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SysML Parametrics and Progress Towards Multi-Solvers and Next-Generation Object-Oriented Spreadsheets
Manas [email protected]
Dirk [email protected]
InterCAXwww.InterCAX.com
Frontiers in Design and Simulation Workshop 2008PSLM Center, Georgia Tech, Atlanta
May 14, 2008
v2
2Copyright InterCAX – All rights reserved
Contents
Complex systems & InterCAX technology
SysML parametrics
Illustrative scenarios– LittleEye: An unmanned aerial vehicle system– Financial projections system
Lessons learnt
Next-generation spreadsheets?
3Copyright InterCAX – All rights reserved
Complex Systems Mechatronics / Integrated Electronics
Product Enclosure
External Interfaces
Printed Circuit Assemblies(PCAs/PWAs)
Die/Chip Package
Packaged Part
InterconnectAssembly
Printed Circuit Substrate (PCBs/PWBs)
Die/Chip
Product Enclosure
External Interfaces
Printed Circuit Assemblies(PCAs/PWAs)
Die/Chip Package
Packaged Part
InterconnectAssembly
Printed Circuit Substrate (PCBs/PWBs)
Die/Chip
Product Enclosure
External Interfaces
Printed Circuit Assemblies(PCAs/PWAs)
Die/Chip Package
Packaged Part
InterconnectAssembly
Printed Circuit Substrate (PCBs/PWBs)
Die/Chip
www.ap210.org
4Copyright InterCAX – All rights reserved
Tsunami detection system
National Oceanic and Atmoshpheric Administration
http://www.ndbc.noaa.gov/dart/dart.shtml
Dec 24, 2006 Tsunami
150,000 dead, millions injured
Click here
A Complex System
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Complex SystemsKey Characteristics
Sub-systems & Interactions – type & number
Stakeholders
Methods, models, and software tools
Lifecycle phases– Requirements– Design– Manufacturing / Realization– Operation
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System Analyses
CAE Solvers
Math Solvers
…System Definition
CAD Modelers
System Modelers
…
FEA Solvers (ABAQUS, ANSYS,…)CFD Solvers (Fluent,…)DEVS Solvers (ARENA,…), …
MatlabMathematicaOpenModelica, …
MCAD (UGS-NX, CATIA, Pro/E,…)ECAD (Zuken CR500, MGC BoardStation,…)
SysML (MagicDraw, Artisan Studio, E+, Rhapsody,…)
Modeling and simulation technology
7Copyright InterCAX – All rights reserved
Contents
Complex systems & InterCAX technology
SysML parametrics
Illustrative scenarios– LittleEye: An unmanned aerial vehicle system– Financial projections system
Lessons learnt
Next-generation spreadsheets?
8Copyright InterCAX – All rights reserved
SysML Parametrics
SysML– OMG standard (www.omgsysml.org)– INCOSE driven– UML for SysML
Parametrics– Relationships between model parameters– Fine-grained– Declarative– Reuse of relationships: Constraint Block
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LittleEye: An Unmanned Aerial Vehicle
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Key Questions for LittleEye Model
Miles scanned by the LittleEye system
What limits the number of miles scanned?
Change in number of miles scanned with change in– Number of UAV / planes– Amount of fuel– Monitoring crew
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Road Scanner System ProblemLittleEye UAV
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Demo of LittleEye example
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LittleEye SysML ModelVarious Diagram Views
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Solving LittleEye SysML ParametricsParaMagic Browser Views
Instance 1 - Before Solving Instance 1 - After Solving
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Contents
Complex systems & InterCAX technology
SysML parametrics
Illustrative scenarios– LittleEye: An unmanned aerial vehicle system– Financial projections system
Lessons learnt
Next-generation spreadsheets?
16Copyright InterCAX – All rights reserved
Financial Projections System
Key questions:– Given projected sales, expenses and financing, what is the
financial position of the company at the end of 3 years?– Given the desired financial position at the end of 3 years,
what are the required sales, expenses and financing?– …
Three YearCorporateFinancial
Projections
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Demo of Financial Projections System
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Financial Projections SysML ModelVarious Diagram Views
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Solving Financial Projections SysML ParametricsParaMagic Browser Views
Instance 1 - Before Solving Instance 1 - After Solving
20Copyright InterCAX – All rights reserved
Contents
Complex systems & InterCAX technology
SysML parametrics
Illustrative scenarios– LittleEye: An unmanned aerial vehicle system– Financial projections system
Lessons learnt
Next-generation spreadsheets?
21Copyright InterCAX – All rights reserved
Lessons Learnt
SysML Parametrics is powerful, flexible, and easy-to-learn, with wide application beyond “systems engineering”
Control of causality is a very important feature for fully exploiting the model.
Areas for improvement– display of large arrays of instance data– inefficiency in repetitive actions– model completeness, redundancy, over/under-constrained– interoperability
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Next-Generation Spreadsheets?
Mental calculation Time
Parametric models– Visible model structure– Flexible control and
causality– Multiple solvers– Multiple data sources Spreadsheets
– Equations– Macros– Visualization
Written tables– Memory– Collaboration
