1 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 Systems Realization Laboratory 7th Annual PDE Conference at Georgia Tech Georgia Institute of Technology Atlanta, Georgia April 19 – 22, 2005

2 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

3 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

4 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

5 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.

6 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

7 Product Data Exchange-Standard Product Models Source: Relationships between design shape, analysis shape, and additional analysis parameters are captured

8 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

9 Product Data Exchange – Analysis Templates Solid Modeler Materials Database Fasteners Database Design ApplicationsAnalysis Applications FEA-Based Analysis Formula- Based Analysis Combine information Add reusable multifidelity 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,

10 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

11 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

12 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

13 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

14 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!

15 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

16 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

17 Questions?

18 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 Muster, D. and F. Mistree, (1988) The Decision Support Problem Technique in Engineering Design. International Journal of Applied Engineering Education, 4(1): p 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, 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.