Capturing Design Process Information and Rationale to Support Knowledge-Based Design-Analysis Integration
National Institute of Standards and Technology
With the increase in complexity of technical products and a trend towards multi-locational product development teams, an efficient and effective framework to support the design of technical artifacts must be developed. Despite the advances in computing and computer supported engineering tools, significant gaps still exist between formal tools that aid engineering design and analysis activities throughout the product development process. Advances in product modeling, design process modeling, and knowledge-based engineering offer opportunities to develop design support systems to bridge the gaps associated with design-analysis integration (DAI).
In this effort the National Institute of Standards and Technology (NIST) and Georgia Tech (GIT) will collaborate to apply and develop technologies to support computer-based design-analysis integration support systems. Initial focus will be on the development and refinement of product models and design process models. These models should support a high level of associativity between the design process and the corresponding product information generated. Additional work will be on the integration of product and process models to support knowledge-based engineering frameworks (EFWs). The knowledge captured can be used to aid design engineers in the selection of or usage of appropriate analysis models or the steps that must be followed to create an analysis model. Long-range goals support the development of computer-based design environments that incorporates both product and process knowledge in collaboration with design engineers to aid in the entire product development process.
Expected benefits include capturing and reusing product knowledge throughout the development process. Such techniques will reduce the time and effort to create appropriate analysis models. Additional benefits will arise from a consistent framework by which to capture product development information in a distributed design environment. These capabilities will lead to decreasing or eliminating gaps associated with design-analysis integration, a major research effort at NIST.
Design-analysis integration (DAI) research.
Mocko, G., R. Malak, C. Paredis, and R.S. Peak. A Knowledge Repository for Behavioral Models in Engineering Design. in ASME 2004 International Design Engineering Technical Conferences and the Computers and Information in Engineering Conference. 2004. Salt Lake City, UT.
Mocko, G., J. Panchal, M. Fernandez, C.J.J. Paredis, and R.S. Peak. Towards Reusable Knowledge-Based Idealizations for Rapid Design and Analysis. in 45th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference. 2004. Palm Springs, CA.
RS Peak, RM Burkhart, SA Friedenthal, MW Wilson, M Bajaj, I Kim (2007) Simulation-Based Design Using SysML—Part 1: A Parametrics Primer. INCOSE Intl. Symposium, San Diego.
RS Peak, RM Burkhart, SA Friedenthal, MW Wilson, M Bajaj, I Kim (2007) Simulation-Based Design Using SysML—Part 2: Celebrating Diversity by Example. INCOSE Intl. Symposium, San Diego.
Bajaj M, Peak RS, Paredis CJJ (2007) Knowledge Composition for Efficient Analysis Problem Formulation - Part 1: Motivation and Requirements. Paper DETC2007-35049, Proc ASME CIE Intl Conf, Las Vegas.
Bajaj M, Peak RS, Paredis CJJ (2007) Knowledge Composition for Efficient Analysis Problem Formulation - Part 2: Approach and Analysis Meta-Model. Paper DETC2007-35050, Proc ASME CIE Intl Conf, Las Vegas.