McManus, Hugh

DSpace@MIT

Introduction to MATE-CON  Presented By Hugh McManus Metis Design 3/27/03 ©Massachusetts Institute of Technology McManus- 032603  2 web.mit.edu/lean 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 Concept Development System-Level Design Detail Design Testing and Refinement Production Ramp-Up From Ulrich & Eppinger, Product Design and Development, 1995  Phases of  Product Development Most relevant to processes  in these phases"©Massachusetts Institute of Technology McManus- 032603  3 web.mit.edu/lean •  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 Mission  Concept Attributes Calculate Utility Develop System Model Estimate Cost Architecture Trade Space Define Design Vector Developing A Trade Space ©Massachusetts Institute of Technology McManus- 032603  4 web.mit.edu/lean What is an Architecture Trade Space? Number of Architectures Explored: 50488	Number of Architectures Explored: 50488	Km	DESIGN VARIABLES: The architectural trade parameters	•	 Orbital Parameters	–	 Apogee altitude (km)	–	 Perigee altitude (km)	–	 Orbit inclination	150-1100	150-1100	0, 30, 60, 90	•	 Physical Spacecraft Parameters	–	 Antenna gain	–	 communication architecture	–	 propulsion type	–	 power type	–	 delta_v	Total Lifecycle Cost	($M2002)	Each point is a specific architecture Assessment of the utility and cost of a large  space of possible system architectures X-TOS"•  Small low-altitude science mission"©Massachusetts Institute of Technology McManus- 032603  5 web.mit.edu/lean Using the Trade Space to Evaluate Point Designs Designs from traditional process"From Jilla, 2002 TPF"•  Terrestrial Planet Finder - a large astronomy system"•  Design space: Apertures separated or connected, 2-D/3-D, sizes, orbits"•  Images vs. cost"[Beichman et al, 1999]"©Massachusetts Institute of Technology McManus- 032603  6 web.mit.edu/lean Using Architecture Models to Understand Policy Impacts  B-TOS Case Study:  Probability of Success Impact of 1994 U.S. Space Transportation Policyfor a Minimum Cost Decision Maker0.980.9850.990.99510% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%B-TOS Architecture Probability of Launch Success (Lifecycle total)UtilityRestrictive U.S.-only Launch Policy Unrestrictive Launch PolicyAA'BB'E'C' CD'DEProbabilit  of Success"Utility"Cost of US Launch Policy:  B-TOS Case Study Using Min Cost Rule0.980.9850.990.99510 100 200 300 400 500 600 700 800Lifecycle Cost ($M)UtilityMin Cost US Min Cost ALLA B C D Utility"Co t"100% of B-TOS architectures have cost increase under restrictive launch policy for a minimum cost decision maker"98% of B-TOS architectures have increased launch probability of success under restrictive launch policy for a minimum cost decision maker"   Restri tive launch policy!   Unrestrictive launch policy!Policy increases cost!Policy increases launch probability of success!B-TOS"•  Swarm of small sats. doing observation"•  Utility for multiple missions"From Weigel, 2002 ©Massachusetts Institute of Technology McManus- 032603  7 web.mit.edu/lean Using Architecture Models to Consider Uncertainty Performance and Cost move differently for different architectures under uncertainty   Arch A Arch B  Arch B Arch A Cost 9.64 9.70 Pd 0.956 0.978   Arch B Arch A Cost 4.25 4.28 Pd 0.997 0.998  TechSat"•  Constellation of satellites doing obs vation of moving objects on the ground"•  Uncertainties driven by instrument performance/cost"From Walton, 2002 [Martin, 2000]"©Massachusetts Institute of Technology McManus- 032603  8 web.mit.edu/lean 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 0.980.9850.990.9951100 1000Lifecycle Cost ($M)UtilityA	E	D	C	B	Utility	Cost Most desirable  architectures	B-TOS""©Massachusetts Institute of Technology McManus- 032603  9 web.mit.edu/lean Questioning User Desires •  Best low-cost mission do only one job well •  More expensive, higher performance missions require more vehicles •  Higher-cost systems can do multiple missions •  Is the multiple mission idea a good one? Equatorial Utility	High Latitude Utility	A-TOS"•  Swarm of very simple satellites taking ionospheric measurements"•  Several different missions"©Massachusetts Institute of Technology McManus- 032603  10 web.mit.edu/lean 0.00500.001000.001500.002000.002500.003000.003500.004000.000.00 0.20 0.40 0.60 0.80 1.00Utility (dimensionless)Cost (M$)Low BipropMedium BipropHigh BipropExtreme BipropLow CryoMedium CryoHigh CryoExtreme CryoLow ElectricMedium ElectricHigh ElectricExtreme ElectricLow NuclearMedium NuclearHigh NuclearExtreme NuclearUnderstanding Limiting  Physical or Mission constraints Hits a “wall” of either physics (can’t change!) or utility (can) SPACETUG"•  Generalpurpose rbit transfer vehicles "•  Different propulsion systems and grappling/observation capabilities"•  Lines show increasing fuel mass fraction"©Massachusetts Institute of Technology McManus- 032603  11 web.mit.edu/lean 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? ©Massachusetts Institute of Technology McManus- 032603  12 web.mit.edu/lean ICE Process (CON with MATE) Thermal Structures Communication Command and Data Handling Configuration Power Propulsion Attitude Determination and Control Mission Systems ICE-Maker Server Cost Reliability MATE ICE Process Leader “Chairs” consist of computer tool AND human expert Verbal or online chat between chairs synchronizes actions Electronic communication between tools and server Key system attributes passed to MATE chair, helps to drive design session •  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 ©Massachusetts Institute of Technology McManus- 032603  13 web.mit.edu/lean SPACETUG Tug Family  (designed in a day) Bipropellant Cryogenic Electric – One way Electric – Return Trip Wet Mass: 11689 kg Wet Mass: 6238 kg Wet Mass: 997 kg Wet Mass: 1112 kg ©Massachusetts Institute of Technology McManus- 032603  14 web.mit.edu/lean Conceptual design details 0%1%16%5%3%2%21%0%52%ADACS (dry)C&DHLinkPowerPropulsion (dry)Structures & MechanismsThermalMating SystemPayloadPropellantPressurantPower System Mass BreakdownSolar array mass66%Battery mass19%PMAD mass9%Cabling mass6%Minimum efficiency 24.5 %Maximum efficiency 28.0 %Nominal temperature 28.0 CTemperature loss 0.5 %/deg CPerformance degredation 2.6 % / yearMinimum temperature 0.5 CMaximum temperature 85.0 CEnergy density 25.0 W / kgSolar array mass 150.6685167 kgTotal solar array area 9.965098159 m^2# of solar arrays 2 #Individual solar array area 4.98254908 m^2LEO Tender 1	mass summary	Detailed information can be 	drawn from subsystem sheets,	including efficiencies, degradations	temperature tolerances, and areas	Select solar array material: 6Triple Junction (InGaP/GaAs/Ge)©Massachusetts Institute of Technology McManus- 032603  15 web.mit.edu/lean 0	50	100	150	200	250	300	350	400	450	500	0	 0.2	 0.4	 0.6	 0.8	 1	Utility 	Cost 	Storable Biprop	Cryo	Electric	Nuclear	Biprop GEO tug	Electric GEO cruiser	Cryo GEO tug	SCADS	Electric GEO Tug	Trade Space Check The GEO mission is near the “wall” for conventional propulsion Electric 	Cryo 	Biprop	©Massachusetts Institute of Technology McManus- 032603  16 web.mit.edu/lean Changes in User Preferences Can be Quickly Understood 40 42 44 46 48 50 52 54 56 58 600.20.30.40.50.60.70.8Lifecycle Cost ($M)Utility40 42 44 46 48 50 52 54 56 58 600.20.30.40.50.60.70.8Lifecycle Cost ($M)UtilityOriginal Revised00.050.10.150.20.250.30.350.40.45Latency Latitude EquatorTimeLifespan AltitudeWeight Factors of each Attribute (k values)      Original RevisedUser changed preference weighting for lifespan Architecture trade space reevaluated in less than one hour X-TOS""©Massachusetts Institute of Technology McManus- 032603  17 web.mit.edu/lean MATE-CON: Emerging Capability User	Needs	Robust	Adaptable	Concepts	Months, not Years	ICE Conceptual Design MATE Architecture  Evaluation •  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.  

Introduction to MATE-CON

http://dspace.mit.edu/bitstream/1721.1/83444/1/PDM_0303_Mcman_MATECON.pdf

Introduction to MATE-CON

Abstract

Similar works

Full text

Available Versions

DSpace@MIT