INCOSE MBSE Grand Challange

Report
INCOSE MBSE Grand Challenge
Space Systems Working Group Entry and MBSE at JPL
Presentation to Frontiers Workshop 2008
Christopher L. Delp
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California, U.S.A.
[email protected]
Space Systems Working Group
Team
• International Group of Engineers
• Commercial and Government
• Students/Academic Team
– MIT
– Georgia Tech
SSWG Team
Carlee Bishop
Chris Delp
Colette Wilklow
Craig Peterson
Dave Kaslow
Deborah A. Cowan
Harvey M. Soldan
James R. Scott
Jeff Estefan
John Brtis
John Keesee
Kenneth Meyer
Leo Hartman
Mahantesh Hiremath
Marc A. Sarrel
Mitch Ingham
Olivier de Weck
Ross Jones
Stephen Piggott
Sima Lisman
Lisa Weeks
Lisa Weeks
James Andary
Darryl Lakins
Elizabeth O'Donnell
Walker, Loren M
Yuuji Nishihara
Seiji Kamiyoshi
Evan Anzalone
Cin-Young.Lee
Kimberly A. Simpson
Alicia R. Allbaugh
Kyran J. Owen-Mankovich
Caley Burke
Peter Waswa
Chase Cooper
Abe Grindle
Henry Hallam
William Symolon
Gautier Brunet
Debarati Chattopadhyay
Ben Renkoski
Kyle Volpe
Brent Tweddle
Michael Lack
Ariane Chepko
Michael Newman
Daniel Kettler
Philip Johnson
Frank Fan
Misha Leybovich
Theo Seher
Lauren Viscito
Isaac Asher
MBSE Challenge Objectives
• Demonstrate solution to “Challenging”
problems using MBSE
– real world problem domain
– non-trivial, broad application
– shareable (e.g., unclassified, non-proprietary)
Approach
• FireSat Example (Space Mission Analysis
and Design)
– Realistic and Sharable
– Use example as documented design
• Meet and Model
• JPL developed State Analysis
• INCOSE Object Oriented System
Engineering Methodology (OOSEM)
FireSat Documented Examples
• requirements
From Space Mission Analysis and Design
(SMAD), Third Edition, by Wiley J. Larson
and James R. Wertz (editors).
FireSat Documented Examples
From Space Mission Analysis and Design
(SMAD), Third Edition, by Wiley J. Larson
and James R. Wertz (editors).
FireSat in SysML
• Communication
– Requirements, behavior and structural elements are visible and
traceable
– Rich problem statement
– Product oriented
• Relationships
– Opaque in text
– Rich in Model
– Standardized (no legend or invention required)
• Reusable
– Model packages can be exported and imported to other models
Use cases
Requirements
Mission Context
Fire Hunting
What is State Analysis?
• A model-based systems engineering methodology
– Based on familiar principles from control theory
– Complementary to the functional decomposition approach
– Intended to help address the complexity challenge
• It provides a methodical and rigorous approach for:
state-based behavioral modeling
Capturing mission
objectives in detailed
scenarios motivated by
operator intent
goal-directed operations engineering
Modeling behavior in
terms of system state
vars & the relationships
between them
Describing the methods
by which objectives
will be achieved
state-based software design
State Effects
act GoalNetw orks [GoalNetw orks]
Goal Elaboration
«macro goal»
BurningProces s
«know ledge goal»
fire presence
Payloa d
Pointing
Spectrum
«allocateActivityPartition»
«allocateActivityPartition»
«allocateActivityPartition» «allocateActivityPartition»
Identify FireCandidate
«know ledge goal»
spectrum state
«maintenance goal»
CandAtmoThresholdConstraint
«maintenance goal»
DesiredPointing
«transition go...
DesiredPointing
Complexity Controlled
Through Simplification
• MBSE provides a centralized repository for
mission information.
• A modeling tool can present a project element
(e.g., a requirement, a subsystem) and
associated relationships
– Avoid searching for information distributed over
multiple documents.
• This greatly simplifies creating and changing
project elements and propagating changes to
related elements.
Mars Science Lab
Mars Science Lab
MSL Tactical Timeline
• Mission Operations
– Complex human organization
– Tasks and timing are critical
• Operating large rover
• 10 instruments
– Sequence drawings have proven popular
• Capture current artifacts
• Back fill model
• Drive with model
GDS Modeling
• New GDS Application
• System Model of GDS
– Understand scope of application
– Deployment for ATLO and Operations
– Future capabilities
• Service Oriented Architectures
• New applications
• New mission requirements
Successes
• Demonstrating System Engineering using
models for Space Systems
– Built a dedicated team
• Models benefits over documents
• Exposing a variety of methods, techniques
and artifacts
• Participation has bred viral interest
Challenges
• Collaboration and Interchange
– Interfacing models
– Moving between tools
– Capturing portions from other tools
• If it ain’t broke…
– Process integrity
• Training … not just in SysML
Looking Forward
• Modeling sub-systems in detail
• Modeling Physics and Analysis
– Integrating MIT/GaTech student team
analysis model
• Executing models
• Continuing to add individuals interested in
Space Systems!
World of Models
• System models interchangeable and
flexible
• Vast libraries of engineering and physics
models
• System engineering will become a nimble
and flexible organization
• More time spent engineering
Back Up Slides

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