Characterizing Fine-Grained Associativity Gaps: A Preliminary Study of
CAD-CAE Model Interoperability
Peak, R. S. (2003), Characterizing Fine-Grained Associativity Gaps: A Preliminary Study of
CAD-CAE Model Interoperability, 2003 Aerospace Product Data
Exchange (APDE) Workshop,
NIST, Gaithersburg, Maryland.
fine-grained associativity gap, design-analysis integration, CAD-CAE
interoperability, knowledge-based engineering (KBE), multi-representation
architecture (MRA), constrained object (COB)
This presentation describes an initial study towards characterizing model
associativity gaps and other engineering interoperability problems. Drawing on
over a decade of X-analysis integration (XAI) research and development, it uses
the XAI multi-representation architecture (MRA) as a means to decompose the
problem and guide identification of potential key metrics.
A few such metrics are highlighted from the aerospace industry. These include
number of structural analysis users, number of analysis templates, and
identification of computing environment components (e.g., number of CAD and CAE
tools used in an example aerospace electronics design environment).
One problem, denoted the fine-grained associativity gap, is highlighted in
particular. Today such a gap in the CAD-CAE arena typically requires manual
effort to connect an attribute in a design model (CAD) with attributes in one of
its analysis models (CAE). This study estimates that 1 million such gaps exist
in the structural analysis of a complex product like an airframe. The labor cost
alone to manually maintain such gaps likely runs in the tens of millions of
dollars. Other associativity gap costs have yet to be estimated, including over-
and under-design, lack of knowledge capture, and inconsistencies.
Narrowing in on fundamental gaps like fine-grained associativity helps both to
characterize the cost of today’s problems and to identify basic solution needs.
Other studies are recommended to explore such facets further.
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