capturing the relationships between design problems and analysis models
DESCRIPTION
Capturing the Relationships between Design Problems and Analysis Models. Gregory Mocko, Jitesh Panchal, and Farrokh Mistree Systems Realization Laboratory Georgia Institute of Technology Atlanta, Georgia 30332-0405. 7th Annual PDE Conference at Georgia Tech Georgia Institute of Technology - PowerPoint PPT PresentationTRANSCRIPT
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Capturing the Relationships between Design Problems and
Analysis Models
Gregory Mocko, Jitesh Panchal, and Farrokh Mistree
Systems Realization LaboratoryGeorgia Institute of TechnologyAtlanta, Georgia 30332-0405
Systems Realization Laboratory
7th Annual PDE Conference at Georgia TechGeorgia Institute of TechnologyAtlanta, GeorgiaApril 19 – 22, 2005
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Systems Realization Laboratory
Systems Realization Laboratory
Research Focus
Objective Capture the linkages between design problems and support
models Decision models, design models, and analysis models
Overarching Question How can product-related information and the relationships
between design problem and analysis models be captured? Approach
Formalize the information transformations between support models in decision-based design
Characterize the information associated with engineering design decisions
Develop a representation of the linkages between design problems and analysis models
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Systems Realization Laboratory
Systems Realization Laboratory
Design-Analysis Integration Problem
Design-analysis integration (DAI) is the seamless integration between design and analysis perspectives by capturing the relationships between computer-based design and analysis models [Peak and co-authors 1998]
The design/structural analysis integration problem is typified by the requirement to share geometric shape and analysis information in an iterative environment [Hunten 1997]
•Why do we link design and analysis?•It is not just a matter of sharing data•We need to link design and analysis to support design decision making•Additional information must be shared to support design decisions
•Why do we link design and analysis?•It is not just a matter of sharing data•We need to link design and analysis to support design decision making•Additional information must be shared to support design decisions
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Systems Realization Laboratory
Systems Realization Laboratory
Design Information Integration – Missing Link
Analysis(e.g., FEA)
Design(e.g., CAD)
Configuration control of design and analysis (AP209)
Fine grained associativities (MRA/COBs)
…
Identify design decisions based on design requirements Compare analysis results
with design requirements
Design Requirements
Design Iteration
Design Problem (Decision)
Characterized by a set of responses that are functions of a common set of design variables, constraints, and bounds specified by the designer and analyst
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Systems Realization Laboratory
Systems Realization Laboratory
Research Foundation - Background
Decision-Based Design (DBD) [Mistree et. al 1990] Principle role of designer is to
make decisions Decisions serves as markers of
progress and information transformations
Decisions serves as units of communication that involve hierarchical decision making
Decision Support Problem (DSP) Technique [Muster et. al 1988] A specific instantiation of DBD Supports the human designer Domain-independent constructs
for modeling design processes
Information models and knowledge representation for modeling design information transformations
Interface for linking computer-based design and analysis models
Increase the use of standard product models to support product data exchange
Overview Research Opportunities
•RQ: How can product-related information and the relationships between design problem and analysis models be captured?•RH: Decision constructs serve as information integrators between design and analysis models.
•RQ: How can product-related information and the relationships between design problem and analysis models be captured?•RH: Decision constructs serve as information integrators between design and analysis models.
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Systems Realization Laboratory
Systems Realization Laboratory
Product Data Exchange-Standard Product Models Standard product models
Product data must be exchanged between design support software
A neutral mechanism for exchanging product data Product data exchange is a required technology
STEP AP203/AP209 Addresses interoperability of product models
between CAD and FEA applications Captures the relationships between design
specification and analysis specification Captures shape, analysis control, analysis output Support design and analysis geometry definitions Configuration control and management of analysis
STEP
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Systems Realization Laboratory
Systems Realization Laboratory
Product Data Exchange-Standard Product Models
Part1
Part1_version1
Nominal Design Shape1
Analysis_DesignVersion
Relationship1Analysis1_Version1 Analysis1
FEM1
Idealized Analysis Shape1
Next_Higher_Assembly1
Part1_version1 Analysis2_Version1 Analysis2
FEM2
Idealized Analysis Shape2
Analysis_DesignVersion
Relationship1
Assembly1
Analysis2_Version2
FEM3
Idealized Analysis Shape3
Analysis_DesignVersion
Relatoinship3
Step 1 Step 2
Step 3
Step 4
Part1
Part1_version1
Nominal Design Shape1
Analysis_DesignVersion
Relationship1Analysis1_Version1 Analysis1
FEM1
Idealized Analysis Shape1
Next_Higher_Assembly1
Part1_version1 Analysis2_Version1 Analysis2
FEM2
Idealized Analysis Shape2
Analysis_DesignVersion
Relationship1
Assembly1
Analysis2_Version2
FEM3
Idealized Analysis Shape3
Analysis_DesignVersion
Relatoinship3
Step 1 Step 2
Step 3
Step 4
Source: http://pdesinc.aticorp.org/pilots/engineering.html
Relationships between design shape, analysis shape, and additional analysis parameters are captured
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Systems Realization Laboratory
Systems Realization Laboratory
Product Data Exchange – Analysis Templates Analysis templates
MRA captures several aspects in design-analysis integration including
• automation of routine analyses, • the representation of design and analysis associativity and of the
relationships among the models, and • the support of various analysis models throughout the life cycle of
the product Address the need to capture fine-grained associativities between
engineering CAD and CAE models Realized through the constrained object (COB) information modeling
language Templates enable quick and efficient analysis integration when product
variants are limited to parametric changes in design specifications
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Systems Realization Laboratory
Systems Realization Laboratory
Product Data Exchange – Analysis Templates
SolidModeler
MaterialsDatabase
FastenersDatabase
Design Applications Analysis Applications
FEA-BasedAnalysis
Formula-BasedAnalysis
Combineinformation
Add reusablemultifidelity
idealizations
Analyzable Product Model(APM)
...
Support multidirectionality
•Coordination of various data sources•Linkages between design and analysis parameters•Enables information to be shared between CAD and CAE tools
•Coordination of various data sources•Linkages between design and analysis parameters•Enables information to be shared between CAD and CAE tools
Source: Peak, R. S.; Fulton, R. E.; Nishigaki, I.; Okamoto, N. (1998) Integrating Engineering Design and Analysis Using a Multi- Representation Approach. Engineering with Computers, Volume 14 No.2, 93-114.
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Systems Realization Laboratory
Systems Realization Laboratory
Product Data Exchange - Summary Benefits
Design and analysis information must be exchanged Relationships between product data and analysis data
must be captured A common “language” is needed to integrate design tools
What is Missing? Data exchange between design and analysis must be in
the context of design decision making Design process and information transformations must be
captured Current efforts focus on product-related information
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Systems Realization Laboratory
Systems Realization Laboratory
Approach – Product and Process Formalization of design decisions
Develop a knowledge representation of engineering design decisions
Development of interface Specification of information exchange in design and
analysis to facilitate access to product data “Plug-and-play” approach for linking design and analysis
models and design support tools
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Systems Realization Laboratory
Systems Realization Laboratory
ModelCenter Implementation – Design Problem
Formulate decisions and organize design and analysis models in light of design requirements Capture the decision
related information Approach for
allocating design requirements
Analysis(e.g., FEA)
Design(e.g., CAD)
Configuration control of design and analysis (AP209)
Fine grained associativities (MRA/COBs)Application of analysis
information on geometry (Simmetrix)
Identify design decisions based on design requirements
Design Requirements
Design Problem
(Decision)
Design Iteration
Compare analysis results with design requirements
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Systems Realization Laboratory
Systems Realization Laboratory
ModelCenter Implementation – Models
Analysis(e.g., FEA)
Design(e.g., CAD)
Configuration control of design and analysis (AP209)
Fine grained associativities (MRA/COBs)Application of analysis
information on geometry (Simmetrix)
Identify design decisions based on design requirements
Design Requirements
Design Problem
(Decision)
Design Iteration
Compare analysis results with design requirements
Leverage standardized product models
Integrate design tools and product data into the design decision
Reuse design and analysis models
Interfaces / wrappers are needed to integrate standards models
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Systems Realization Laboratory
Systems Realization Laboratory
ModelCenter Implementation – Linkages
Analysis(e.g., FEA)
Design(e.g., CAD)
Configuration control of design and analysis (AP209)
Fine grained associativities (MRA/COBs)Application of analysis
information on geometry (Simmetrix)
Identify design decisions based on design requirements
Design Requirements
Design Problem
(Decision)
Design Iteration
Compare analysis results with design requirements
Capture the linkages between design and analysis parameters in the context of a design decision
Design-analysis integration has meaning in the context of a design decision!
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Systems Realization Laboratory
Systems Realization Laboratory
ModelCenter Implementation - Discussion Information exchange between design and analysis is
relevant in the context of design decisions Additional information must be captured in design and
analysis models Constraints and bounds on system variables and
responses Decision-related information Relationships/transformations between variables
Shortcomings Does not rely on standardized product models Decision templates & interface are developed for specific
problems• Generalized decision models and interfaces are
needed
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Systems Realization Laboratory
Systems Realization Laboratory
Closure Design and analysis information must be exchanged in the context of
design decision making A standardized information model is needed to capture decision-
related information Engineering decision enable the design process to be modeled
Decisions serve information integrators Decisions capture the information transformation in the design
process A standardized interface is needed between design and analysis models
Towards “plug-n-play” integration and information exchange
A look to the future… A standardized models that captured process will enhance PLM Conventional tools address what is the design information, not how it
was created Decision-based design provides a means for modeling design
processes
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Systems Realization Laboratory
Systems Realization Laboratory
Questions?
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Systems Realization Laboratory
Systems Realization Laboratory
References Fenves, Steven, Choi, Young, Gurumoorthy, Balan, Mocko, G, Sriram,
R.D. , (2003) Master Product Model for the Support of Tighter Integration of Spatial and Functional Design, NISTIR 7004
Hunten, K.A., (1997) CAD/FEA Integration with STEP AP209 Technology and Implementation
Mistree, F., W.F. Smith, B.A. Bras, J.K. Allen, and D. Muster, (1990) Decision-Based Design: A Contemporary Paradigm in Ship Design. Transactions, Society of Naval Architects and Marine Engineers, 98: p. 565-597.
Muster, D. and F. Mistree, (1988) The Decision Support Problem Technique in Engineering Design. International Journal of Applied Engineering Education, 4(1): p. 23-33.
Peak, R. S.; Fulton, R. E.; Nishigaki, I.; Okamoto, N. (1998) Integrating Engineering Design and Analysis Using a Multi- Representation Approach. Engineering with Computers, Volume 14 No.2, 93-114.
Wilson, M.W., The Constrained Object Representation for Engineering Analysis Integration, in G.W. Woodruff School of Mechanical Engineering. 2000, Georgia Institute of Technology: Atlanta, GA.
http://pdesinc.aticorp.org/pilots/engineering.html