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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.

Lecture 10 Highlights of Quantitative Epoch-Based Implementations

Dr. Donna H. Rhodes Dr. Adam M. Ross rhodes@mit.edu adamross@mit.edu

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)