Introduction to MATE-CON
Presented By
Hugh McManus
Metis Design
3/27/03
A method for the front end
•
•
•
MATE Architecture Tradespace Exploration
•  A process for understanding complex solutions to complex problems
ICE Integrated Concurrent Engineering
•  Rapid Conceptual/Preliminary Design Method
Allows informed upfront decisions and planning
Most relevant to processes
in these phases"
Concept
Development
System-Level
Design
Phases of Product Development
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Detail
Design
Testing and
Refinement
Production
Ramp-Up
From Ulrich & Eppinger, Product Design and
Development, 1995
©Massachusetts Institute of Technology McManus- 032603 2
Developing A Trade Space
Mission
Concept
•
•
•
•
•
•
Understand the
Mission
Create a list of
“Attributes”
Interview the
Customer
Create Utility Curves
Develop the design
vector and system
model
Evaluate the potential
Architectures
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Attributes
Define Design
Vector
Develop System
Model
Calculate
Utility
Estimate
Cost
Architecture
Trade Space
©Massachusetts Institute of Technology McManus- 032603 3
What is an Architecture Trade
Space?
X-TOS"
Km
•  Small low-altitude
science mission"
DESIGN VARIABLES: The architectural
trade parameters
•
Physical Spacecraft Parameters
•
Orbital Parameters
Apogee altitude (km)
Perigee altitude (km)
Orbit inclination
–
–
–
–
–
Antenna gain
communication architecture
propulsion type
power type
delta_v
web.mit.edu/lean
Each point is
a specific
architecture
150-1100
150-1100
0, 30, 60, 90
–
–
–
Total Lifecycle Cost
($M2002)
Assessment of the utility and cost of a large
Number
ofofArchitectures
Explored:
50488
Number
Architectures
Explored:
50488
space
of possible
system
architectures
©Massachusetts Institute of Technology McManus- 032603 4
Using the Trade Space to Evaluate
Point Designs
TPF"
•  Terrestrial Planet
Finder - a large
astronomy system"
•  Design space:
Apertures
separated or
connected, 2-D/3D, sizes, orbits"
•  Images vs. cost"
Designs from traditional process"
From Jilla, 2002
web.mit.edu/lean
[Beichman et al, 1999]"
©Massachusetts Institute of Technology McManus- 032603 5
Using Architecture Models to
Understand Policy Impacts
Cost of US Launch Policy: B-TOS Case Study Using Min Cost Rule
1
Policy
increases
cost!
Utility
Utility"
0.995
D
100% of B-TOS architectures have cost
increase under restrictive launch policy
for a minimum cost decision maker"
C
B
0.99
Restrictive launch policy!
Unrestrictive launch policy!
B-TOS Case Study: Probability of Success Impact of 1994 U.S. Space Transportation Policy
for a Minimum Cost Decision Maker
E
1
0.985
D'
D
E'
A
C'
C
0.995
0.98
0
100
200
300
400
Cost"
500
600
700
800
Lifecycle Cost ($M)
•  Swarm
of small
sats.
98%
of B-TOS
architectures
have
increased launch
doing
observation"
probability
success under
•  Utility forofmultiple
restrictive
launch policy for a
missions"
minimum cost decision
maker"
Utility
B-TOS"
Min Cost ALL
0.99
Utility"
Min Cost US
0.985
0.98
0%
Policy increases
launch probability
of success!
10%
20%
30%
40%
50%
B
A'
A
70%
80%
90%
B-TOS Architecture Probability of Launch Success (Lifecycle total)
Probability of Success"
Restrictive U.S.-only Launch Policy
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60%
B'
Unrestrictive Launch Policy
©Massachusetts Institute of Technology McManus- 032603 6
From Weigel, 2002
100%
Using Architecture Models to
Consider Uncertainty
TechSat"
Cost
Pd
Arch
B
9.64
0.956
Arch
A
9.70
0.978
Arch A
Arch B
Cost
Pd
Arch
B
4.25
0.997
Arch
A
4.28
0.998
•  Constellation of
satellites doing
observation
of moving
Performance
objects
the ground"
andonCost
•  Uncertainties driven
move
by instrument
performance/cost"
differently for
different
architectures
under
uncertainty
[Martin, 2000]"
web.mit.edu/lean
©Massachusetts Institute of Technology McManus- 032603 7
From Walton, 2002
Assessing Robustness and
Adaptability
•
•
•
Pareto front shows trade-off of accuracy and cost
Determined by number of satellites in swarm
Could add satellites to increase capability
1
E
D
C
Utility
Utility
0.995
Most desirable architectures
B
0.99
0.985
A
B-TOS"
"
0.98
100
Cost
1000
Lifecycle Cost ($M)
web.mit.edu/lean
©Massachusetts Institute of Technology McManus- 032603 8
Questioning User Desires
•
•
Best low-cost mission do only one job well
More expensive, higher performance missions require more
vehicles
Higher-cost systems can do multiple missions
Is the multiple mission idea a good one?
A-TOS"
•  Swarm of very
simple satellites
taking ionospheric
measurements"
•  Several different
missions"
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High Latitude Utility
•
•
©Massachusetts Institute of Technology McManus- 032603 9
Equatorial Utility
Understanding Limiting
Physical or Mission constraints
4000.00
SPACETUG
"
Low Biprop
3500.00
•  General
Medium Biprop
High Biprop
purpose
orbit
Extreme Biprop
transfer
Low Cryo
vehicles
"
Medium Cryo
•  Different
High Cryo
propulsion
Extreme Cryo
systems
and
Low Electric
grappling/
Medium Electric
High Electric
observation
Extreme Electric
capabilities"
Low Nuclear
•  Lines
show
Medium Nuclear
increasing fuel
High Nuclear
mass
fraction"
Extreme Nuclear
Cost (M$)
3000.00
2500.00
2000.00
1500.00
1000.00
500.00
0.00
0.00
0.20
0.40
0.60
0.80
1.00
Utility (dimensionless)
Hits a “wall” of either physics (can’t change!) or utility (can)
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©Massachusetts Institute of Technology McManus- 032603 10
Integrated Concurrent Engineering
(ICE)
•
•
•
•
•
•
ICE techniques from Caltech and JPL
Linked analytical tools with human experts in the loop
Very rapid design iterations
Result is conceptual design at more detailed level than
seen in architecture studies
Allows understanding and exploration of design
alternatives
A reality check on the architecture studies - can the
vehicles called for be built, on budget, with available
technologies?
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©Massachusetts Institute of Technology McManus- 032603 11
ICE Process (CON with MATE)
ICE Process
Leader
“Chairs” consist of
computer tool AND
human expert
MATE
Mission
Cost
Power
Key system
attributes passed to
MATE chair, helps to
drive design session
Systems
Propulsion
Thermal
ICE-Maker
Server
Communication
Structures
Configuration
Command
and Data
Handling
Attitude
Determination
and Control
Electronic
communication
between tools and
server
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Reliability
•
•
•
Directed Design Sessions
allow very fast
production of preliminary
designs
Traditionally, design to
requirements
Integration with MATE
allows utility of designs
to be assessed real time
Verbal or online chat
between chairs
synchronizes actions
©Massachusetts Institute of Technology McManus- 032603 12
SPACETUG Tug Family
(designed in a day)
Bipropellant
Wet Mass: 11689 kg
Electric – One way
Wet Mass: 997 kg
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Cryogenic
Wet Mass: 6238 kg
Electric – Return Trip
Wet Mass: 1112 kg
©Massachusetts Institute of Technology McManus- 032603 13
Conceptual design details
LEO Tender 1
mass summary
Power System Mass Breakdown
Solar array
mass
66%
0%
1%
16%
ADACS (dry)
C&DH
5%
3%
2%
52%
21%
Link
Power
Propulsion (dry)
Structures & Mechanisms
Thermal
Mating System
Payload
Propellant
Pressurant
0%
Cabling mass
6%
PMAD mass
9%
Select solar array material:
Detailed information can be drawn from subsystem sheets,
including efficiencies, degradations
temperature tolerances, and areas
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Minimum efficiency
Maximum efficiency
Nominal temperature
Temperature loss
Performance degredation
Minimum temperature
Maximum temperature
Energy density
Battery mass
19%
6 (InGaP/GaAs/Ge)
Triple Junction
24.5
28.0
28.0
0.5
2.6
0.5
85.0
25.0
%
%
C
%/deg C
% / year
C
C
W / kg
Solar array mass
150.6685167 kg
Total solar array area
9.965098159 m^2
# of solar arrays
2#
of Technology
Individual solar array area©Massachusetts Institute
4.98254908
m^2McManus- 032603 14
Trade Space Check
500
450
400
Biprop
300
Cost
350
250
Storable Biprop
Cryo
Nuclear
Electric
Biprop GEO tug
200
Electric GEO cruiser
Cryo Cryo GEO tug
SCADS
150
Electric GEO Tug
100
Electric 50
0
0
0.2
0.4
Utility
0.6
0.8
1
The GEO mission is near the “wall” for conventional propulsion
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©Massachusetts Institute of Technology McManus- 032603 15
Changes in User Preferences Can
be Quickly Understood
Weight Factors of each Attribute (k values)
Architecture
trade space
reevaluated
in less than
one hour
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
Original
Latency
Latitude
Revised
Equator
Time
User changed
preference
weighting for
lifespan
X-TOS"
"
web.mit.edu/lean
Lifespan
Altitude
Original
y
t
i
l
i
t
U
Revised
0.8
0.8
0.7
0.7
0.6
y
t
i
l
i
t
U
0.5
0.6
0.5
0.4
0.4
0.3
0.3
0.2
40
42
44
46
48
50
52
Lifecycle Cost ($M)
54
56
58
60
0.2
40
42
44
46
48
50
52
54
56
Lifecycle Cost ($M)
©Massachusetts Institute of Technology McManus- 032603 16
58
60
MATE-CON: Emerging Capability
•
Linked method for progressing from vague user needs to conceptual/
preliminary design very quickly
•
•
MANY architectures, several/many designs considered
Understanding the trades allows selection of robust and adaptable
concepts, consideration of policy, risk.
User
Needs
MATE
Architecture
Evaluation
ICE
Conceptual
Design
Robust
Adaptable
Concepts
Months, not Years
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©Massachusetts Institute of Technology McManus- 032603 17