calculated for
the designs • Looks like Bob should
choose design # 4
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7. Path Analysis
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Selecting an operationally responsive multi-
concept disaster surveillance system (another complex example)
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Stakeholders Firefighter
ORS Owner
Multi-Concept Operationally Responsive Disaster Surveillance
Acquisition Cost Time Between AOI
Price/Day Max % of AOI Covered
Cost/Day Time to Max Coverage
Responsiveness Imaging Capability
Time to IOC Data Latency
Attributes (Firefighter/ORS Owner)
Design Concepts • Aircraft • Satellite • Sensor Swarm • SoS designs consisting of any two of above
• Epoch Analysis
• Pareto Trace
Pareto Trace for ORS Owner v. Cost
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Attributes for Selected Stakeholders
Attributes were generated by the design team by proxy for Firefighters and ORS Owner
Responsiveness (min) 0 168
Util
ity
Utility Curve 1
Imaging (NIIRS level) 5 9
Util
ity
Utility Curve 1
0
Attribute Name Attribute Definition
Firefighter Attribute Range
ORS Owner Attribute Range
Attribute Units
Acquisition Cost Cost to acquire system
0-800 0-1000 $M
Price/day Amortized price paid for operations per day
0-25 N/A $K/day
Cost/day Cost of operations per day
N/A 0-2500 $K/day
Time to IOC Time between initial need for system and initial operating capability
0-180 0-180 days
Responsiveness Time from request to initial observation of AOI
0-168 0-168 hours
Max % AOI Covered
Percentage of AOI imaged by system
5-100 5-100 percentage
Time to Max Coverage
Time to maximum coverage of AOI
0-1440 0-1440 minutes
Time between AOI Time from AOI_1 to AOI_2
0-120 0-120 minutes
Imaging Capability NIIRS level of images
5-9 5-9 NIIRS level
Data Latency Time between start of imaging to reception of images by user
0-360 0-360 minutes
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First-Pass Model Single System Concepts
Costs for each Stakeholder for each AOI
Constants
Concept Models
Aircraft
LEO Sat
Sensor SwarmFinance Model
Att->UtilityAttributes
Costs
Utility for each Stakeholder for each AOI
Design Space
Stakeholder Info AOI info
Costs for each Stakeholder for each AOI
Constants
Concept Models
Aircraft
LEO Sat
Sensor SwarmFinance Model
Att->UtilityAttributes
Costs
Utility for each Stakeholder for each AOI
Design Space
Stakeholder Info AOI info
First-Pass Model Flow
Concept Design Number
of Assets
Wavelength Aperture Size (m)
Aircraft ScanEagle 1 IR 0.04
Sensor Swarm Camera Swarm 50 IR 0.04
Comparison of diverse concepts on tradespace
Pareto Set includes multiple concepts
Utility-Utility Tradespace
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Epoch Changes in Stakeholder Preference
Original Attribute Relative Weights Changed Attribute Relative Weights
1.00 ScanEagle and Camera Swarm (150 units)
SoS
1.00 RQ-11 Raven UAV and Camera Swarm (150 units)
SoS
1.00 ScanEagle Aircraft
Normalized Pareto Trace (N=5)
Description Concept
Severe disaster Nominal disaster
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Second-Pass Model Stakeholder Info
Firefighter 0-24 hours
95° 50´N - 97° 10´N
16°40´N – 18°0´N
Cyclone Nargis disaster, Yangon area, Burma
3
0-20 hours
116°41´N - 116°59´N
32°55´N - 33°22´N
Witch Creek Fire, CA
2
0-12 hours
89°50´W - 90°15´W
29°50´N - 30°05´N
Hurricane Katrina disaster area, LA
1
Time Longitude Range
Latitude Range
Description AOI Num
Area of Interest Info
• Aircraft and Satellite selected for detailed modelling • Both legacy and new designs included • AOI definition more refined compared to first-pass • Stakeholder utility curves are non-linear • SoS modelling is similar to first-pass, using combination of Aircraft and Satellite
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Epoch-Era Analysis for Change in AOI
Katrina Witch Creek
1
0.99
0.98
0.96
0.95
Myanmar
OR
S O
wne
r
0.95 0.96 0.98 0.99 1 Firefighter
0.95 0.96 0.98 0.99 1 Firefighter
0.95 0.96 0.98 0.99 1 Firefighter
Aircraft Satellite SoS
1.00 Aircraft (UAV w/ piston, IR) + satellite (800 km, sun-synch, IR)
SoS 925
0.67 Aircraft (Cessna, IR) + satellite (120 km, 23 deg, IR)
SoS 1061
1.00 120 km sun-synch orbit, IR payload Satellite 2764
1.00 ScanEagle Aircraft 2116
Normalized Pareto Trace (N=3)
Description Concept Design Num
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Summary
• Epoch-based thinking has been applied to several case studies – Housing buying – Satellite radar system designing – Disaster surveillance system selecting – Design of Off-shore Patrol Cutter* – Design of an Army unmanned vehicle System of
System** • Additional cases on-going (this is an active area
of research)
* SDM Thesis, Schofield, D. (2010)
** SDM Thesis, Koo, K (2010)